Metadata on Crossref

Schema 5.5 now available: adding CRediT, new record types for blogs and posters, and more

Patricia Feeney — Thu, 09 Jul 2026 00:00:00 +0000

Research is rarely limited to a single contributor performing a single role. Behind every research output are people contributing in various ways: software development, data analyses, methodology design, and much more. Often, the same person contributes in several of these ways. Until now, Crossref metadata could only capture part of that picture, but this is changing with Schema 5.5.

Crossref Schema 5.5 includes several improvements across different content types, but its most significant enhancement is the expanded support for contributor roles through the introduction of multiple roles per contributor, option to specify the corresponding author, and compatibility with the CRediT (Contributor Roles Taxonomy): a community-owned taxonomy of 14 contributor roles, which has been adopted and made available in multiple languages.

These enhancements allow members to describe research contributions in much greater detail, creating richer metadata that better reflects how research is actually produced, and supporting greater accountability and more comprehensive research assessment.

If your workflow already distinguishes between different kinds of contributions, Schema 5.5 gives you a way to record that detail more accurately using the CRediT taxonomy values. CRediT can be adopted gradually, where it fits your editorial or production workflow.

Figure 1: Until now, contributors could be assigned a single contributor role using Crossref’s existing contributor role vocabulary. In Schema 5.5, members can indicate that the same contributor was responsible for different roles, such as corresponding author; writing: reviewing and editing; and data curation.

Existing deposits remain fully supported, and members can continue using the current contributor role attribute while planning implementation of the new repeatable role type element. For our members, who have been using CRediT in their workflows already, as ever – we encourage updating your metadata when practicable.

Why this update is kind of a big deal

This update gives more accurate credit to all of the people behind research outputs. Crossref vocabulary includes roles that aren’t recognised in CRediT, and vice versa. Capturing richer contributor metadata recognises contributions that may not be visible in a single author line and improves transparency around how research is produced, thereby enabling downstream systems to interpret that information more reliably. The update also offers better interoperability with CRediT, which is well recognised across the scholarly ecosystem.

Figure 2: Schema 5.5 is an expansion of Crossref contributor metadata. Members can describe contributors using Crossref’s existing contributor role vocabulary, as well as the internationally recognised CRediT taxonomy.

In turn, this strengthens metadata reuse across repositories, discovery services, funders, institutions and other infrastructure providers; and supports evaluation, reporting and discovery workflows. Better contributor metadata strengthens the connections that make up the Research Nexus.

What else is included in Schema 5.5?

Beyond the expanded contributor support, Schema 5.5 includes several additional enhancements across the metadata schema.

1. Updates to report series metadata

Support has been added for metadata elements that were previously missing from report series records, including Crossmark, funding, and licence information.

2. Posted content improvements: now including blogs and posters

Posted content includes preprints, eprints, and other types of content that have been posted to a stewarded host platform. We’re all about persistence, so it’s vital that everything registered with us be maintained. Note that accepted manuscripts are not considered posted content. Schema 5.5 refreshes posted content sub-types by introducing blog and poster.

At the same time, we are “retiring” working paper, dissertation, and report from posted-content sub-types. Over time, these have been developed into separate record types that benefit from richer, dedicated schemas.

Finally, archive locations can now also be included for posted content records.

3. Expanded archive support

A new archive location, CINES, has been added to the list of supported archive providers.

4. Clinical trial metadata across more record types

Clinical trial information is no longer limited to journal articles and conference papers. Schema 5.5 extends support across additional content types, including books, datasets, dissertations, reports, posted content, standards, and pending publications.

Schema adoption

Taken together, the updates in our latest schema support more holistic recognition of contributions to the research and its communication, as well as greater accountability and integrity in related processes.

To support gradual adoption, Schema 5.5 maintains backwards compatibility with existing deposits. Members can continue using the current contributor_role attribute while preparing to implement the new repeatable role element. We have prepared a migration guide to help members transition to Schema 5.5.

As you prepare to adopt Schema 5.5, we encourage members to include contributor roles whenever they are available from editorial workflows and to use recognised vocabularies consistently, including CRediT roles where appropriate.

New Crossref Service Providers program ready for applications

Madhura Amdekar — Tue, 23 Jun 2026 00:00:00 +0000

We are pleased to announce the re-launch of the Crossref Service Providers program. From today, we are accepting applications from organisations providing tools for metadata registration to Crossref members. Participation in this program is free and the application involves an accreditation process to determine eligibility and the appropriate participation tier.

As a membership organisation, Crossref supports its members to provide rich and complete metadata which facilitates integrity judgements, increases discoverability, linking among scholarly objects and activities, and improves transparency. Service providers are key collaborators in this work because they enable our members to adopt better metadata practices.

We ran an earlier version of this program which was paused in 2022 for review. We are now pleased to reintroduce the program as a new structure for our collaboration with service providers. If you are an organisation that provides tools that enable record registration for Crossref members, we invite you to apply for the program via this application form.

Scope and goals of the program

Crossref service providers have historically included organisations such as hosting platforms, manuscript submission systems, grant management systems, XML and metadata providers, and other general publishing services organisations that work with Crossref members to create, register, and/or display metadata on their behalf. As we re-launch the program, the initial focus will be purely on service providers that enable content registration for Crossref members. In the future, and based on community feedback, the program may expand to include additional types of service providers.

The primary goal of the program is to enable registration and maintenance of high-quality and rich metadata by Crossref members, contributing to a more complete research nexus. We aim to achieve this through a closer collaboration between Crossref and service providers. Participants of the Service Providers program will make reasonable efforts to accommodate any changes made to the Crossref schema, promote best metadata practices as per Crossref Participation Reports, and share information about the services that they are able to integrate and provide to their clients.

Participants of the Service Providers program will commit to:

Staying up to date with Crossref services and policies, including participation in ongoing meetings and communications.
Providing feedback to Crossref on our services.
Giving Crossref information about their client service offerings and workflows, including metadata delivery options and test accounts.
Promoting metadata best practices as represented in Crossref Participation Reports.
Making reasonable efforts to accommodate changes to the Crossref schema and services.
Ensuring that their clients’ content and landing pages are kept up to date (including ensuring that clients’ DOIs resolve to active landing pages at all times).

Participants of the Service Providers program will benefit from learning about changes and new services ahead of time coupled with regular updates about our services and policies. We will also list all accredited service providers on our website, and all participants will receive a digital Crossref badge to display on their website. We look forward to providing participants with credentials to access our test system for testing integrations, and providing training where necessary.

Service Providers program tiers

Better metadata support helps improve discoverability, transparency, and the integrity of the scholarly record. We developed two Service Providers program tiers in order to signal to the community the richness of metadata and support these organisations offer to Crossref members. At the Basic Tier, participants are able to provide members with the core metadata support, while the Advanced Tier includes additional features that enable richer metadata support for Crossref members – the details are laid out below.

Application and accreditation process

Applications to join the program are being accepted via this form. The application form asks for basic organisational information including your contact details and the services you provide to Crossref members. You will then be asked about your organisation’s technical capabilities and workflows, including your ability to support metadata registration, manage multiple client prefixes, and comply with the display guidelines for Crossref DOIs. The form also includes questions about metadata support, such as whether your platform can facilitate the deposit and update of recommended and optional metadata elements, which schema versions you are able to support, and the provision of alternative metadata delivery options.

We recommend reviewing the questions to ensure that the appropriate technical and operational requirements can be met before beginning the application. If you require clarification on any of these questions, please do not hesitate to reach out to us.

Basic Tier requirements and questions

Enable Crossref members to register content and deposit required metadata, as per Crossref’s required, recommended and optional metadata.
Ability to support and display multiple client prefixes.
Ensure continuous resolution of clients’ DOIs following platform migrations.
Provide platform support to members.
Comply with the display guidelines for Crossref DOIs.
Maintain communication channels with Crossref and/or participate in trainings.
Notify Crossref when large-scale metadata updates are planned (i.e. when you are aware of daily updates exceeding 500,000 DOIs updated by a single client (Crossref member)).
Use Crossref members’ credentials to register content on their behalf.
Follow industry best practices for credentials security and account protection.

Advanced Tier requirements and questions

In addition to meeting all the Basic Tier requirements, applicants must confirm whether they:

Provide alternative metadata delivery options.
Support recommended and optional metadata elements.
Support latest schema versions (5.3.1 and above).

Following a review of application forms, we will schedule accreditation calls from August 2026 onward that will involve demonstrations of the required functionality and an assessment of the applicant’s ability to meet the requirements of the program. This process will help determine the appropriate tier.

We ask that participants on the Service Providers program renew their accreditation at the beginning of each calendar year, starting in 2028. This will entail the submission of a re-accreditation form which may contain new requirements such as support for newer schema versions.

We look forward to working more closely with service providers to support richer metadata and seamless infrastructure workflows.

Building better connections: the story of Crossref's metadata development

Patricia Feeney — Thu, 18 Jun 2026 00:00:00 +0000

Three years ago, we asked our members what they needed from Crossref’s metadata. We received confirmation that we were going in the right direction, as well as some new ideas to explore. This helped set the course for our metadata development work since then, and continues to guide where we’re headed next.

Every metadata update we make is driven by the same set of priorities: supporting metadata that reflects our organizational truths, focusing on what metadata our members can actually provide, and aligning with best practices, vocabularies, and standards that our wider scholarly community has established. More recently our Metadata Advisory Group has helped us explore both the minutia of working with metadata as well as larger ideas around the value and impact of the metadata we support.

What We’ve Accomplished

Our schema 5.4 update included several new or expanded types of metadata. First, citation metadata can now be labelled with a publication type. This means when a work cites an article, a preprint, a dataset, or software, that distinction is clear, helping make citations without an accompanying DOI metadata record easier to identify. Second, version information is now supported across all record types, giving the scholarly record a more precise handle on exactly which version of a work is being described.

We’ve also made two meaningful improvements to how funding relationships are captured. ROR IDs are now supported as funder identifiers in both our standard metadata schema and our grants-specific schema. Also, Grant DOIs can now be explicitly identified within funding metadata, making it possible to draw clearer lines between research outputs and the grants that supported them.

What’s happening now

A significant update is nearly here. Schema 5.5 will expand contributor metadata to support multiple roles per contributor, and will introduce support for CRediT — the ANSI/NISO taxonomy for contributor roles. This means that an individual’s complete contribution to a research output can finally be described in our metadata, rather than flattened into a single role or omitted entirely. The schema isn’t released yet, but the final version of the XML schema is available in our GitLab repository for those who want to get a head start.

We’ll next begin implementation work for a new Grants schema (0.3.0). This update will remodel investigator names to include a new role (beneficiary) as well as an organizational grant recipient, making it possible to include recipient info for grants given to organizations. Grant records include project metadata, so this update will also include support for RAiD, a persistent identifier for projects. The XML schema for this update is also available in a GitLab repository.

What’s up next

Our next planned major update will build substantially on the contributor work in version 5.5. In the next version (6.0) we will remodel names to expand our current limited structure to support a variety of name types as well as alternate names. We’ll also expand the contributor identifiers we collect to include ISNI and Wikidata identifiers, better supporting contributors for whom an ORCID is not possible. Our organizational contributor will be remodelled as well to include organization-level identifiers like ROR.

We’ll also introduce statements to Crossref metadata. Statements will allow members to include free-text statements including funding acknowledgements, ethics declarations, AI usage disclosures, and other important contextual information that doesn’t fit neatly into structured fields.

Other updates include expanding our support for abstracts encoding beyond JATS to include ONIX, BITS, and a generic markup option, and implementing better in-schema validation to avoid surprises at the time of deposit.

Progress means letting go of the past. We’re planning to deprecate all schemas prior to version 5.3.1 by the end of 2027, to be carried out in phases as outlined in our deprecation blog post. This is a necessary step to keep our infrastructure sustainable and to ensure members are working with schemas that reflect current capabilities and standards.

Looking further ahead

Beyond 6.0, we’re exploring further support for provenance in metadata (to establish who is doing what to a metadata record), a rethinking of how we handle dates so that they better capture the lifecycle of a research object, better support for research objects we don’t yet fully support, and making our metadata inputs more consistent. The Metadata Development roadmap has full details on what’s being explored and prioritized.

Each of these updates contributes to Crossref’s research nexus vision: strengthening connections between funders and research, more accurately capturing and recognizing contributor roles in the scholarly record, and collecting free-text content to fill in the gaps that structured metadata alone can’t address. Better metadata means better research integrity and more trustworthy infrastructure for everyone who depends on it.

Two billion citation links in Crossref help research travel further

Kornelia Korzec — Tue, 26 May 2026 00:00:00 +0000

We’ve recently reached an important milestone for the research nexus: the works in our metadata corpus are now connected with over 2 billion citation links! This is a great opportunity to share a dedicated dataset and discuss why these are important for science.

The reference metadata is a lifeline of discoverability. Scholars use citations to critique and build on existing research. They acknowledge the contributions of others through references. Our members can then deposit those references as part of metadata with Crossref, and we use those to link the cited and citing objects. This results in complex thematic networks that can be explored by interested researchers. Many tools for research discovery use the linked reference metadata in Crossref to support searches of related content.

The citation links are derived from bibliographic references in the metadata of one work that include DOIs of materials it cites (scholarly works, data, code, etc.). It’s always best if the members can deposit these relationships in full. In a recent post, we shared that nearly half of these links are asserted by our members through metadata deposits, and the other half are created thanks to our automated matching. This form of metadata enrichment happens when members include some information about the references but without the DOI of the cited work, and it’s enough to automatically find and add that DOI. The enrichment supports making data more useful for the community.

The most important impact of citation links is the increased discoverability of connected works. Reference metadata is an important tool for improving visibility and readership of our members’ content. These links are also the foundation of our Cited-by service, which enables implementing members to display citation counts of the work they published on their landing pages.

The chart below shows the cumulative count of citations over time, by the created date of the citing DOI’s record. These include records linked by DOI either through member-submitted metadata or matched by Crossref, as well as records that are unmatched. Unmatched records can include records that we were unable to match with the information we have, but also records that truly have no DOI to link to. You can explore the full citation dataset of all 2 billion citation links between Crossref DOIs available now as a (somewhat hefty) download.

Cumulative count of references deposited to Crossref by created date of citing DOI

The push for open citation data is something that has unfolded over the last few decades, making more and more of these relationships public. Notably, the growth in citation links reflects not just the output of new scholarship, but also a sustained effort to extend coverage of the historical scholarly record. We can see evidence of this playing out over time by looking at our historical data—periodic snapshots of Crossref’s metadata going back to 2019. When comparing successive snapshots and examining the publication dates of citing and cited works, we can classify each newly appearing citation as either a new paper citation, or a retrospective one. A new citation is where the citing work was published since the previous snapshot, representing real growth in the scholarly record. A retrospective citation is where both papers already existed but the link between them had not yet been captured by Crossref, and these represent indexing catchup rather than new publishing activity.

The chart below shows the cumulative count of citations added in each category since 2019. In the early years of our data, retrospective backfill was the dominant source: the blue line climbs steeply from 2019 to 2021 as a large volume of previously uncaptured historical citation relationships entered the corpus. Over time, however, that rate of backfilling has levelled off. New paper citations, meanwhile, have grown steadily throughout the period, and by 2025 they surpassed the cumulative retrospective total. The open citation ecosystem continues recovering historical links, but the citation network’s growth is now increasingly driven by the natural momentum of scholarly publishing itself.

Cumulative citations added to Crossref by type, 2019–2026. Retrospective citations (blue) represent links to and from works that existed before the previous snapshot; new paper citations (green) come from works published since the last snapshot.

Combined with other metadata for more context, reference metadata supports bibliographic and meta-research on different aspects of the scholarly process, and can support judgements about research integrity and conflicts of interest.

Stereotypically, when talking about references, we consider links to published works (whether preprints, journal articles, or books). However all types of records in Crossref can be cited. Thanks to the changes in our latest schema, members can now signal the types of content that is being referenced. And with our new Data citations endpoint, the community can explore specifically links from Crossref-registered records to research data, including citation links to works within Crossref, as well as DataCite’s corpus.

Close to half of all records registered with Crossref still have none or not enough reference information to make such connections. We invite members to regular Metadata health-check webinars to support them in improving completeness of their records for increased transparency and visibility.

Why metadata matters for research integrity: a new joint guide from Crossref and DataCite

Madhura Amdekar — Thu, 23 Apr 2026 00:00:00 +0000

Preserving the integrity of the scholarly record is an important component of the overall endeavour to protect research integrity. Open scholarly infrastructure enables persistent recording of research objects and associated metadata, which provides an evidence trail for these objects for all in the research community. Crossref and DataCite – as providers of essential infrastructure for preservation of the scholarly record – we share our joint expertise in the new guide on “Why metadata matters for research integrity and how to contribute”.

Both our organisations enable our members to share metadata about the research outputs, resources, and activities that they produce and steward. That metadata about scholarly outputs provides important information about them, which can help evidence integrity. To highlight how and which elements in the Crossref and DataCite metadata schemas support this endeavour, we are excited to make our new guide, available at https://doi.org/10.5281/zenodo19695957.

This joint guide offers practical information for all stakeholders in the scholarly ecosystem about the different metadata elements supported by Crossref and DataCite that can help in assessing the integrity of the scholarly record. With growth in the type and complexity of research outputs over the years, there is also a growing need to be able to ascertain the trustworthiness of research outputs. Metadata directly supports this function. Creators and stewards of research outputs can provide metadata about the content that they produce, including information on who authored the work, who funded it, which other works it cites, whether it was updated after publication, how it relates to other items in the research ecosystem, and more. This guide lists the metadata elements that capture this information in the Crossref and DataCite metadata schemas and the important role played by each of them in assessing integrity and rigour. We hope that by knowing more about the applications of metadata for preserving the integrity of the scholarly record, prospective authors, researchers, publishers, repositories, integrators, and funders will be encouraged to contribute rich and accurate metadata when registering DOI records.

This information can also be leveraged by researchers and users of metadata who are looking to incorporate open metadata into their tools and analyses. All of the metadata in Crossref and DataCite can be accessed via open APIs and public data files. This guide contains details of what each of the metadata elements can be used for, helping you to identify the right data that you need for your analyses of interest, such as looking at citation patterns, network analysis, and other research integrity trends.

As you read through this guide, please share your feedback and any questions that you may have via the Crossref community forum.

Strengthening community connections in São Paulo

Susan Collins — Mon, 13 Apr 2026 00:00:00 +0000

Versão em português

As our global community continues to grow, it is important for us to build and maintain our connections within it. In March this year, we had the opportunity to visit São Paulo for a community event at the Fundação Getúlio Vargas. The content of our presentations is available online. Events such as this provide an opportunity for us to update our members on Crossref fundamentals and developments, and help us better tune in to the varied needs of our communities and learn how we can work together more effectively. This was our third visit to Brazil, with previous events held in Campinas and São Paulo in 2016, and Goiânia and Fortaleza in 2018.

Our membership in Latin America has grown steadily in the meantime. We currently work with more than 3,300 members across the region; and the largest number is based in Brazil, with over 1,900 members. The majority of these represent universities, societies, and government organisations, followed by libraries and foundations that also register their works with us. In total, our members in Brazil have contributed over 2 million open metadata records to the Research Nexus.

On March 3, we welcomed 60 attendees, which included members, sponsors, service providers, and researchers. Each of these groups contribute unique perspectives and experiences, and use our services in a variety of ways. We were also joined by four Crossref ambassadors - Pedro López Casique from Mexico, Juan Felipe Vargas, Nicolás Mejía Torres from Colombia, Edilson Damasio from Brazil, as well as colleagues from SciELO Brazil.

Photo: Crossref staff and ambassadors: Leandro Contreras, Pablo López Casique, Nicolás Mejía Torres, Luis Montilla, Susan Collins, Juan Felipe Vargas, Jason Portenoy, and Isaac Farley

We started the day with an emphasis on metadata quality, the role of Crossref DOIs, and content registration best practices. We offered an overview of our helper tools: the updated Metadata Manager for record registration and Participation Reports for reviewing metadata completeness. Pedro, who is also a Publication Support Specialist with Public Knowledge Project (PKP), gave an overview of working with the Open Journals Systems (OJS) platform, which is widely used by our members throughout Brazil.

Photo: PKP’s Pedro López Casique highlighting Brazil as the second highest user of OJS-hosted journals globally.

Later in the day we shifted to more technical topics including metadata retrieval, the use of metadata for discoverability and research integrity, and common metadata errors in the registration process. Roberta Takenaka, systems developer at SciELO, discussed an overview and challenges of the adoption of DOIs in the SciELO network.

This was a tri-lingual event with presentations delivered in English, Portuguese, and Spanish, with live interpretation available for participants and presenters.

Photo: Isaac Farley discussing metadata updates

During the session, we asked attendees to share their feedback on both the value of Crossref to their organisation and the challenges they face when working with us. Participants noted persistence, the commitment to scientific development, metadata standardisation, interoperability, and increasing content visibility as important benefits. The most common challenge reported was language - the majority of our documentation is in English, which makes it difficult for many to fully utilise the available resources. Several mentioned that costs can be a challenge for some organisations, and others noted that more training opportunities, held in Brazilian Portuguese, would be appreciated.

Photo: Participants chatting during the morning coffee break

The question and answer sessions covered a wide range of technical topics, including OJS integrations, interpreting monthly resolution reports, updating metadata in bulk, and implementing Crossmark. During the coffee breaks, discussions continued as participants shared their thoughts, additional questions, and feedback with us.

Following the presentations, we held small group sessions with participants to gather feedback on two ongoing projects. Leandro Contreras, our new UX researcher, met with a group to gather information on how users interact with our website, as part of our website architecture improvement project. Luis Montilla, Technical Community Manager, led a group discussion with editors to learn more about editorial workflows and how they interact with scholarly metadata.

Many of the participants also joined us for our Metadata Sprint, which took place in the days following, exploring the uses of open scholarly metadata in creating new tools and solutions. These events were an opportunity to reconnect with the community, gather feedback to create additional training and support materials, share developments and resources, and strengthen our connections with members and key collaborators. Ana Marlene Freitas de Morais, former vice-president of the Associacao Brasileira de Editores Cientificos do Brasil (ABEC Brasil), our largest Sponsor in Brazil, stressed the importance of face-to-face collaborations, such as this event, for engagement in Brazil. Through our Ambassadors, Sponsors, and other partners, we aim to continue building lasting relationships and supporting our growing community in Brazil.

With special thanks to our hosts at Fundação Getúlio Vargas for the generous use of their venue and support personnel.

Português version

À medida que nossa comunidade global continua a crescer, é importante para nós construir e manter nossos laços dentro dela. Em março deste ano, tivemos a oportunidade de visitar a nossa comunidade em São Paulo num evento na Fundação Getúlio Vargas. O conteúdo das apresentações está disponível online. Eventos como este nos proporcionam uma oportunidade de atualizar nossos membros sobre os fundamentos e desenvolvimentos da Crossref, além de nos ajudar a nos sintonizar melhor com as diversas necessidades de nossas comunidades, e aprender como podemos trabalhar juntos eficazmente. Esta foi a nossa terceira visita ao Brasil, com eventos anteriores realizados em Campinas e São Paulo em 2016, e em Goiânia e Fortaleza em 2018.

Nosso conjunto de membros na América Latina tem crescido de forma constante ao longo do tempo. Atualmente, trabalhamos com mais de 3.300 membros em toda a região; e o maior número está concentrado no Brasil, com mais de 1.900 membros. A maioria deles representa universidades, sociedades e organizações governamentais, seguidas por bibliotecas e fundações que também registram seus trabalhos conosco. No total, nossos membros no Brasil já contribuíram com mais de 2 milhões de registros de metadados abertos para o Research Nexus.

No dia 3 de março, recebemos 60 participantes, entre os quais membros, patrocinadores, prestadores de serviços e pesquisadores. Cada um desses grupos traz perspectivas e experiências únicas, e utilizam nossos serviços de diversas maneiras. Também contamos com a presença de quatro embaixadores da Crossref: Pedro López Casique, do México; Juan Felipe Vargas e Nicolás Mejía Torres, da Colômbia; e Edilson Damasio, do Brasil, e também colegas da SciELO Brasil.

Foto: Equipe e embaixadores da Crossref: Leandro Contreras, Pablo López Casique, Nicolás Mejía Torres, Luis Montilla, Susan Collins, Juan Felipe Vargas, Jason Portenoy e Isaac Farley

Começamos o dia com ênfase na qualidade dos metadados, no papel dos DOIs da Crossref e nas boas práticas de registro de conteúdo. Apresentamos uma visão geral das nossas ferramentas: Metadata Manager, atualizado para registro de registros e os Participation Reports para verificar a integridade dos metadados. Pedro, que também é especialista em suporte a publicações no Public Knowledge Project (PKP), apresentou uma visão geral do trabalho com a plataforma Open Journals Systems (OJS), amplamente utilizada por nossos membros em todo o Brasil.

Foto: Pedro López Casique, da PKP, destacando o Brasil como o segundo maior usuário de revistas hospedadas no OJS em todo o mundo.

No decorrer do dia, passamos a abordar temas mais técnicos, incluindo a recuperação de metadados, o uso de metadados para a visibilidade e a integridade da pesquisa, e erros comuns de metadados no processo de registro. Roberta Takenaka, desenvolvedora de sistemas da SciELO, apresentou uma visão geral e discutiu os desafios da adoção de DOIs na rede SciELO.

Este foi um evento trilíngue, com apresentações em inglês, português e espanhol, com interpretação simultânea disponível para participantes e palestrantes.

Photo: Isaac Farley discussing metadata updates.

Durante a sessão, pedimos aos participantes que compartilhassem comentários sobre o valor da Crossref para suas organizações, e sobre os desafios que enfrentam ao trabalhar conosco. Os participantes destacaram a persistência, o compromisso com o desenvolvimento científico, a padronização de metadados, a interoperabilidade e o aumento da visibilidade do conteúdo como benefícios importantes. O desafio mais comum relatado foi o idioma - a maior parte da nossa documentação está em inglês, o que dificulta para muitos a utilização plena dos recursos disponíveis. Vários mencionaram que os custos podem ser um desafio para algumas organizações, e outros observaram que mais oportunidades de treino, ministradas em português do Brasil, seriam bem-vindas.

Foto: Participantes conversando durante o intervalo da manhã.

As sessões de perguntas e respostas abordaram uma ampla variedade de tópicos técnicos, incluindo integrações com o OJS, interpretação de relatórios mensais de resolução, atualização em massa de metadados e implementação do Crossmark. Durante os intervalos para o café, as discussões continuaram enquanto os participantes compartilhavam suas ideias, perguntas adicionais e comentários conosco.

Após as apresentações, realizamos sessões em pequenos grupos com os participantes para coletar feedback sobre dois projetos em andamento. Leandro Contreras, nosso novo pesquisador de experiência do usuário (UX), reuniu-se com um grupo para coletar informações sobre como os usuários interagem com nosso site, como parte do nosso projeto de melhoria da arquitetura do site. Luis Montilla, gerente da comunidade técnica, conduziu uma discussão em grupo com editores para aprender mais sobre os fluxos de trabalho editoriais e como eles interagem com metadados acadêmicos.

Muitos dos participantes também se juntaram a nós no nosso Metadata Sprint, realizado nos dias seguintes, para explorar os usos de metadados acadêmicos abertos na criação de novas ferramentas e soluções.

Esses eventos foram uma oportunidade para nos reconectarmos com a comunidade, coletar feedback para criar materiais adicionais de treinamento e apoio, compartilhar desenvolvimentos e recursos, e fortalecer nossos laços com os membros e principais colaboradores. Ana Marlene Freitas de Morais, ex-vice-presidente da Associação Brasileira de Editores Científicos (ABEC Brasil), nosso maior patrocinador no Brasil, destacou a importância das colaborações presenciais, como este evento, para o engajamento no Brasil. Por meio de nossos Embaixadores, Patrocinadores e outros parceiros, nosso objetivo é continuar construindo relacionamentos duradouros e apoiando nossa crescente comunidade no Brasil.

Agradecemos especialmente aos nossos anfitriões da Fundação Getúlio Vargas pelo generoso uso de suas instalações e pela equipe de apoio.

Metadata for research integrity: a joint guide from Crossref and DataCite

Helena Cousijn — Wed, 01 Apr 2026 00:00:00 +0000

Why metadata matters for research integrity and jow to contribute

Some aspects of research integrity depend on accurate, complete, and connected metadata. This joint guide from Crossref and DataCite sets out the metadata elements most critical for assessing research integrity—and how all stakeholders can contribute to and benefit from a richer, more trustworthy scholarly record.

Strategists

Understand why metadata is infrastructure for research integrity. Why completeness, accuracy, and openness across the scholarly record matters for systemic trust in research.

Decision-makers

Know which metadata elements to require, check, and act on. A practical resource for publishers, funders, and institutions making metadata-related policy decisions.

Practitioners

Learn how to deposit, enrich, and query research integrity metadata. Step-by-step guidance using Crossref and DataCite services and open APIs.

What this guide covers

This guide walks through the key metadata elements that enable research integrity assessment, and explains how to contribute them via Crossref and DataCite:

Contributors and their roles—identifying who did what
Affiliations—linking researchers to institutions
Dates—submission, acceptance, publication, and update dates
Funder, funding, and grant information—transparency on who paid for the research
Versioning—tracking how a work has changed over time
Retractions, corrections, and updates—keeping the record accurate
Abstracts and descriptions—what the work is actually about
Clinical trials—registration and reporting
References—connecting works to what they cite
Peer reviews—when and how work was reviewed
Publisher and steward—accountability for the record
Record and resource types—what kind of object is this?
Relationships and related identifiers—linking datasets, preprints, articles, and more
Rights, licences, and access—how the work can be used

The guide also sets out a call to action for each stakeholder group: how to enrich your records, query existing metadata via APIs, and report inconsistencies.

Read the full guide

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Voices from Crossref Metadata Sprint in São Paulo

Luis Montilla — Tue, 31 Mar 2026 00:00:00 +0000

This year, we placed a spotlight on the Latin American community, hosting the second Crossref Metadata Sprint in São Paulo, Brazil from 4 - 6 March 2026. In our first tri-lingual event, we brought together 31 participants from Argentina, Brazil, Colombia, Ecuador, and Mexico. Our goal was to foster community co-creation using the open scholarly metadata. The Sprint was an opportunity to pose questions, share ideas, collaborate on research, and propose innovative solutions that enhance the use of metadata in scholarly communication and beyond.

Read on for more details about the content of the Sprint, and the resulting projects. You can also register to join our Sprint Showcase call on 22nd April to hear directly from the team about their creations.

We were excited to receive more than 100 expressions of interest for this sprint. We’re excited to see the growing enthusiasm in this space and will find new ways to channel it (watch the space!). We sought to balance that interest with ensuring a productive size of the group for the sprint. Our participants included librarians, researchers, grad students, developers, journal editors, and scholarly communications professionals. They engaged in rich, multilingual conversations about the different editorial practices across the region - dynamically jumping between Spanish, Portuguese, and English.

We coordinated our activities and ideas with the SciELO Brazil team, who also participated in the Sprint. SciELO is one of the most recognized scholarly organizations in the region and an important source of open scholarly content and metadata; articles, books, preprints, and datasets published in different languages.

Some of the participants of the 2nd Crossref Metadata Sprint, and Crossref Staff

Susan Collins, Luis Montilla, Isaac Farley, Jason Portenoy, and Leandro Contreras from Crossref acted as facilitators, providing general support, answering questions, and clarifying the ins and outs of Crossref tools and interfaces.

Using the key learning from our first Metadata Sprint, we created opportunities for the group to interact and get acquainted remotely, before the event, to help them hit the ground running and maximise the value of the time we spent together. It really paid off in terms of quality and progress of the sprint projects.

Projects summary

The projects developed also have their own mini stories. When we opened the call for expressions of interest, we invited individual pitches for projects that make creative use of Crossref metadata to answer questions and support solutions to problems faced by our communities locally. During the preparations to the event, participants refined their proposals and coalesced into project teams. This is the list of the projects they progressed during our Sprint:

Crossref Metadata Refiner: A tool that queries the Crossref API for any publisher prefix or ISSN and computes a Crossref Health Score for each DOI, crossing citation count with metadata completeness. The result is a prioritized action list for the member: fix the most-cited papers with the worst metadata first.
Improving Error Messages in Crossref Submission Details: A proposal for the redesign of the presentation of error messages in the Crossref Submission Details interface. Instead of showing only raw XML diagnostics, display structured and human-readable messages.
Scholarly Retractions and Corrections Tool: The development of a user-friendly form for Crossref members to fill in correction and retraction metadata.
Best practices for metadata journals in OJS, according Crossref schema: A guide that shows the correct completion of metadata fields in order to avoid errors already seen in everyday work, and facilitate the correct registration of metadata with the necessary quality to avoid errors in XML export.
Metrics for publishers using the Crossref API: A Power BI dashboard that summarises members’ metrics and indicators based on metadata retrieved from the REST API.
Metadata Integrity Check: A proposal for the implementation of a second stage of XML integrity verification after using the XML parser. This additional step would allow preliminary verification of the presence of mandatory metadata elements and encourage the inclusion of recommended metadata, such as institutional affiliations and references.
Integration OJS / OPS - Crossmark: This project advanced the development of a plugin for the current versions of OJS (3.4 and 3.5), so that when an article receives a correction, update, or new version after publication, each published version of the same work receives its own DOI, while maintaining structured relationships between these versions.
Automated Detection of Reference Rot in Scholarly Web Citations: An automated evaluation pipeline to retrieve citations containing URLs, then traces redirect behavior, and records HTTP status codes and final page locations. It also extracts evidence from both the citation data and the webpage itself, including titles, creators, identifiers, and other metadata.

We will hold a community call where the teams will showcase their projects. If anything here caught your eye and you would like to learn more – join us on 22nd of April (or register to receive the recording). In the spirit of the São Paulo Sprint, we will hold the call in three languages again! Register now to join our Sprint Showcase call.

I am still in awe at what our community achieved in such a short time in the Sprint: dashboards, clever API integrations, best practices manuals… all of these projects are sure to make a mark. The Metadata Sprint in São Paulo is a testament to my belief that great ideas are everywhere, and I’m happy to have taken part in amplifying them!

Said Leandro Contreras, User Experience Researcher

Like many in attendance, this was my first Crossref Metadata Sprint. I went into the event hoping to make connections, help where I could, and learn from those in attendance. Thanks to Susan and Luis for all their planning and thoughtful leadership and the collaborative spirit of everyone participating in São Paulo, the sprint was three days full of rich co-creating, thoughtful shared problem solving, and lots of fun. It exceeded my expectations! I learned a lot and am eager for the next steps with the projects completed there. I hope to be able to participate in another Crossref sprint again very soon (and, encourage everyone reading to get to one in the future)!

Said Isaac Farley, Head of Support

Voices from the Sprint

During and after the Sprint, participants were actively sharing their experiences online. Here are a few highlights from across the community:

Being in this collaborative space allows us to deepen knowledge, exchange experiences with professionals from different countries and, above all, improve the quality of the metadata of our articles. This technical work, often invisible to the reader, is essential to ensure greater visibility, traceability and scientific impact to RBC’s publications.

Carina Munhoz de Lima - Librarian at Revista Brasileira de Cancerologia, on Linkedin, 5 March 2026.

The session was a valuable opportunity to exchange knowledge, strengthen professional ties and reflect on the current challenges around metadata management and scholarly communication.

Sandra Gisela Martín - Library System Director at the Catholic University of Córdoba, on Linkedin, 10 March 2026.

The best experience of the Sprint was recognizing the potential of combining open infrastructure, reusable data and collaboration, with the accompaniment of Crossref experts.

Sofia E. Calle Pesántez - Research Impact and Scholarly Publishing Consultant, On Linkedin, 10 March 2026.

I am grateful to see Crossref’s concern in personally listening to the demands of the Latin American scientific community!

Alex Mendonça - Client Solutions Manager at ScholarOne, on Linkedin, 5 March 2026.

Its been an absolute privilege representing Galoá at the Crossref metadata Sprint in Brazil… our specific focus during this Sprint has been clear: rolling up our sleeves to elevate the quality of metadata for Brazilian and Latin American scientific publications.

Fabiano Sant’Ana - Founder at Galoá, on Linkedin, 6 March 2026

It was wonderful to connect with so many people working to strengthen scholarly communication in the region, and to meet the Crossref staff who organised such a thoughtful and engaging program.

Zach Coble - Graduate Research Assistant, University of Missouri-Columbia, on Linkedin, 7 March 2026

We developed a free tool for registering retractions in the Crossref metadata Sprint… the motivation for the project was to develop a solution that would make the Crossmark registration process easier and more user-friendly.

Eugênio Telles, Genius Design blog, also on Crossref’s community forum. Browse Eugênio’s gallery of photos on Instagram, 8 March 2026

Participants

None of this would’ve been possible without our enthusiastic participants. Huge thanks to everyone! Here is the full list of those who attended our second Metadata Sprint:

Name	Affiliation
Julia Bottesini	Data-PASS Journal Editors Discussion Interface
Pedro Cacique	Public Knowledge Project
Sofia Calle	Red Iberoamericana de estudios científicos de la edición, evaluación y circulación del libro
Zach Coble	University of Missouri
Edilson Damasio	Universidade Estadual de Maringá
Ana Claudia Ribeiro	Editora E-papers
Eugênio Fernandes Telles	GeniusDesign
Jhonathan de Seixas Miranda	Lepidus Tecnologia
Juan Felipe Vargas Martinez	Journals & Authors
Mariana Garroux Montezuma	Sabesp
Nicolas Mejia Torres	Universidad de La Sabana
Juliana Aaparecida Bolzan	Universidade Federal de Santa Catarina
Deise Katiuscia Xavier Kaisa Oliveira	Centro Universitário de Mineiros
Glicélia Pereira Silva	Centro Universitário de Mineiros
Carolina Tanigushi	SciELO
Amanda de Souza Ramalho	SciELO
Karolayne Costa Rodrigues de Lima	Universidade Federal do Paraná
Sara Jaqueline Santos da Silva	Universidade Federal de Uberlândia
Diego Abadan M. Melgarejo	Lepidus Tecnologia
Natalino Perovano Filho	Universidade Estadual do Sudoeste da Bahia
Sandra Gisela Martin	Universidad Católica de Córdoba
Roberta Takenaka	SciELO
Amélia Galdino Monteiro Amâncio	Instituto de Física Gleb Wataghin
Quele Pinheiro Valença	Universidade Estadual de Santa Cruz
Rafael Dias Da Silva Campos	Universidade Federal do Triângulo Mineiro
Igor Moura Danieleviz e Silva	Lepidus Tecnologia
Heytor Diniz Teixeira	Universidade de São Paulo
María Eduarda Dos Santos Puga	Universidade Federal de São Paulo
Fabiano Sant’Ana	Galoá Science
Flaviane Cristina Rocha Cesar	Centro Universitário de Mineiros
David Antonio Da Costa	Universidade Federal de São Paulo

The second Crossref Metadata Sprint in a nutshell

On metadata enrichment

Dominika Tkaczyk — Thu, 19 Mar 2026 00:00:00 +0000

Metadata is communication; it can tell a story about research and paint a picture for others to respond to and learn from, across the world and throughout the forthcoming generations. Metadata can feel technical with words like ‘infrastructure’ and ‘schema’, and sometimes, like tech in general, it comes with hyperbole. But metadata really is part art (storytelling and pictures) and part science (structured models and standards) with both aspects being equally important, and requiring people as well as systems. That necessary combination of human and machine involvement also makes metadata challenging.

Crossref, as the earliest adopter of DOIs specialising in scholarly research, became synonymous with DOIs in this community. However, not everyone realises that DOIs can be registered with any one of nine different agencies, which are all separate organisations with entirely separate systems that do not at present integrate or connect. And what’s more – there isn’t a central or shared “DOI schema” – each agency develops the metadata for the purposes of their organisation or community. In Crossref’s case, with our vision to create the research nexus as a complete and robust network of relationships between objects, people, and institutions of scholarship – that community encompasses the whole of the research enterprise.

The immense 180 million records of research outputs in Crossref are maintained in a system that 24,000 member organisations have already invested in. Those records benefit from rich and format-appropriate metadata schema, developed in close collaboration with the community, which makes it possible for our members to offer contextual information about each object they register. We have a long history of working with our members on recording that context, creating tools, and providing support to adopt standard metadata, enriching the context for the benefit of the scholarly community, and society at large.

Of course, those metadata records are not perfect, both in terms of quality and completeness, and the frustration around gaps in metadata is particularly strong. We are working to improve the quality and completeness of the metadata from many angles: by working with the community to understand their needs and obstacles, by identifying and analysing potential sources for additional metadata, by maintaining and adopting the existing system to changing environment, and by planning a new flexible system that will allow third-party assertions and automated enrichment workflows.

In 2020, we published a paper for the inaugural issue of Quantitative Science Studies on Crossref: The Sustainable Source of Community-Owned Scholarly Metadata and blogged an introduction to it under Crossref Metadata for Bibliometrics. One of the things our analyses in 2019 showed was that over 80% of records between 2013-2016 had been updated. Reviewing the numbers recently, we continue to see this stewardship and maintenance of metadata, amounting to almost 70% of records from the past decade being updated at least once. On the dawn of reaching 2 billion citation links, we’d like to share our experience, plans, and views on this ubiquitous activity of updating and connecting metadata – by our members and by automations built into the system by us. Altogether, these constitute the enrichment process to improve the usability of the information for the community.

Metadata available through Crossref

Crossref collects, processes, stores, and shares metadata records for a wide range of research outputs. While each record describes an individual research output, it also mentions other entities and their attributes - and, most importantly, the relationships between them. Two works identified by DOIs, for example, may be linked by a citation relationship. A person identified by an ORCID may be connected to an institution identified by a ROR ID through an affiliation relationship. A preprint and its corresponding journal article, each with its own DOI, can be linked by an “is preprint of” relationship. A research output may be associated with a grant through a “financed by” relationship. Together, these entities and relationships form the foundational building blocks of the research nexus.

As of March 14, 2026, the Crossref database contains 180,034,490 metadata records describing research outputs. You can download all the records and examine them yourself in the latest public data file. The plot below illustrates how the number of works has changed over time, showing that the rate of growth is accelerating.

The metadata records describe research outputs of various types, including:

journal articles
books and book chapters
conference proceedings
peer reviews
reports
datasets
preprints
dissertations
grants
and more

The majority of works in the Crossref database (67%) are journal articles. However, the distribution of record types has changed considerably over time. Newer types, such as components, datasets, and posted content, are growing more quickly than more traditional ways of communicating research:

Research outputs in the Crossref database are represented by rich metadata records, which may include:

basic bibliographic metadata (title, publication dates, contributors, journal title, conference name, volume and issue numbers)
authors’ affiliations and ORCID identifiers
abstracts and links to full text
funding metadata, including funders and grant details
license metadata
bibliographic reference lists
clinical trial numbers
updates such as corrections or retractions
relationships between works and other entities, such as “is translation of”, “is review of”, “is preprint of”, or “is version of”
components associated with the work, such as figures, tables, and supplemental materials

All metadata is freely available through the Crossref REST API, and additional services, such as Crossref Search, are also provided.

A natural question is: where does all this metadata come from? This is important for two main reasons. First, it helps address the question of trust, as understanding the origin of the metadata allows users to better assess its reliability. Second, it points us to the right place when investigating or addressing issues or gaps in the data.

At first glance, the answer might seem straightforward: from Crossref members. Crossref members, such as publishers, research institutions, universities, funders, museums, libraries, data and subject repositories, and conference providers, register metadata for the outputs they publish. Crossref stores this metadata and makes it available to the community.

In reality, however, the story is more complicated.

Metadata enrichment layers

The initial metadata deposit is only the beginning of what can become a long and rather fascinating journey. What users can see in our REST API is often the result of a series of updates and additions that occur over time, sometimes coming from multiple sources and happening in different ways. We can think of these ways as enrichment layers.

Each enrichment layer offers opportunities to improve the metadata while also introducing its own considerations and challenges. Rather than forming a sequence of clearly separated stages, these layers intertwine, overlap, and affect one another, collectively shaping how a research output is represented within the research nexus.

Enrichment layers are essential for completeness of the research nexus. If we relied solely on the original, one-off deposits from members, the metadata would be full of gaps, limiting the usefulness of any analysis or assessment based on it. While the scholarly metadata will never be perfectly complete, applying these enrichment layers is how we gradually and collectively build a fuller, more accurate picture of the research nexus.

One important caveat is that more metadata doesn’t magically equal better metadata. In fact, there’s often a delicate tradeoff between completeness and quality: the harder one pushes to fill every gap, the greater the chance of introducing errors. At Crossref, we believe quality comes first. We recognise that no dataset will ever be perfect, but we’re equally unwilling to apply enrichment processes without quality control. Any enrichment we introduce must meet a high bar for accuracy — no exceptions, no shortcuts.

The order of the enrichment layers discussed here loosely reflects how established they are within the scholarly ecosystem. There also might be a correlation, or at least a perceived one, between this ordering and the reliability of the underlying processes. That said, one must tread carefully when making such interpretations: perceived reliability is not the same as actual reliability.

Layer 1: Member updates

Crossref members not only deposit metadata, but also update it over time. This is an essential part of the system for several reasons. There may be errors in the originally deposited metadata that need to be corrected. Also, the initial record may contain gaps that can be filled later as more information becomes available. In addition, many changes naturally occur: landing page URLs may change, works may be archived in new locations, or identifiers for affiliated organisations may become available. Those situations also ideally result in an update.

This update process is well established. Over 24,000 Crossref members form a large global community that operates under shared membership terms. As part of these terms, members are responsible for maintaining and updating their metadata records. In this governance framework it is clearly defined who owns and stewards the metadata associated with each record, and who is responsible for the quality level and issues.

Member updates are very common. As an example, over 80% of works deposited between 2013 and 2020 were updated at least once. This demonstrates the community’s commitment to improving completeness and quality of the scholarly record. The plot below shows the percentage of works created in a given month that were updated at least once.

However, this layer also comes with challenges. It relies on members actively meeting their obligations to maintain and improve their metadata. As a result, gaps and inconsistencies can remain, and overall metadata quality is never perfect.

Our plans for the future in this area largely build on what is already happening. This includes developing and maintaining effective user interfaces for updating metadata, evolving the input metadata schema to keep pace with changes in the scholarly landscape, offering regular workshops on metadata improvements, and collaboratively establishing best practices while educating members on how to apply them.

Layer 2: Community feedback loop

Crossref metadata is widely used and examined by a large community of consumers. As a result, issues with metadata are sometimes identified by community members and reported back to us. When this happens, Crossref does not directly correct the metadata records. Instead, we contact the relevant member responsible for the record and able to deposit an update.

In this layer, the stewardship of metadata remains with the member, while responsibility for metadata quality broadens to include other actors in the community. This creates significant potential for scaling by involving a large community in identifying and reporting metadata issues.

At present, however, this process is not automated. Crossref staff effectively act as intermediaries between those reporting issues and the responsible member. As a result, the process has limited scalability. It also depends on the willingness of members to act on the reports they receive, as they are not obligated to respond to such reports.

In the future, we may explore automating portions of this workflow to handle community feedback more efficiently and lighten the load on everyone involved.

Layer 3: Metadata matching

Metadata matching is the task of finding an identifier for an item based on a structured or unstructured description of it. Matching strategies run as fully automated processes that analyse information deposited and updated by members and add identifiers, filling gaps in the metadata.

There are many instances of metadata matching problems, for example:

bibliographic reference matching: finding a DOI for a cited paper based on a bibliographic reference,
funder matching: finding the ROR ID for a funder based on its name,
affiliation matching: finding the ROR ID for an organisation based on an affiliation string,
preprint matching: finding the DOI for a preprint that precedes a given journal article,
grant matching: finding the grant DOI based on an award number and a funder name.

This layer is unique, as it focuses on a crucial type of gap in the scholarly record: the missing relationships between entities. Indeed, adding an identifier for an entity mentioned within a metadata record of a research output is typically an equivalent of asserting a relationship between that output and the matched entity. For example, bibliographic reference matching inserts citation relationships, and funder name matching - funding relationships between a research output and a funding organisation. These relationships form the foundation of the research nexus.

Currently, at Crossref, we perform two types of matching. We match bibliographic references to the DOIs of cited outputs, and funder names to Funder IDs. Both processes rely on fuzzy comparisons and other heuristic approaches to identify likely matches.

In the case of bibliographic reference matching, as it turns out, more than half of the cited DOIs (1 billion) available in the Crossref database originate from automated metadata matching:

In the case of funder name matching, the distribution is very different, but the matching strategy was still able to fill in some of the gap:

Metadata matching is a particularly valuable form of enrichment for several reasons. Matching strategies can often achieve high levels of accuracy while working in a fully automated way. This makes them highly scalable and drastically reduces the need for human oversight. Their focus on relationships also strengthens the foundations of the research nexus.

At the same time, this enrichment layer presents a number of challenges.

Its most fundamental limitation to remember is that metadata matching can only fill gaps when there is at least some useful information to work with. For example, it can identify a cited document only using structured or unstructured citation data, and the funding organisation can only be identified if some funding information is available. But if citation information, or funding information, is completely absent, as is the case for 101M (56%) records and 166M (92%) records respectively, then matching simply isn’t possible.

Matching strategies can also be complex and time-consuming to research, develop, and maintain. They require additional considerations of issues such as openness, explainability, complexity, flexibility, and cost.

Perhaps most importantly, in the case of matching, it becomes less clear who is responsible for the information introduced through the matching process. This is particularly important because matching results are never perfect, meaning there is always a risk of introducing errors. The risk is further amplified by the fact that matching strategies typically operate in a fully automated, unsupervised manner. As a result, careful evaluation of matching performance, as well as maintaining accurate provenance records, becomes increasingly important.

At Crossref, we have ambitious plans in this area. We intend to rebuild Crossref’s metadata matching workflows using modern software development and data science practices. The goal is to create a dedicated, consolidated matching service that will eventually replace all existing production matching processes, with results made available through the REST API. This project will cover six matching tasks: bibliographic reference matching, funder name matching, preprint matching, affiliation matching, grant matching, and title matching. You can learn more about metadata matching at Crossref at a dedicated project page.

Layer 4: Third-party datasets

There are many databases containing scholarly data, and one way to fill gaps in Crossref member-provided metadata is to incorporate additional metadata from those external sources.

We already have one example of this. Crossref ingests data from the Retraction Watch database to supplement information about retractions and other updates to records:

This layer has several advantages. It draws on subject-specific and metadata-specific expertise, avoids reinventing work that has already been done elsewhere, and reflects a collaborative community-driven approach to improving the scholarly record.

However, there are also important challenges to consider. Integrating external data often involves multiple data licenses or acquisition arrangements, and there may be less control over data quality compared to metadata that comes directly from members. There is also a risk that relying too heavily on external sources could shift responsibility away from the member stewards of the metadata. Finally, it can be difficult to determine which external datasets provide sufficient value and longevity to justify long-term integration.

Looking ahead, we plan to explore further opportunities to incorporate third-party datasets, carefully considering the value they bring, as well as issues of licensing, sustainability, and data quality.

Layer 5: Unstructured content scraping

A significant amount of scholarly information still exists in fully unstructured forms, such as full-text PDF documents and web pages. In principle, extracting information from these sources could help fill many gaps in existing metadata.

In a lighter-touch approach, analysing full-text documents can also help verify existing metadata elements. If such a check fails, the unverified element may be removed from the record — which, perhaps counterintuitively, can also count as enrichment, since improving accuracy is every bit as important as adding new information.

There are also important challenges to consider. Extracting metadata directly from unstructured sources could substantially shift responsibility away from the original data stewards or owners, weakening the current stewardship model. The results of automated extraction may also be inconsistent or of relatively low quality. In addition, there are potential legal and rights-related concerns, particularly when processing full-text materials. Finally, developing reliable extraction methods would require substantial research and engineering effort.

For all these reasons, the practical usefulness of this approach remains uncertain, and Crossref currently has no plans to run such processes in production. We will, however, keep a close eye on emerging extraction technologies and may consider adopting them in some form if future evaluations show clear value.

Summary

Metadata is far more than a technical afterthought of the publishing process. It is the connective tissue of the scholarly ecosystem, linking research objects, people, and institutions into a coherent, navigable network. At Crossref, this takes the form of a vast and continually evolving corpus of more than 180 million metadata records, all contributing to the emerging research nexus, being built through collective community effort to help the global research community discover, interpret, and reuse knowledge effectively.

The initial metadata record deposited by members is only the beginning. Its quality and completeness can improve over time through multiple enrichment layers: member-driven updates, community feedback, automated metadata matching, and the incorporation of third-party datasets. These processes help fill gaps and strengthen the reliability of the scholarly record, all while upholding a firm commitment to accuracy and stewardship.

Taken together, these layers reflect a long-term, collaborative effort across technology developments, community participation, and responsible automation, to ensure that scholarly metadata becomes richer, more interconnected, and more useful for everyone who relies on it.

2026 public data file now available

Martyn Rittman — Tue, 17 Mar 2026 00:00:00 +0000

Once a year we release all metadata records for content registered with Crossref in a public data file. This year’s version, containing nearly 180 million records, is now available. It includes metadata associated with all Crossref-registered DOIs in JSON-lines format.

All our metadata is openly available via our REST API at all time and this file provides the same information all in one place for those who find that format useful for their tools and analysis. You can access the file via Academic Torrents at https://doi.org/10.13003/nggf-vt1j or directly from AWS. For further guidance and tips, see our documentation. The complete, compressed files are 208 GB.

Our metadata has several sources:

Primarily, it comes from records deposited by over 24,000 members spread across over 160 countries. This year, we are pleased to have added a number of new countries by expanding our GEM program, which supports participation in the Crossref community from those in the most economically disadvantaged regions.
Second, we enrich the data by adding automated matches, for example by adding DOIs to deposited references, and organisation identifiers to funders. We are undertaking a renewal of our matching processes, starting later this year with matching funders to ROR identifiers.
Finally, we use selected third party sources to enrich the metadata. Currently we include retractions from the Retraction Watch database.

Most of the data can be freely reused and is not subject to copyright. Some limitations are applied to abstracts. See our documentation for more details about licensing.

Why do we do this?

The community is key to everything we do. Without the thousands of members depositing metadata, we would have nothing to share. And without countless organisations and individuals making use of the metadata, it would have no impact or value. Our mission is to serve our community, and making metadata publicly and openly available is one of our key values. The public data file is just one of a number of ways in which we enable metadata retrieval.

Over the last year, there have been over 600 downloads of the public data file. In addition, we see around 2 billion hits to our public APIs each month. We are always excited to hear about the diverse and interesting ways in which metadata can be used.

What’s different this year?

Thanks to the rich metadata, the records deposited with Crossref are interconnected with many types of relationships between works, people, and organisations, that tell the story of the research endeavor. The latest public data file reflects the current status of the research nexus as we know it and we’re delighted to share it with the community.

This year’s dataset contains 12.7 million new records (a 7.6% increase since last year). Across the board, we’re also seeing richer metadata records, with more abstracts (up 15%), ORCID identifiers for authors (up 20%), ROR identifiers for organisations (up 250%), and links to grant identifiers for funding (reaching 50,000 records).

Research integrity is a current theme in our community. We can see that members increasingly look to leverage metadata in service of asserting trust in their works. An additional 27% more records have Crossmark enabled, meaning that the member responsible is open about research integrity practices, and committed to communicating corrections, retractions, and other post-publication changes. In addition, this year’s snapshot contains retractions from the Retraction Watch database. If you have any questions or feedback about the public data file, or would like to discuss how you can use it, head over to our community forum and join the conversation.

Insights from a roundtable on author affiliation metadata

Amanda French — Thu, 22 Jan 2026 00:00:00 +0000

It’s been said that Americans are unusual in tending to ask “Where do you work?” as an initial question upon introduction to a new acquaintance, indicating a perhaps unhealthy preoccupation with work as identity. But in the context of published research, “What is this author’s affiliation?” is a question of global importance that goes beyond just wanting to know the name – and perhaps prestige level – of the place a researcher works.

When collected, used, and analyzed at scale, data about author affiliations can provide intriguing insights about international collaboration trends, signal trust and lack of trust in particular research institutions, generate business intelligence for publishers, help universities track the work their researchers do, help funders demonstrate the impact of their funding, and much more.

In November we partnered with OA Switchboard to organize a roundtable on author affiliation metadata for the Crossref community, service and infrastructure providers, production vendors, data scientists, researchers, and librarians. We aimed to bring together scholarly information professionals with many diverse perspectives; ultimately, participants from more than 40 organizations joined the roundtable to share their experiences and their thoughts.

In focusing on a single type of metadata, we hoped to focus our discussions, as well. Similarly, in October the Barcelona Declaration on Open Research Information organized a roundtable on “Moving Funding Metadata Forward” in which it became clear that “improving the quality and coverage of funding metadata was on the agenda of many organisations and there was a strong interest in collaborating on practical next steps.”

While many of the issues and solutions discussed at both roundtables are similar, in the course of the author affiliation metadata roundtable we identified some unique challenges as well as benefits related to this particular flavor of information. In this blog post, I’ll share these insights.

Insights from presenters

I opened the roundtable with a brief introduction and a working definition of affiliation metadata: names and/or identifiers such as Research Organization Registry (ROR) IDs for organizations where research was conducted or with which authors and contributors are associated, usually officially, as in their place of employment.

Next, to create a shared context for discussion, we heard four presentations on the current state of author affiliation metadata, its importance, and Crossref’s ongoing initiative to enhance it automatically.

Nees Jan van Eck of Leiden University’s Center for Science and Technology Studies (CWTS) shared observations on the state of author affiliations from a preprint titled “Crossref as a source of open bibliographic metadata” that presents the findings of an analysis performed annually since 2021. Nees’s key points:

Crossref is a foundational data source for bibliographic metadata.
Affiliation metadata is available for only 1 out of 3 journal articles in Crossref for the period 2023-2024.
There is considerable variation in the extent to which Crossref members deposit affiliation metadata.
Downstream sources try to fill gaps using suboptimal approaches, leading to missing, inaccurate, and inconsistent linking of publications to institutions.
Publications lacking affiliation metadata in Crossref are less visible in bibliometric applications, analyses, studies, and tools (such as the open edition of the Leiden Ranking of over 2800 universities).

Next, Yvonne Campfens of OA Switchboard reiterated the desirability of the Crossref community providing complete and accurate author affiliation metadata at the source. Yvonne called upon publishers to “Integrate metadata creation in your systems and workflows before publication and relay it throughout the editorial, production, and publication processes.”

Yvonne pointed out that in the context of managing Open Access agreements, publishers ought to keep in mind that providing good affiliation metadata improves customer satisfaction, since institutions and consortia need to have that information in order to connect research to the correct organization. In closing, Yvonne featured best practices from OA Switchboard’s Data Quality Challenge:

eLife captures affiliations at submissions with “author select,” ensuring that ROR IDs are introduced early and verified before publication, coupled with a quality assurance process during proofing. (See also our piece on Metadata Excellence Award winner eLife.)
EMS Press captures metadata via manuscript extraction as early as at submission, building on globally valid identifiers whenever possible (ROR IDs, DOIs, ORCIDs).
Pensoft Publishers uses AI-assisted metadata extraction with human review and in-house metadata validation.
Beilstein-Institut performs post-acceptance metadata quality assurance through automation and expert review.
The Royal Society embeds metadata in OA payment and agreement workflows.
American Chemical Society (ACS) has a multi-method persistent identifier matching strategy with near-complete coverage.
The American Society for Microbiology (ASM) combines AI-powered submission tools with editorial oversight via expert manual checks. (See also our piece on Metadata Excellence Award winner ASM.)
Rockefeller University Press (RUP) maintains ROR IDs across the full publishing workflow with “author select” at submission through metadata deposits upon publication. (See also the ROR case study on RUP.)

Adam Day of Clear Skies Ltd began his talk by wryly framing the first and second rules of data science as contradictory: “Never fix data: always use sources that produce high-quality data in the first place,” but also “Get good at fixing data, because you will have to.” Adam went on to demonstrate the central role author affiliation metadata plays in research integrity investigations, displaying anonymized data for institutions with a high number of alerts. In conclusion, Adam reiterated the importance of author affiliation metadata to research integrity efforts:

Data analysis is critical to research integrity.
Quality data helps enormously by giving oversight, saving time, and assisting investigations.

Lastly, our own Director of Technology Dominika Tkaczyk gave an account of our plans to enrich author affiliation metadata by matching organization name text strings to ROR IDs as part of our metadata matching initiative. A strategy for performing such matching has already been developed and tested and an open dataset of results made available. Tests on a set of 3,000 affiliations sampled from our metadata show that the strategy can be expected to match 95 million ROR IDs to organization names with 97.35% precision, an astronomical increase over the less than 1 million ROR IDs deposited in Crossref records to date.

Dominika concluded the presentation portion of the session by reiterating that our planned enrichment of author affiliation metadata

Will use flexible and transparent matching strategies (and open code),
Will welcome community participation in developing new strategies, and
Will be available in the REST API.

Automatic matching of organization names to ROR IDs in author affiliations cannot solve the problem of missing organization names, of course, but it represents a huge leap forward in addressing metadata quality issues.

All of our speakers’ presentations are available on Zenodo at https://doi.org/10.13003/661591chqlyw.

Insights into challenges

In the next stage of the event, participants broke into six breakout groups to identify factors contributing to incomplete or inaccurate affiliation metadata. Participants were pre-assigned to groups randomly by role to ensure a variety of perspectives in every discussion.

At least two participants, it should be noted, pointed out that it would be helpful to agree on a definition of “complete” and “accurate” affiliation metadata, which in itself is a challenge, and one we did not address in this roundtable. For instance, practices most recently have trended away from defining a complete author affiliation in open metadata as including an institutional address, although many internal databases might include such information separately.

Even without such definitions, however, all six groups were able to identify several general areas for attention, and one participant provided a particularly helpful categorization of these areas that is largely reused here.

Inherent data complexity

Research organizations have names in different languages, abbreviations, and many other name variants.
Research organizations have frequent name changes, mergers, and rebranding.
Research organizations have different degrees, levels, and complexity of hierarchical granularity, and authors, publishers, and software systems are often misaligned as to which level in an organization’s structure is appropriate to use in a particular instance.
Research organizations often lack official policies on how affiliations should be written, leading to hundreds of variations for a single institution.

Corresponding authors often submit information for all co-authors, which can lead to inaccuracies.
Many authors have multiple profiles across multiple submission systems, which can introduce errors.
Authors may have “octopus affiliations,” claiming affiliations with many institutions that are difficult to verify.
Authors may fail to update affiliations when changing institutions between manuscript acceptance and publication.
Authors may demonstrate “apathy” when repeatedly filling out submission forms, sometimes providing incomplete, inconsistent, or incorrect information.
On occasion, authors might even provide false or purchased affiliations, which of course is a significant research integrity concern.

Technical barriers

Many manuscript tracking and peer review systems, especially legacy systems, lack structured fields for affiliations or don’t support open organization identifiers like ROR.
Some systems limit authors to a single affiliation, despite many researchers having multiple institutional connections.
Some systems only collect affiliation information for the corresponding author.
Some systems link affiliations to user accounts instead of to publications.
Different systems use competing identifier registries, including proprietary identifier registries, creating interoperability challenges.

Publisher practices

Even when publishers improve current metadata collection practices, historical data correction is resource-intensive and often not prioritized.
Publishers collect affiliation information at submission but don’t ensure that it is maintained throughout all stages of the publication process and deposited in metadata.
Some publishers are unaware of the importance of author affiliation metadata or do not prioritize its improvement.
Some publishers deliberately choose not to deposit affiliation metadata to Crossref, viewing it as value-added information they’ve invested in curating.

Insights into solutions

Naturally, we didn’t rest at identifying challenges: after a break, we gathered in the same groups to brainstorm approaches to improving author affiliation metadata.

Adopt collective approaches

Collective action, where corrections and improvements made by various stakeholders flow back into shared systems, has historically worked for proprietary systems and could be even more powerful with open infrastructure.
Since those who do not provide metadata “upstream” will inevitably have it provided for them “downstream” by multiple separate entities using multifarious methods, provenance metadata indicating who asserted author affiliations and how (whether automatically or with the author’s or editor’s input) would help metadata users assess trust levels.

Engage authors and institutions

Reach out to authors and institutions to educate them on the need for more consistent affiliation reporting, especially in terms of language, name format, and degree of hierarchical granularity.
Demonstrate the benefit to institutions of maintaining accurate records in registries like ROR, including abbreviations and name variants.
Publishers and/or software systems should allow authors to review (though not necessarily edit) affiliation information during the proofing process to verify accuracy. Authors should not, however, need to know, see, or use ROR IDs.

Improve the tech

Publishers would welcome submission systems that incorporate structured fields for author affiliations with well-designed auto-suggestions linked to ROR or other organization identifiers.
Making affiliation data mandatory at submission could significantly improve capture rates, although it would be important to ensure that independent researchers can use these systems as well.
Enable collection of affiliations for all authors, not just the corresponding author.
Pull in verified affiliation information from ORCID.
Increasingly, intelligent matching systems can be implemented to reduce author burden and perhaps also increase accuracy and completeness of metadata.
Better crosswalks between different organization identifier systems would make it vastly easier for publishers to maintain better metadata. Since open registries cannot include proprietary information, proprietary registries should provide their customers with crosswalks to all standard open identifiers.

Encourage publisher best practices

Publishers can use already-available tools to help assess and improve the quality of both new and legacy author affiliation metadata.
Share the benefits of improved author affiliation metadata for internal and external analytics, customer satisfaction, and research integrity.
Identify best practices in collecting and structuring author affiliation metadata.
Understand that the entire research ecosystem would benefit from publishers sharing collected affiliation data with Crossref.

It’s worth mentioning that these solutions are heterogeneous: not all strategies can be implemented by any one actor nor even by any one sector of our profession. Clearly, collaborative action is necessary for substantive change.

Moving forward

The affiliations metadata roundtable represented an important step in addressing affiliation metadata challenges in a productive and collaborative way. If there was a consensus, it was that while perfect completeness and accuracy of author affiliation metadata may not be achievable (or even definable), incremental improvements can substantially enhance the quality and availability of affiliation metadata for the entire scholarly information community.

Here at Crossref, we intend to use the insights from this roundtable to inform our support of the Crossref community, including publishers, service providers, and metadata users. We welcome your comments, questions, and suggestions on this issue! Share your thoughts with Amanda French at alfrench@crossref.org.

References

van Eck, N. J., & Waltman, L. (2025). Crossref as a source of open bibliographic metadata (No. smxe5_v2). MetaArXiv. https://doi.org/10.31222/osf.io/smxe5_v2
Tkaczyk, D. (2025). Crossref relationships involving research organisations [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.15254993
French, A., van Eck, N. J., Campfens, Y., Day, A., & Tkaczyk, D. (2026, January 19). Affiliations Metadata Roundtable 2025—All Presentations. https://doi.org/10.13003/661591chqlyw

Participating organizations


Africa PID Alliance / TCC Africa	Frontiers Media SA
American Association of Cancer Research (AACR)	Iowa State
American Chemical Society (ACS)	Kriyadocs / Exeter Premedia Services
American Physical Society (APS)	MDPI
American Society for Microbiology (ASM)	Noyam Publishers
Aptara	OpenAIRE / OpenOrgs
Australian Research Data Commons (ARDC)	Optica Publishing Group
Atypon	ORCID
Beilstein-Institut	Oxford University Press
California Digital Library (CDL)	Public Knowledge Project (PKP)
Cambridge University Press	Public Library of Science (PLOS)
Carnegie Mellon University	River Valley Technologies
CHORUS	Rockefeller University Press
Clarivate / Web of Science	SAGE Publications
Copernicus GmBH	Barcelona Declaration on Open Research Information
Curtin University / Curtin Open Knowledge Initiative (COKI)	Silverchair / ScholarOne
De Gruyter Brill	Springer Science & Business
Digital Science / Figshare	TNQTech
Digital Science / Symplectic Elements	University of Laval
eLife	University of Chicago Press
Elsevier BV	University of Split
Enago

The best way of acknowledging research funding in the metadata: Crossref Grant ID

Patricia Feeney — Tue, 06 Jan 2026 00:00:00 +0000

We are very pleased to kick off the New Year with another important schema update and the news that a Grant DOI field is now supported for all record types. This means that Crossref members can explicitly include the Crossref Grant IDs as part of their DOI metadata records for publications and any other output type, accurately linking research outputs to the funding that made it possible, all through metadata. We hope that our members will leverage this to respond to recent calls for stronger funding transparency and best practices for reporting funding sources in research outputs.

Funding information is very important for the research community. As explored by some key European funder representatives, providing mechanisms to clearly link funding with its outputs is essential for the community to have a full picture of the research endeavour.

When funders systematically register grants with persistent identifiers and make this information openly available, they create a foundation that publishers and infrastructure providers such as repositories can reliably build upon when depositing output metadata.”

– Hans de Jonge, Katharina Rieck and Zoé Ancion

Up until now, if a Crossref member wanted to include a Crossref Grant ID to unambiguously identify the output funding source, they would need to use other available fields, such as for an award number. While it was an important step towards increasing transparency and is heavily used for reporting and impact assessment, being an unstructured field, it was prone to errors, and of course, funders’ internal award identifiers are not unique, persistent, or necessarily open. This limited our ability to create unambiguous relationships with the Crossref Grant DOIs registered by our now ~50 funder members. As the new field becomes increasingly populated by our members, this rich metadata will pave the way for capturing and representing the funding relationships in a more accurate and complete way and fulfilling one of our commitments at the recent funding metadata workshop with the Barcelona Declaration.

The Crossref Grant ID field in the schema is a clear signal of the growing demand for these persistent Grant IDs (Crossref DOIs), and the relationships these help us create. Those connections can in turn enable streamlined reporting for the grantees, as well as compliance tracking and programme evaluation for funders.

As part of our work to enable the research nexus, Crossref has been proactively identifying funding information and prototyping metadata enrichment processes through matching projects, ensuring that as many relationships as possible are established and made discoverable. With this schema update, we aim to lower barriers and encourage more members to register output-funding relationships at source. This will facilitate the links that make the research nexus a connected, interoperable, and an important source of information that ensures a transparent and trustworthy research process.

We encourage all Crossref members to start incorporating Grant DOIs when available into your metadata submissions. By taking advantage of this new field, you’ll help build a more complete and transparent record of research funding, making it easier for the community to understand and trace the impact of funded research.

When collecting funding information for your publication, please consider asking the authors for the Grant DOI (Crossref Grant ID) as well as the funder’s details (such as their name and identifier). Here’s how the U.S. Department of Energy, Office of Scientific and Technical Information’s (OSTI-DOE) grant https://doi.org/10.46936/aps-182101/60010611 can be included in the metadata for related works, from datasets, to preprints, conference proceedings, journal articles, and more:

<assertion name="fundgroup">
 <assertion name="ror">https://ror.org/04qxsr837</assertion>
 <assertion name="grant_doi">10.46936/aps-182101/60010611</assertion>
 </assertion>

Similarly, a grant https://doi.org/10.3030/732489 from European Union H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP, would be represented in related work’s metadata as follows:

<assertion name="fundgroup">
 <assertion name="funder_name”>H2020 LEIT Information and Communication Technologies
 <assertion name="funder_identifier”>10.13039/100010669</assertion>
 </assertion>
 <assertion name="grant_doi">10.3030/732489</assertion>
</assertion>

For more technical documentation and implementation guidance, please visit our funding data documentation. If you have questions or need support integrating Grant IDs into your workflow, our support team is here to help!

Highlights of a very busy year: our 2025 annual report

Ginny Hendricks — Thu, 18 Dec 2025 00:00:00 +0000

As we finish celebrating our 25th anniversary, we can look back on a truly transformational year, defined by the successful delivery of several long-planned, foundational projects—as well as updates to our teams, services, and fees—that position Crossref for success over the next quarter century as essential open scholarly infrastructure. In our update at the end of 2024, we highlighted that we had restructured our leadership team and paused some projects. The changes made in 2024 positioned us for a year of getting things done in 2025. We launched cross-functional programs, modernised our systems, strengthened connections with our growing global community, and streamlined a bunch of technical and business operations while continuing to grow our staff, members, content, relationships, and community connections.

Read on for the highlights of a very busy year, grouped around our four strategic themes.

Strategic theme 1: Contribute to an environment where the community identifies and co-creates solutions for broad benefit

Enhanced tools and services

In October, we released an enhanced Participation Reports dashboard that shows metadata coverage across all 180 million records and provides individual member organisations with actionable gap reports to guide them to improve metadata completeness. The new tool provides more complete coverage of all members and resource types, now including funders and grants, with up to 11 best-practice metadata elements publicly tracked.

We launched support for journal articles in the New Metadata Manager record registration form (initially only for grants), which includes built-in reference and relationships deposit capabilities. In the New Metadata Manager, it’s now also possible to search for previously registered DOIs to edit your metadata records. In the coming years, we are planning to expand the new Metadata Manager to support all the many different content types that you can register with Crossref DOIs.

After a long break between regular updates, we have fixed our process for and just released v.1.63 of the Open Funder registry. With the updated process, we’re now able to resume more frequent updates to the registry (while of course still working towards the transition to ROR for funders).

Throughout 2025, we conducted a website information architecture review to improve the information we provide to our members and the wider community. Based on the recommendations from this review, we will be renewing our website and documentation in 2026.

Deprecations and modernisation

‘Old’ Metadata Manager is to be retired at the end of 2025, with users transitioning to the ‘New’ version or to our other helper tools for registering and updating DOIs. All users have been contacted during 2025 and received training on how to use the New Metadata Manager.

We also announced the deprecation of Co-access, which will end in 2026, bringing an end to the service that allowed duplicate DOIs for book content. Users of co-access have been informed and are in the process of transitioning to multiple resolution.

Together with Turnitin and our members, we are working to transition all subscribers to our Similarity Check service to a new version of iThenticate 2.0. We are happy to report that all platforms with integrations with us transitioned to 2.0 during 2025, and we will continue working with our members to get everyone transitioned during 2026.

Eating our own DOI dogfood

In June this year, we were particularly pleased to finally support the registration of DOIs for our own content, this very blog, through partnering with Rogue Scholar. Blogs are a growing format for scholarly discourse and our own blog is no different as it’s the main way that we share guidelines and best practices, as well as news and stories from the scholarly community. With a Crossref DOI for all blogs going back to 2006, we’re setting ourselves up to ensure better future preservation of the discussion and information about Crossref.

Community connections

We delivered 29 metadata health-check webinars over the course of the year, in French, Indonesian, Spanish, and English, reaching 2,166 participants with practical advice on identifying gaps in journal metadata using Participation Reports.

Crossref Accra took place in March as our first in-person event in a GEM country. We also held similar events in Ecuador and Türkiye with Crossref Quito in September and Crossref Ankara in November. At these three events, we welcomed key figures from each country’s library, government, publishing, and academic communities and we learned so much about the thriving communities there, and also that even more dedicated workshops on the specifics of metadata quality improvements would be appreciated.

Our metadata sprint in Madrid in April brought together community members to tackle specific problems collaboratively, with teams exploring coding, documentation, translation, and research using our open metadata. We’re already planning our next sprint in São Paulo for March 2026, and it will be held in three languages: Portuguese, Spanish, and English.

A strategic goal for Crossref is to grow research funders’ adoption of the Grant Linking System, and we produced the first in a series of interviews with funder members this year to highlight how and why Crossref DOIs are fulfilling goals to assess the reach and return of their research support for FWF (Austria), NWO (Netherlands), FCCN|FCT (Portugal), and Wellcome. This year, we welcomed more funders including Fonds de recherche du Québec (Canada) and Independent Research Fund Denmark as part of their national research platform NORA; we look forward to reporting on their experiences and outcomes next year and others as they work towards Crossref Grant DOI adoption.

We continued working closely with PKP and renewed our partnership to help drive better experience for OJS users registering metadata with Crossref. We also delivered a proportion of the metadata health-checks together to maximise the learning opportunities for our members using OJS; and we joined PKP’s Sprint in Oslo to help make improvements to OJS and OMP.

Crossref staff members serve on almost 50 committees, boards, and other community bodies alongside our own direct work. These include in the areas of research integrity, metascience, metadata and PID standards, open science policy or monitoring, development of new models (such as Diamond OA), editorial production, library and institutional publishing, and citation and other metadata analyses. We also work with other DOI Registration Agencies and support the sustainability of the DOI Foundation with an additional annual subsidy. Many DOI RAs are also Crossref Sponsors so that their members can access our unique reference matching service. While we often might advise, we also learn a huge amount from collaborating with the numerous systems and initiatives that make up the wider research community.

Our involvement with developing the Barcelona Declaration on Open Research Information led us to become the fiscal host and to participate in most of the working groups on open metadata. Of particular note this year was the Funding Metadata Working Group round table about moving forward the state of funding metadata, which we co-hosted with Barcelona Declaration colleagues, and three funding bodies, NWO (Netherlands), FWF (Austria), and ANR (France) as we heard from publishers and their vendors about challenges and how to overcome them to increase the quantity and quality of available open funding metadata.

All our community engagement activities have been enthusiastically supported and enriched by our indispensable Ambassadors and our group of now 130 Sponsors, organisations that help thousands of Crossref members with local language and technical support and lower cost access to our membership.

Strategic theme 2: A sustainable source of complete, open, and global scholarly metadata and relationships

Schema developments

The grant schema version 0.2.0 was released in January, adding support for ROR identifiers to identify funders and new funding types for in our taxonomy, including APC, BPC, and infrastructure. All of these funding types can be specified in the metadata of our grant-giving members alongside the existing types such as use of facilities or salary/training awards, etc.

Version 5.4 of our publications schema was released in March, marking our first update in many years and a great opportunity to learn how to do this and make the process more efficient. This release introduced typed references to denote the type of object referenced (dataset, blog, software, etc.), preprint status indicators, and version numbering.

Just last week, we also added a dedicated field for grant DOIs to our publications schema. This means it’s now possible to indicate in an article’s metadata which grant(s) funded the research using the persistent identifier. This is an essential step toward better alignment between grant funding and research, enriching the Research Nexus.

We also launched our new Metadata Advisory Group and they have already devised sub-working groups in three focus topic areas:

Multilingual metadata
Subjects and keywords
Relationships

Public data file

We released the 2025 public data file in March, containing metadata for (at the time) over 165 million research outputs from more than 22,000 organisations.

Inaugural Metadata Awards

In May, we launched the first-ever Metadata Awards to recognise members demonstrating excellence in metadata completeness and enrichment. Winners included Noyam Publishers (Ghana), GigaScience Press (Hong Kong), eLife (UK), American Society for Microbiology (USA), Universidad La Salle Arequipa (Peru), and Instituto Geologico y Minero de España (Spain). The awards will be held biennially going forward.

Metadata Matching project

In April, we launched the metadata matching project with the aim of building a more complete picture of the research nexus over time by automatically identifying missing relationships between entities across the scholarly record. The project’s goal is to modernise Crossref’s enrichment workflows by rebuilding them using modern software development and data science practices.

We are in the throws of developing a consolidated matching workflow that will eventually replace all existing production matching processes, with results exposed through the REST API. All new matching strategies will be rigorously evaluated, and the resulting data will be accompanied by clear provenance information. This project covers six matching tasks:

bibliographic reference matching
funder name matching
preprint matching
affiliation matching
grant matching
title matching

In the meantime, while work continues on integrating matching results into the REST API, we’ve been releasing standalone matching datasets for separate download and analysis. These include relationships between preprints and journal articles, relationships involving research organisations, and relationships between grants and research outputs.

Data infrastructure and Research Nexus participation dashboard

Staying on the data science front, we’ve established an internal data environment that combines all relevant data sources (scholarly metadata, logs and usage data, and external datasets) in their raw forms into a single place. This environment is supported by a suite of modern tools and data processing techniques, enabling data science experiments and analytics pipelines to run effectively at scale.

Building on this foundation, we plan to develop a series of dashboards to monitor the state of the scholarly record over time. These dashboards will feature both work-level and member-level statistics (for example, how many works of a given type have been registered, or how many members are registering grant IDs) as well as more detailed insights at the relationship level (for example, how many bibliographic references have been automatically matched, or how many times ROR IDs are included in funder assertions). Some of these statistics are already available in a public spreadsheet for now, pending the dashboard.

Retraction Watch integration

In 2023, Crossref acquired the Retraction Watch database to make it open data. Initially, this was done through sharing simple CSV files, but this year we have set up a pipeline to feed this information into our REST API, which means that Retraction Watch data is now fully available through the REST API, integrated with Crossref member-supplied retraction and correction metadata. This is the first example of Crossref integrating third-party metadata, and we’re learning a lot about how to best incorporate other datasets in future.

Metadata API and services improvements

From 1 December 2025, we revised rate limits for the REST API to ensure system stability whilst maintaining free access to metadata for everyone. Changes were made to the rate limits for our ‘public’ and ‘polite’ APIs, while the limits for our Metadata Plus users stayed the same. We continue to make all metadata openly available to the whole community.

We also improved how information from our content system feeds into the REST API. A tool we call ‘pusher’—because it pushes information from the content system to the REST API—was rebuilt so that we now have a more reliable transfer of information between our two systems.

While adding to technical improvements, we’ve also worked to better understand the use of and streamline the service offering for paid options. We’ll share more about this year’s Metadata Plus consultation soon. And based on feedback, we have already retired the ‘Query Affiliate’ service, where a handful of organisations still paid us a fee to access our XML API, whereas no credentials have been required for some time.

Strategic theme 3: Manage Crossref openly and sustainably, modernising and making transparent all operations so that we are accountable to the communities that govern us

Infrastructure modernisation

One of our biggest projects of 2025—if not the biggest—was the move from our data centre into the cloud (AWS). For 25 years, Crossref had been running a physical data centre in Massachusetts, USA, but as part of modernising our systems, it was high time to move everything into the cloud. The move to AWS took several months, but we successfully completed this move to the cloud in July this year. We’re spending these last weeks of 2025 fully decommissioning our data centre, which means that we are removing all the equipment we had there and locking the door for the last time.

A part of the move to AWS included moving onto an open-source database solution, PostgreSQL. This reduced our reliance on closed, costly licensed solutions, while also aligning with our POSI commitment to open-source. Running our entire system in AWS provides a more stable, modern approach to our infrastructure, but it also is expensive. We expect to spend about 2 million USD on AWS fees next year, with the majority of this cost coming from REST API usage. Some of the improvements described above will help us manage those costs and better observe traffic patterns.

Our new cloud infrastructure is a bittersweet milestone: while we are happy to not have to rely on a physical presence to support a 24/7 global infrastructure, we also say a sad farewell to our much-loved and long-suffering Sys Admin, Tim Pickard, who has been with Crossref since 2002, and has contributed significantly and unwaveringly to keeping our system up and running in the data centre. Tim will be leaving Crossref at the end of the year; we’re grateful to Tim for all his years of dedication, and we will greatly miss his impressive Hawaiian shirt game on our all-staff calls.

After 25 years, it was also time to get serious about modernising our core content system, because even though it serves our community well, an older system with legacy code is a constant risk and frustration. We’ve therefore embarked on a multi-year modernisation project where we are replacing our old code piece by piece. We no longer want to have one big content system (a monolith), but are planning to identify different pieces of functionality and rebuild these as separate services (a modular, flexible, and robust approach). This year, we already managed to reconstruct some smaller pieces (for example, the ‘pusher’ mentioned above), and next year we will tackle larger projects, such as Metadata Matching and Authentication.

We continue to prioritise open, timely communication for planned or unplanned service interruptions and encourage everyone to monitor our status page at status.crossref.org. We’ll further hone our incident response processes in 2026, including openly posting incident reviews, and we’ll also centre system maintenance and documentation clarity in everything we do.

RCFS Projects

The Resourcing Crossref for Future Sustainability projects (RCFS) and the work of our Membership & Fees Committee resulted in deciding not to change some things (such as the basis for annual membership fees), but to change three things about our fees, as reported in July:

A new lower membership fee tier of 200 USD for members with annual revenues/expenses of under 1000 USD - so far, this includes around 3000 members. See below for more info.
A removal of volume discounts to reduce complexity in our billing code; they were little used, and those who did use these were fine with the loss of the discount.
A removal of the rule that only publishers of a title could register peer review reports (including comments and annotations) at the lower 0.25 USD fee for the first review; this lower fee is now available to any member to register any reviews of any other members’ works.

A new late-breaking addition to these fee decisions is the reduction of fees for members registering grants. As of January 1st 2026, there will be no fee for back-year (BY) grant registration, to encourage the faster adoption of older grants, which are more likely to have research outputs to be matched. This will be a two-year pilot to trial how a reduced fee incentivises adoption and boosts metadata connections, and could be extended to other record types as we monitor its success and sustainability. In addition, the 2 USD fee per current-year (CY) grant record is being reduced to 1 USD in line with the next-nearest fee, this is a permanent change for the foreseeable future.

Membership growth, efficiencies, and accessibility

In March, the board voted to update membership terms and bylaws to clarify processes for suspending and revoking membership, and to be more explicit about member practices that preserve the integrity of the scholarly record. A short-term Member Practices Working Group will be meeting in the first half of 2026 to draft these.

Crossref now serves 23,600 members across 164 countries, with continued growth particularly in Asia and Latin America. We’ve continued our ongoing member onboarding activities to support new members joining the community. We see around 230 new members join each month, and have welcomed 2,700 this year so far. We recently reported on how the shape of membership has evolved over our 25 years of operation.

From January 2026, we’re introducing a new lower membership fee tier of 200 USD for organisations with annual revenue or expenses of 1,000 USD or less, making membership more accessible to low-resourced organisations. Already, over 3000 members have been eligible to move into or join under that fee, and the idea is to monitor how this affects Crossref’s financial sustainability and potentially adjust the 200 USD annual fee down again in future years.

From 1 January 2026, the GEM program, which offers fee-free membership and content registration for all members from certain countries, will expand to include 18 additional countries, further reducing financial barriers to participation in the scholarly record, so we expect several hundred further members to join the existing 600 organisations in this category. More information about the GEM program expansion here.

As our membership base continues to grow, the Membership and Finance teams are constantly exploring ways to make shared processes more efficient. A key component in this work has been the efforts to automate several tasks within both teams to help us manage the additional work caused by our growth and allow our teams to focus more on providing the best quality service we can.

Our membership team continues to support our members, sponsors, service providers, metadata users and the wider community by email and through our community forum. The membership team includes staff members who focus on member support, and staff members who focus on technical support. During 2025 so far, we’ve received 36.8k member enquiries through our support system, a 17% increase from last year. This includes 22.6k inquiries related to general membership and 13k technical support enquiries. We’ve received 3.8k membership applications, and welcomed 2.7k new members.

Growth by the numbers

Crossref continues its steady revenue growth in 2025 due to the expansion of our membership base. With the addition of new members and the general growth of Crossref, comes an increase in the transaction-based tasks our Finance team handles.

So far in 2025 we have issued 14,833 invoices, which is a 9% increase since last year. We’ve seen an 11% increase in the number of payments received and applied, and a 12% increase in the amount of credit and debit memos applied over the same time last year. We have also seen a 42% increase in the number of billing-related tickets, totalling 20,723. A large segment of these tickets are related to fee updates associated with the new $200 membership tier.

Not all transactional work in Finance has increased as steadily, with increased revenue of 8% we have also seen a 14% increase in operating expenses. Through the strategic consolidation of vendors and use of financial tools, we have only seen a 1% increase in Accounts Payable invoices processed.

Organisational sustainability

Finance-wise, we’re doing well. We’re projecting to finish this year with revenue of 14,200,000 USD and expect revenue next year of 14,500,000 USD. We’re budgeting 2% growth in overall revenue, accounting for some of the changes to fees that will reduce our earnings on membership dues, but anticipating continued growth of content registration revenue.

Revenue and expenses trends

About 67% of our expenses come from personnel costs, and the other 33% include non-personnel costs like AWS, travel, legal fees, etc. As we continue to build out the team, we have ten new positions planned for the next year (recruitment for many of these is already underway or done). With additional staff roles and AWS expenses, we’re expecting expense growth of 16%. We post our financial statements and Form 990 filings on the financials page on our website.

Revenue per member size (by tier)

As the chart above shows, we still see ’the long tail’ of smaller members in the lowest fee category (275 USD) contributing more revenue than those in the largest category (50,000 USD) at 5.8 million USD versus 5 million USD.

Another aspect of sustainability is our impact on the world around us. And this year we were able to publish a second report on Crossref’s carbon footprint, having monitored and controlled for several carbon-heavy activities, primarily staff travel. Our reported emissions went up 40% from 2023 to 2024, due to more travel given our growth in staff and members, better recording our emissions (for example, with hotel stays), and including travel that we support for our partners, ambassadors and board members. In terms of travel spending, we are still well below 2019 when we were smaller, demonstrating that we are following through on not going back to the pre-pandemic norm.

We were one of the first open infrastructure organisations to adopt the POSI Principles and now have a few years’ experience in trying to meet them. Together with other adopters, we proposed updates and additions to the principles, based on real-world practice, and gathered a lot of community comment, resulting in the group publishing POSI v2 in October. We conduct a self-assessment every other year and we’ll be involving all our staff in the next self-assessment, due later in 2026.

Open governance through board election and annual meeting

We continued our commitment to being member-led and community-driven. This year’s anniversary Annual Meeting in October brought together members to discuss strategy, metadata developments, and hear the results of their voting in our board election. It comprised two half-days of online conferencing and several in-person satellite meetings spread across five continents, gathering close to 500 members of our community. It was a platform to reflect together on the past quarter of the century of building community infrastructure and connections underpinning the progress of scholarship, and to share plans for the future.

Each member has one vote, and together they elected the following organisations to serve a three-year term alongside the rest of the board:

Tier 1 candidates (electing one seat):

Rebecca Wambua, Distance, Open and e-Learning Practitioners’ Association of Kenya

Tier 2 candidates (electing four seats):

Damian Bird, CABI
Rose L’Huillier, Elsevier*
Anjalie Nawaratne, Springer Nature*
Nick Lindsay, The MIT Press*

*returning board member

Congratulations to the remaining and incoming board members as we start their new term in January 2026. Have a look at all the outputs from our Annual Meeting.

Strategic theme 4: Foster a strong team—because reliable infrastructure needs committed people who contribute to and realise the vision, and thrive doing it

Team structure

We reorganised the team heading into 2025 because we had ambitious goals that required a more structured, collaborative approach. We reorganised the work around three strategic, mission-driven areas of focus described above. This was our first full year with the cross-functional program groups in place, and the activities reported here make it evident that our team members, both existing and new, are firing on all cylinders.

New staff and new roles

We welcomed eight new team members in 2025. In February, we welcomed our new Director of Programs & Services, Helena Cousijn, and a new member of the Technical Support team, Arley Soto. In March, we welcomed our new Community Manager for funders, Rocío Gaudioso Pedraza. In April, we launched our new Data Science team by welcoming Jason Portenoy and Alex Bédard-Vallée. In November, we welcomed our new DevOps Engineer, Thelma Laryea, and our new Program Technical Lead for the OSO program, Bharath Govindarajan. In December, we welcomed another member of the Technical Support team, Natali Giorgobiani.

We also had team members step up into new roles. Dominika Tkaczyk completed the new leadership team by taking on the Director of Technology role, Paul Davis has started his new role as Product Manager, and Michelle Cancel has taken on the Head of Human Resources role. And there’s more to come! As next year begins, two team members will step into Program Technical Lead roles: Carlos del Ojo Elias for the CRN program and Patrick Vale for the CCT program. Together with the Program Technical Lead for the OSO program and the Head of Infrastructure Services, these roles will complete the new structure of the technology team. This structure is more closely aligned with how our work is organised and will enable stronger coordination both within and across cross-functional programs.

Supporting a thriving global culture

As our team grows in different aspects within our new org structure to meet the needs of the community, we remain committed to supporting a thriving culture through training, conducting regular temperature checks, and organising our annual staff retreat. This year, we continued our work on psychological safety and introduced workshops on giving and receiving feedback and on consensus building. We were able to put some of this training into practice at our in-person all-staff event in Split, Croatia, where we all came together to build our roadmap.

We are ending the year with 51 staff in 14 countries and look forward to diversifying and evolving even further as a team in 2026—we’re currently hiring in UX, Communications, and Membership—and keep an eye on our jobs page for forthcoming opportunities in Software, DevOps, Metadata, and Operations!

Thank you to our community of members, partners, board, ambassadors, sponsors, metadata users, service providers, integrators—and of course our team—for making 2025 such a productive year. Together, we’re building a richer, more connected research ecosystem for the benefit of society. We can’t wait to continue the work together in 2026.

Metadata in editorial workflows

Madhura Amdekar — Wed, 03 Dec 2025 00:00:00 +0000

Background

Scholarly metadata, deposited by thousands of our members and made openly available can act as “trust signals” for the publications. It provides information that helps others in the community to verify and assess the integrity of the work. Despite having a central responsibility in ensuring the integrity of the work that they publish, editorial teams tend not be fully aware of the value of metadata for integrity of the scholarly record. How can we change that?

Thousands of publishers and institutions from all over the world, big and small, are Crossref members, providing us rich metadata for their publications. During our discussion with the community on this topic, it has surfaced that it is usually the technical or production teams, which interact closely with Crossref, where the appreciation of benefits and value of metadata remain confined.

Although editors may interact with some aspects of metadata when they screen manuscripts that come their way, it is not evident whether they see metadata as useful for signalling trust. In the last couple of years, we have been specifically engaging with editors, meeting them, speaking to them, and writing for them on this topic. As next steps in this effort, we are now keen to engage with the diverse editorial community to understand where metadata fits in their workflows, and to identify opportunities for providing visibility to the importance of rich metadata.

To get a better grasp on this subject, I reached out to Christine Ferguson, to share her rich experience across many editorial roles with me, and to try and paint a better picture of the mutual gaps in understanding when it comes to publication metadata. Here’s what we discovered about the different editorial roles and some ideas for how Crossref might better engage with editors.

We know that

Our members come in all shapes and sizes, and that is also reflected in the diversity of editorial functions that may exist within their organisations. Some of our publishing members have editorial staff whose role is to screen submissions, which includes checking them to make sure that the manuscripts are formatted correctly, and have all the required information e.g. on ethics approvals, or ORCIDs (Open Researcher and Contributor ID) of authors. They then pass these manuscripts on to an external or an academic editor, who is usually a subject matter expert and is responsible for the editorial oversight of the content, to manage the rest of the peer review process, such as assessing the novelty and scope of the work, inviting and securing reviewers, and making a final decision on the manuscript. The academic editors make up a vast majority of the editorial community, variously serving as the editor-in-chief, section editors, and members of the editorial board. They usually volunteer their time as an editor, while having another primary job function.

Other publishers may have in-house editors who are subject matter experts themselves and manage the peer review process. Manuscripts can come to these editors after initial checks have been performed on them or the editors may also perform these checks, following which selected manuscripts undergo the peer review process.

Production editors assume responsibility for the manuscripts that are accepted. Their role is to make the manuscript production and publication ready, often liaising with the authors to finalise the formatting, and finally assigning it to an issue.

Then there are editorial roles that may be a combination of one or more of the above. The size and operational structure of an organisation may determine how editorial and other responsibilities are delegated within the organisation. For some of our medium or smaller members, it may be that the same individual or team is responsible for one or more tasks related to assessing the scientific content of the manuscript, managing the peer review process, as well as being in charge of the post-production workflows such as registering metadata with Crossref.

There are also emerging publishing workflows involving solicited peer-reviews of preprints or other types of works, which sometimes retain a form of editorial oversight.

In summary, editorial roles and responsibilities may vary quite a lot within our member organisations and we have less clarity about editorial roles and responsibilities within member organisations.

All of these different flavors of editors also interact with metadata at various stages in their workflows. For example, the title of the manuscripts, names of authors, whether they have ORCIDs and what is reflected in their ORCID records, and the abstracts may be used to assess the novelty and integrity of the work under consideration. The names of authors, especially if they are not known personally to the editor, can be verified in part by an ORCID check, ensuring the individuals exist, are affiliated to the organisations as claimed, that they have the relevant expertise to write or contribute to the manuscript, and to be able to find what they have written previously on the subject. Making sure that whether all or some of the authors (e.g. the corresponding author) have provided their ORCIDs, or if the link to where the dataset has been deposited in a repository resolves correctly, is usually a part of the pre-screening or post-acceptance checklists. As our recent metadata awardee, ASM has highlighted that having this metadata can be hugely beneficial during the peer-review management process, such as for identifying conflicts of interest, to ensure data policy compliance, and even for carrying out systematic analyses.

We’d like to know more about…

whether all editors interact with metadata in their workflows, and whether they are sufficiently informed about the power of rich metadata. It is evident that there is a lot of diversity in editorial roles and functions. Editors, whether they are mostly concerned with scientific content or with the manuscript peer-review process, are closely connected to the researcher community and the latest research topics and trends. By virtue of this, they are in an excellent position to ascertain the important metadata elements most relevant in their scholarly community. If we have a better understanding of how editors are using metadata in their workflows, we’d be able to identify specific opportunities for engaging with this key community to create greater recognition of the role of metadata in preserving the integrity of the scholarly record.

What we have in mind is to engage systematically with editorial community members and understand from them how, where, and which metadata are they using in their workflows. We’d like to do so by talking to editors who represent different Crossref members, perhaps in small groups, where participants will be able to share which metadata elements they interact with. We’d also like to share with them information about the use of metadata for research integrity. We’d like to understand whether they have been leveraging metadata in this context and the relevance of this information for them. Via this exercise, we hope to pick out some commonalities about the use of metadata in editorial workflows. Ultimately, we’d like to use this information to create resources that can be used for educating editors (and ultimately the researchers who submit their work for publication) about the importance of metadata, especially in signalling trust and preserving the integrity of the scholarly record.

Announcing changes to REST API rate limits

Martyn Rittman — Wed, 05 Nov 2025 00:00:00 +0000

Our REST API makes all of the metadata we hold publicly available. It receives the majority of our API traffic, with around 1 billion hits per month. It’s one of the key ways that we fulfil our mission to make research objects easy to find, cite, link, assess, and reuse. From 1 December 2025, we will be revising the rate limits for the public and polite pools of the REST API to ensure that we can maintain a stable and reliable system, and that metadata is freely available to everyone.

We haven’t changed the rate limits since the REST API was launched in 2013. In the past five years, the number of requests to the REST API has tripled and the number of metadata records has increased by a third, from 120 million to around 180 million. This means an increase in the resources needed to run it, and we’ve seen periods of instability where we haven’t been able to keep the API available for all users. We have decided that it is the right time to revisit rate limits to check that they’re in line with what our technology can provide and what our community needs. As a result, we will apply the following for the public and polite pools:

Public pool:

Request type	Rate limit	Concurrency limit
Single record	5	1
List of records (queries, filters, etc.)	1	1

Polite pool:

Request type	Rate limit	Concurrency limit
Single DOI record	10	3
List of records (queries, filters, etc.)	3	3

The rate limit is the number of total requests that can be made per second. The concurrency limit is how many requests can be running at the same time. This means that for longer-running requests you may need to wait for previous requests to finish before you can make a new one.

Here are some examples of single records requests:

The second case here will be directed to the polite pool because an email is included using the ‘mailto’ parameter. And here are examples of requests that return lists of records:

The second and third examples here will use the polite pool.

Our guiding principle in making these changes is to keep all of the metadata available to everyone, all of the time. These changes to rate limits won’t restrict current users from accessing the metadata they want to retrieve, but it will make it easier for us to maintain the system now and in the future.

Which use cases do we support?

Our metadata has a broad range of applications. If you’re someone who uses the REST API, we’re glad that you are part of our community! Our mission includes making it easier to find, reuse, and assess scholarly research outputs. By using metadata, you’re helping us to fulfil that goal.

The main uses of the REST API fit into several categories. The new rate limits will continue to support these, among many others:

I have some metadata, what is the DOI?
I have a DOI, what is its metadata?
I want all of the metadata, just give me everything.
Research on a specific topic or subset of metadata, often refreshing the results every few weeks or months.

Rate limits can encourage responsible usage. The majority of API users make requests at a low rate and will not need to make any changes, however a few send spikes of large numbers of requests in a short space of time, sometimes making it difficult for others to access the service. These can be smoothed out by lower rate limits. Complex requests that search across large numbers of items put more pressure on our systems than requests for a single content item, so we have decided to set different rate limits for different types of request.

Who will be affected?

We estimate that the changes might affect around 40 users per week across the public and polite pools, and this is only for some of their requests. In all of the cases we’ve seen, the rate of requests could be slowed down and users would still be able to get the same results. In other words, the aim of these changes is to make the load on the API more predictable, not to reduce the total number of requests or amount of metadata transferred. No changes are being made to the Metadata Plus service or other APIs, such as the XML API and OAI-PMH endpoint.

Do I need to change how I use the API?

If you’re reading this, thank you! It’s clear that you want to be a considerate user of our services. Almost all users can continue to use the REST API in exactly the same way, you won’t need to change anything. Here is some general advice that will help you make the most of the service and ensure that you won’t encounter issues.

Use a mailto parameter. This gives you access to the polite pool meaning higher rate limits and meaning we can get in touch with you if needed. We’ll only use your address to contact you about your API requests.
Check the HTTP response status for your requests. This is always good practice and can help you identify malformed requests and where you reach rate limits.
Cache results to avoid repeatedly making the same requests. Most records don’t change on a regular basis. How often you update the cache will depend on what you are interested in, but most metadata fields rarely change.
If you are making a very high volume of requests or have very complex analysis to carry out, consider downloading the public data file which is made available once a year and contains all of our metadata. You can update it with recent additions using the REST API.
If you are relying on our metadata in a production service, Metadata Plus can provide more stability, support, and access to monthly snapshots of our entire database.

We have more tips and tricks for the REST API in our documentation. If you have questions, please join the conversation on our Community Forum.

New tool to report on completeness of open research information globally

Kornelia Korzec — Tue, 21 Oct 2025 00:00:00 +0000

Wednesday 22nd October 2025—Crossref, the open scholarly infrastructure nonprofit, today releases an enhanced dashboard showing metadata coverage and individual organisations’ contributions to documenting the process and outputs of scientific research in the open. The tool helps research-performing, funding, and publishing organisations identify gaps in open research information, and provides supporting evidence for movements like the Barcelona Declaration for Open Research Information, which encourages more substantial commitment to stewarding and enriching the scholarly record through open metadata.

Crossref’s Participation Reports now offer expanded features and provide full coverage of all members and all resource types registered with Crossref DOIs (Digital Object Identifiers)—over 175 million records representing a significant share of global research production from organisations in 164 countries. Each of Crossref’s 23,000 members has a dashboard to visualise their metadata contributions, display coverage of key information for scholarly works, and get actionable feedback via a gap report that specifies records that need enrichment, all helping to make more transparent the work that goes into creating and curating the scholarly record.

For any Crossref member—whether journal publisher, research funder, university, or museum—coverage of up to 11 key elements is public and visible to everyone, including: references, abstracts, ORCID iDs, affiliation strings, ROR IDs, Open Funder Registry IDs, funding award numbers, text-mining URLs, licence URLs, Similarity Check URLs (for text-based plagiarism checking) and the presence of a Crossmark policy, indicating the organisation’s commitment to declare corrections and retractions. These metadata elements provide greater context and visibility for research objects such as journal articles and preprints, grants and awards, books and book chapters, standards, datasets, conference papers and various ‘other’ content such as scholarly blogs, images, and even physical museum artefacts.

Mochammad Tanzil Multazam, Library Director of Universitas Muhammadiyah Sidoarjo, and Secretary of the Supervisory Board of Relawan Jurnals, says, “As a sponsoring organisation for several thousand small publishers across Indonesia, we support Crossref members to register complete metadata for their works. Despite time and resource constraints, this new actionable open report on key metadata elements will help drive improvements in the information they share for their publications. This has wide-reaching implications for the visibility of that research and trust among the community, and therefore has the potential to support Indonesian scholarship in the global context.”

Lena Stoll, Program Lead at Crossref, explains, “We are happy to have extended participation reports to cover more diverse record types, including grants, datasets, dissertations, and more, and to make it easier for our members to act on their ongoing improvements to enrich their records and build towards the vision of an open and more complete Research Nexus.”

Ludo Waltman, Scientific Director and Professor of Quantitative Science Studies at the Centre for Science and Technology Studies (CWTS) at Leiden University, comments, “As a representative of the researcher and metascience communities, this data is of great importance for us to analyse the trends and effects of global research activity. Crossref is one of the main driving forces in open infrastructure, and its commitment to supporting metadata completeness through this open reporting dashboard is a significant step for the open research information movement.”

Access Crossref Participation Reports and search for any Crossref member organisation.

Participation report for a typical Crossref member, Universidad La Salle Arequipa in Peru

About Crossref

Crossref runs an open infrastructure to link research objects, entities, and actions, creating a lasting and reusable scholarly record that underpins open science. Together with their 23,000 members in 164 countries, Crossref drives metadata exchange and supports nearly 2 billion monthly API queries, facilitating global research communication, for the benefit of society.

Integrating grant metadata for seamless research interconnectivity at FCCN|FCT

Rocío Gaudioso Pedraza — Wed, 15 Oct 2025 00:00:00 +0000

Click here for the version in Portuguese

Welcome back to our series of case studies of research funders using the Grant Linking System. In this interview, I talk with Cátia Laranjeira, PTCRIS Program Manager at FCCN|FCT, Portugal’s main public funding agency, about the agency’s approach to metadata, persistent identifiers, Open Science and Open Infrastructure. With a holistic approach to the management, production and access to information on science, FCCN|FCT’s decision to implement the Grant Linking System within their processes was not simply a technical upgrade, but a coordinated effort to continue building a strong culture of openness. With the mantra “register once, reuse always”, FCCN|FCT efforts to embrace open funding metadata was only logical.

Could you introduce your organisation?

We are FCCN, the digital services of the FCT, the Foundation for Science and Technology, which is the main public funding agency in Portugal. FCT supports research and innovation in Portugal through multiple funding instruments targeting researchers, projects, institutions and international partnerships. FCCN is focused on providing digital services to the scientific and academic community in Portugal.

I am the manager of a program called PTCRIS, part of the FCCN, within the ‘Scientific Knowledge’ pillar of the unit. PTCRIS is a broad program, whose main goal is to fulfill the mantra ‘register once, reuse always’. We aim to develop an integrated ecosystem of scientific information, so all the projects we run have this main goal and that’s what we work towards. We develop infrastructure and added-value services, such as the scientific curriculum vitae management platform and an indicator system that exposes information of all the funding that supports research and innovation in Portugal.

What motivated you to join Crossref?

We had already adopted ORCID and we also developed a national PID, connected to the citizen card additional to ORCIDs. In 2015 we adopted the ISNI and we also had DOIs for research outputs. So we were clearly missing one piece, which was metadata for funding. At the same time we started developing a national infrastructure on science and technology funding, to have an aggregated and holistic view of the funding that is distributed in Portugal.

Before that the information was scattered across different databases and websites from many different funders, so we organised and aggregated this information into a platform called SciPROJ, which brings together all the information on scientific funding in one place, with quick and flexible access. But we didn’t have persistent identifiers for grants, and this was at the same time that Crossref started to build the Grant Linking System, so we were actually one of the first organisations to join, and in 2023 we had a pilot, where we registered 6000 grants, and we have been registering funding metadata ever since.

Can you tell us about your experience using the Grant Linking System?

The beginning of the pilot was the most critical stage of the process; some effort was needed to map our data models to the Crossref grant metadata schema. FCCN wasn’t in a bad position to do this since we already had all that information in a registry and it was well organised, we just had to map them to make sure that the information we had could be shared following the Crossref metadata schema and best practices. It has been two years since the pilot, which puts us in phase 2 of the implementation of the system. During the pilot we concentrated on registering both historical and current grants’ metadata, in the current phase, we are focusing on current grants’ metadata.

What do you find useful about registering grant metadata with Crossref?

Although this is the very beginning of this journey, we envision a world where we have the ability to link grants to any other object and entity that comprises the ecosystem: people that execute that funding, projects, institutions, outputs. Outputs are something particularly important to us, like for many other funders, because we want to be able to monitor the impact of our funding and that is something that is always at the back of our mind.

We are actually developing more and more services that aim to show how these links can be very useful to retrieve information from the system. For example, we are developing an indicator system that is focusing on the funding but also on the outputs and the links between the two. We are also monitoring OA trends, to see how FCT funding is contributing to Open Science initiatives.

Additionally, our OA policy was recently launched but we currently don’t have any system that allows us to track policy compliance. We are working towards that, but to achieve this it is absolutely fundamental that grants are linked to the outputs through metadata.

What are your hopes for the GLS and greater transparency in funding metadata in general?

The interconnectivity and interoperability of entities and objects, which is something that the field of scientific information management has always wanted to do, but that it’s very difficult to do. There have been attempts in the past to achieve this using information from the acknowledgement sections of publications, but this is fairly inefficient and there needs to be more structure to it. A critical piece of this puzzle would be to influence publishers, manuscript submission platforms to facilitate the systematic sharing of grant IDs and grant metadata by design. I think this is something that is still missing and that I would like to see happening soon.

Has anything surprised you while implementing the Grant Linking System?

Something that we have seen that was surprising was that researchers, who in general are not that concerned about PIDs, when it came to grant IDs, they would ask us proactively what the Crossref grant ID for their award was! It was very refreshing to see that we didn’t need to do any advertising to socialize Crossref grant IDs among our grant holders. I think that tells you about the high level of awareness there is within our community of the importance of the Crossref grant ID, using it and putting it in the acknowledgment section of their publications.

Based on your experience, what would be your advice for colleagues from other research funders?

I would say go for it! The more the merrier! This is like any other similar information system – it only works if there are enough people using it, registering grants metadata that facilitate the links between objects.

It is a very easy process to get into. Once you map the metadata schema to your own data it’s not a technically difficult thing to do. For us it’s an automated process that runs very smoothly, from grant registration to communicating this information to grant holders. We can see this in action in this example: the grantee published an article that acknowledges their funding through Crossref’s grants IDs or funding received being acknowledged in the website of a Research Center.

If you could change something about the GLS or how the grant metadata you register is used, what would it be?

I would love to have access to a visualization of grants’ metadata, how many outputs are linked to, and how they relate to other objects and entities. That would really give us a clearer understanding of the impact that our funding is having. We’d also love to see better integration between Crossref and ORCID for grants—just like it works for publications. Ideally, when a grant is registered and linked to a researcher, they’d be notified and could easily add it to their ORCID record. This would allow the information to flow seamlessly into their national CV via PTCRISsync, ensuring consistency and reducing manual work.

We are grateful to Cátia Laranjeira and FCT|FCCN for sharing their perspective and long-standing experience in this space. Their experience highlights the role that funding metadata plays in an interconnected and complete research and funding ecosystem.

Version in Portuguese

Translation by Edilson Damasio

Integração de metadados de financiamento pela FCCN|FCT para reforçar a interoperabilidade da informação sobre a atividade científica

Bem-vindo(a) de volta à nossa série de estudos de caso sobre instituições financiadoras de investigação que utilizam o Grant Linking System. Nesta entrevista, conversamos com Cátia Laranjeira, gestora do programa PTCRIS na FCCN|FCT, a principal agência pública de financiamento à ciência em Portugal, sobre a abordagem da instituição aos metadados, identificadores persistentes, Ciência Aberta e Infraestruturas Abertas.

Com uma abordagem holística à gestão, produção e acesso à informação científica, a decisão da FCCN|FCT de integrar o Grant Linking System nos seus processos não representou apenas uma evolução técnica, mas sim um esforço coordenado para consolidar uma forte cultura de abertura. Sob o lema “registar uma vez, reutilizar sempre”, a adoção de metadados abertos de financiamento pela FCCN|FCT foi um passo natural e coerente com essa visão.

Poderia apresentar a sua organização?

A FCCN é a unidade de serviços digitais da FCT — Fundação para a Ciência e a Tecnologia, a principal agência pública de financiamento à ciência em Portugal. A FCT apoia a investigação e a inovação através de diversos instrumentos de financiamento dirigidos a investigadores, projetos, instituições e parcerias internacionais. A FCCN dedica-se a disponibilizar serviços digitais à comunidade científica e académica portuguesa.

Na FCCN|FCT, sou gestora do PTCRIS, um programa integrado no pilar do Conhecimento Científico. O PTCRIS é um programa abrangente que tem como objetivo central concretizar o princípio “registar uma vez, reutilizar sempre”. Trabalhamos para desenvolver um ecossistema integrado de informação científica, e todos os projetos que conduzimos convergem nesse propósito. Desenvolvemos infraestruturas e serviços de valor acrescentado, como a plataforma de gestão do currículo científico CIÊNCIAVITAE e um sistema de indicadores que disponibiliza informação sobre todos os financiamentos que apoiam a investigação e a inovação em Portugal.

O que motivou a adesão à Crossref?

A FCCN tinha já adotado o ORCID e desenvolvido um identificador nacional persistente (PID), ligado ao cartão de cidadão, como complemento aos ORCIDs. Em 2015, adotámos o ISNI e também tínhamos DOIs para a produção científica. Ficava claramente em falta um elemento: os metadados de financiamento.

Ao mesmo tempo, iniciámos o desenvolvimento de uma infraestrutura nacional de financiamentos de ciência e tecnologia, com o objetivo de ter uma visão agregada e holística do financiamento que suporta a investigação e inovação em Portugal.

Antes disso, a informação estava dispersa por diferentes bases de dados e websites de múltiplos financiadores. Organizámos e agregámos esta informação numa plataforma chamada SciPROJ, que reúne toda a informação sobre financiamentos científicos num único local, com acesso rápido e flexível. No entanto, ainda não existiam identificadores persistentes para os financiamentos, coincidindo com o momento em que a Crossref começou a desenvolver o Grant Linking System. Fomos, assim, uma das primeiras organizações a aderir. Em 2023, realizámos um piloto com 6.000 financiamentos registados, e desde então temos vindo a registar continuamente os metadados de financiamento.

Pode falar-nos sobre a sua experiência com o Grant Linking System?

A FCCN iniciou a utilização do Grant Linking System com um piloto, que constituiu a fase mais crítica do processo. Foi necessário algum esforço para mapear os nossos modelos de dados para o esquema de metadados de financiamentos da Crossref. A FCCN estava, no entanto, bem posicionada para isso, uma vez que já dispunha de toda a informação num registo organizado; o passo necessário foi apenas assegurar que esta informação pudesse ser partilhada de acordo com o esquema de metadados da Crossref e as melhores práticas.

Já passaram dois anos desde o piloto, o que nos coloca na fase 2 de implementação do sistema. Durante o piloto, focámo-nos no registo de metadados de financiamentos históricos e atuais; na fase atual, estamos focados no registo de metadados de financiamentos atuais.

O que considera útil no registo de metadados de financiamento na Crossref?

Embora este seja ainda o início deste percurso, a FCCN idealiza um ecossistema em que seja possível ligar financiamentos a qualquer outro objeto ou entidade do sistema científico — projetos, pessoas que executam esses financiamentos, instituições onde são executados e produções científicas que dele resultam. Estes últimos são particularmente importantes para nós, como para muitos outros financiadores, pois queremos monitorizar o impacto do financiamento — uma preocupação que está sempre presente no nosso trabalho.

Estamos, de facto, a desenvolver serviços que demonstram o valor dessas ligações para a recuperação de informação no sistema. Um exemplo é o sistema de indicadores em desenvolvimento, que se centra nos financiamentos, nas produções científicas e nas relações entre ambos. Estamos também a acompanhar as tendências de Ciência Aberta, para perceber de que forma o financiamento da FCT está a contribuir para as iniciativas de Open Science.

Além disso, a política de Acesso Aberto da FCT foi recentemente lançada, mas ainda não dispomos de um sistema que permita monitorizar a conformidade com essa política. Estamos a trabalhar nesse sentido, mas para o concretizar é absolutamente essencial que consigamos associar inequivocamente os financiamentos às produções científicas através de metadados.

Quais são as suas expectativas para o GLS e para uma maior transparência dos metadados de financiamento em geral?

A interconectividade e interoperabilidade entre entidades e objetos é algo que a área da gestão de informação científica sempre procurou alcançar — embora seja um objetivo difícil de concretizar. No passado, houve várias tentativas nesse sentido, recorrendo à informação presente nas secções de agradecimentos das publicações, mas esse método revelou-se pouco eficiente e carece de uma estrutura mais sistemática.

Uma peça essencial deste puzzle seria influenciar as editoras e as plataformas de submissão de manuscritos a facilitarem a partilha sistemática de identificadores e metadados de financiamento. Este é um elemento que ainda falta concretizar, mas que gostaríamos de ver implementado em breve.

Algo o surpreendeu durante a implementação do Grant Linking System?

Algo que nos surpreendeu durante a implementação do Grant Linking System foi a reação dos investigadores. Normalmente, os investigadores não demonstram grande preocupação com identificadores persistentes (PIDs), mas, neste caso, começaram a procurar ativamente o identificador Crossref do seu financiamento! Foi muito positivo perceber que não foi necessário fazer qualquer esforço de divulgação para promover o uso dos Grant IDs da Crossref entre os beneficiários dos financiamentos. Isso mostra o nível de consciência existente na comunidade científica sobre a importância destes identificadores — usá-los e incluí-los na secção de agradecimentos das publicações.

Com base na sua experiência, qual seria o seu conselho para colegas de outros financiadores de investigação?

Com base na nossa experiência, o conselho para outros financiadores seria simples: avancem! Quanto mais, melhor! Este tipo de sistema de informação só é verdadeiramente eficaz quando há muitas entidades a utilizá-lo, a registar metadados de financiamento e a criar ligações entre objetos.

É também um processo simples de implementar. Uma vez feito o mapeamento entre o esquema de metadados e os dados internos da instituição, não há grandes desafios técnicos. No nosso caso, o processo é totalmente automatizado e flui de forma eficiente, desde o registo do financiamento até à comunicação dessa informação aos beneficiários. É possível ver isso em prática em vários exemplos — desde artigos que reconhecem o financiamento através dos Grant IDs da Crossref até ao reconhecimento do apoio financeiro nos sites dos centros de investigação.

Se pudesse alterar algo no GLS ou na forma como os metadados dos subsídios que regista são utilizados, o que seria?

Se pudéssemos mudar algo no Grant Linking System ou na forma como os metadados de financiamento são utilizados, gostaríamos de ter acesso a uma visualização interativa que mostrasse quantas produções científicas estão ligadas a cada financiamento e como esses se relacionam com outras entidades e objetos. Isso permitiria compreender de forma muito mais clara o impacto real dos financiamentos.

Gostaríamos também de ver uma melhor integração entre a Crossref e o ORCID no que respeita aos financiamentos — tal como já acontece com as publicações. Idealmente, quando um financiamento fosse registado e associado a um investigador, este seria notificado e poderia adicioná-lo facilmente ao seu registo ORCID. Assim, a informação fluiria automaticamente para o currículo nacional via PTCRISsync, garantindo consistência e reduzindo o trabalho manual.

Agradecemos à Cátia Laranjeira e à FCT|FCCN por partilharem a sua perspetiva e longa experiência neste domínio. A sua experiência destaca o papel que os metadados de financiamento desempenham num ecossistema de investigação e financiamento interligado e completo.

Connecting the dots: FWFs transition to linked grant metadata to support a thriving culture of openness

Rocío Gaudioso Pedraza — Wed, 23 Jul 2025 00:00:00 +0000

Click here for the version in German

As a new Community Engagement Manager at Crossref, dedicated to working with the funders community, I frequently hear requests for examples and case studies of adopting Crossref’s Grant Linking System (GLS) by ‘funders like us’. This has spurred me to start a series of blog posts presenting funders’ perspectives on joining Crossref and using our system – to demonstrate how it’s done.

In the first case study of a series, I speak with Katharina Rieck, Open Science Manager at the Austrian Science Fund (FWF), Austria’s national funding agency for basic research, about the agency’s approach to research metadata, transparency and openness, and the role that the Grant Linking System plays in it.

With a strong track record in Open Access and Open Science, the FWF’s decision to implement grant IDs represents more than a mere technical upgrade. What began as an initiative to enhance the openness and interoperability of grant information illustrates that truly open research infrastructure is not solely a matter of systems, but about people, policies and collaboration.

Katharina was also elected to the Crossref Board at our November 2024 Annual Meeting, and started her three-year term in January 2025.

Could you introduce your organisation? And what is your role?

The Austrian Science Fund (FWF) is Austria’s national funding agency for basic research. The FWF funds all disciplines, from Social Sciences and Humanities to Life Sciences and Natural Sciences and Technology. As Open Science Manager, I am responsible for developing the FWF’s Open Science strategy, including the development of the Open Access Policy for Peer-Reviewed Publications, the Open Access Policy for Research Data as well as the FWF Research Data Management Policy. I am also responsible for the development and implementation of funding instruments such as the FWF Open-Access Block Grant and support for Open Science infrastructures.

What motivated you to join Crossref?

For more than two decades, the FWF has actively promoted and supported various aspects of Open Science. In 2004, it published its first Open Access Policy, making it one of the first funding organizations worldwide to adopt an Open Access policy for publications. In line with the commitment to open research information as a core pillar of Open Science, the FWF has taken further steps to strengthen openness and transparency: it joined Crossref to register grant DOIs and became a signatory of the Barcelona Declaration on Open Research Information and joined Crossref to register grant DOIs.

While funding metadata––information about projects funded by the FWF––has long been freely available on our website, the launch of the Research Radar in 2023 marked a significant step forward. Our goal was not only to maintain accessibility but to ensure that the data published in the Research Radar is interoperable and aligned with the FAIR principles. By implementing the Grant Linking System from Crossref, we assign each FWF funded project a unique, persistent identifier with associated metadata, helping to make FWF grant information open, interoperable and sustainable.

Can you tell us about your experience using the Grant Linking System?

We have been using the Grant Linking System since November 2023. With the launch of the FWF’s new website and the introduction of the Research Radar, we began registering Crossref grant IDs (DOIs) for all grants included in the Research Radar database. As a result, all FWF-funded projects dating back to 1995 are now uniquely identifiable. The process of registering grant metadata with Crossref is straightforward, and we have set up a smooth internal workflow that enables the registration of DOIs after the FWF’s funding decision.

It is important to note that implementing Crossref grant IDs involved more than just a technical setup––it required the development of new internal processes and coordination through a dedicated Crossref grant DOI implementation group. The implementation process also resulted in a revised structure for grant numbers (DOI suffixes) for FWF-funded projects, establishing a sustainable and future-proof system.

How was your journey to socialise the Grant Linking System within your research community? How did you communicate the importance of identifiers and grant metadata to your grant holders?

The introduction of grant DOIs was supported by a comprehensive communication strategy, including dedicated online resources (e.g., New Identification Numbers for FWF Projects –– FWF), updates across multiple pages of the FWF website (such as Carrying out Your Project –– FWF), and presentations at various events. This communication strategy aimed to explain the purpose and value of the “new numbers” ensuring that researchers and stakeholders understood how this contributes to greater visibility, traceability, and openness of funded research.

As a funding organisation, we require grant recipients to acknowledge FWF support in all research outputs resulting from their projects. With the integration of grant DOIs into FWF’s metadata, the standardised acknowledgment text was updated to ensure that the DOIs are now included in outputs. The new required wording is: ‘This research was funded in whole or in part by the Austrian Science Fund (FWF) [grant DOI],’ and is now a requirement in the FWF funding agreement. Including the grant DOI both in the output metadata and the acknowledgment text enhances traceability and supports more effective analysis of FWF-funded outputs.

What do you find useful about registering grant metadata with Crossref?

One of the key benefits of registering grant metadata is the enhanced interconnectivity and the unique identification of FWF’s grant information. By registering our grants with Crossref, funding information becomes more than just information on the FWF website––it becomes interoperable data that is accessible and reusable. This not only increases visibility but also enables us to better analyse the outcomes of funded projects and ensures that the data is accessible as well as (re)usable by the broader research community.

In addition to assigning Crossref Grant IDs and registering grant metadata, the FWF has required ORCID IDs for researchers since 2016 and mandates the use of ROR IDs for institutions. The consistent use of persistent identifiers in metadata ensures the interoperability of FWF grant information and facilitates seamless integration with external data sources.

What are your hopes for the GLS and greater transparency in funding metadata in general?

The FAIRness and openness of research information––including metadata on funding information, research outputs, researchers, and institutions––are fundamental to a well-functioning research ecosystem. I hope to see a broader adoption of persistent identifiers in metadata, particularly in grant information, as well as a broader commitment to openly sharing research information as expressed in the Barcelona Declaration. Moreover, a key objective should be to ensure the highest possible accuracy of metadata at the point of entry. This entails, for instance, that publication metadata accurately includes funding metadata.

What were the key challenges you encountered when embracing the GLS, and how did you overcome them?

One of the key challenges we encountered when adopting the GLS was ensuring seamless integration in our existing IT infrastructure and workflows. Integrating the new number across different systems required considerable coordination. We overcame this challenge by establishing a dedicated implementation team that included IT experts.

Another challenge involved communicating and disseminating information regarding the grant DOI, ensuring that researchers and other relevant stakeholders were adequately informed. This was successfully managed through targeted and comprehensive communication efforts.

Based on your experience, what would be your advice for colleagues from other research funders?

It is important to recognise that registering grant identifers and metadata goes beyond a mere technical implementation. This is an opportunity to engage with diverse stakeholders, rethink processes and highlight the value of open funding metadata for the entire research community.

We are grateful to Katharina Rieck and FWF for generously sharing their insights and know-how. Their experience highlights the importance of seeing metadata not just as information, but as a shared resource that connects and empowers the research community.

Version in German

The title has been changed slightly from the original version. Translation by Lena Stoll.

Connecting the Dots: Wie der FWF durch die Umstellung auf vernetzte Fördermetadaten eine Kultur der Offenheit fördert

Als neue Community-Engagement-Managerin bei Crossref, die sich der Zusammenarbeit mit Fördergebern widmet, werde ich häufig gefragt, ob ich Beispiele und Fallstudien von „Förderern wie uns“ geben kann, die Crossrefs Grant Linking System (GLS) bereits eingeführt haben. Dies hat mich dazu veranlasst, eine Blogreihe zu starten, in der ich die Perspektiven von Fördergebern auf eine Crossref-Mitgliedschaft und die Nutzung unseres Systems vorstelle – um zu zeigen, wie es funktioniert.

In der ersten Fallstudie dieser Reihe spreche ich mit Katharina Rieck, Open-Science-Managerin beim Österreichischen Wissenschaftsfonds FWF, Österreichs nationaler Förderagentur für Grundlagenforschung, über den Ansatz des FWF zu Forschungsmetadaten, Transparenz und Offenheit sowie über die Rolle, die das Grant Linking System dabei spielt.

Mit seiner langjährigen Erfahrung im Bereich Open Access und Open Science stellt die Entscheidung des FWF, Grant-IDs (DOIs für Fördermittel) einzuführen, mehr als nur eine technische Verbesserung dar. Die Initiative begann mit dem Ziel, die Offenheit und Interoperabilität von Förderinformationen zu verbessern, aber schon bald wurde klar, dass eine wirklich offene Forschungsinfrastruktur nicht nur eine Frage der Systeme ist, sondern auch Menschen, Regelwerke, Abläufe und die Zusammenarbeit betrifft.

Katharina Rieck wurde auf unserer Jahresversammlung im November 2024 außerdem in Crossrefs Board of Directors gewählt und ist im Januar 2025 ihre dreijährige Amtszeit angetreten.

Bitte stellen Sie den FWF kurz vor und erklären Sie unseren Leser:innen, was Ihre Rolle dort ist.

Der Österreichische Wissenschaftsfonds FWF ist Österreichs nationale Förderorganisation für Grundlagenforschung. Der FWF fördert alle Disziplinen, von den Sozial- und Geisteswissenschaften über die Lebenswissenschaften bis hin zu Naturwissenschaften und Technik. Als Open-Science-Managerin bin ich für die Entwicklung der Open-Science-Strategie des FWF verantwortlich, einschließlich der Entwicklung der Open-Access-Policy für begutachtete Publikationen, der Open-Access-Policy für Forschungsdaten sowie der FWF-Richtlinie zum Forschungsdatenmanagement. Darüber hinaus bin ich verantwortlich für die Entwicklung und Umsetzung von Förderinstrumenten wie der Open-Access-Pauschale des FWF sowie die Unterstützung von Open-Science-Infrastrukturen.

Was hat Sie dazu bewogen, Crossref beizutreten?

Der FWF fördert und unterstützt seit mehr als zwei Jahrzehnten aktiv verschiedene Aspekte von Open Science. 2004 veröffentlichte er seine erste Open-Access-Policy und war damit eine der ersten Förderorganisationen weltweit, die eine Open-Access-Policy für Publikationen eingeführt haben. Im Einklang mit seinem Engagement für offene Forschungsinformationen als zentrale Säule von Open Science hat der FWF weitere Schritte unternommen, um Offenheit und Transparenz zu stärken: Der FWF ist Crossref beigetreten, um Grant-DOIs zu registrieren, und ist Unterzeichner der Barcelona Declaration on Open Research Information.

Zwar sind Metadaten zur Forschungsförderung – also Informationen über FWF-geförderte Projekte – schon seit Langem über unsere Website frei verfügbar. Doch die Einführung des Research Radar im Jahr 2023 war nochmal ein bedeutender Fortschritt. Unser Ziel war es nicht nur, den offenen Zugang zu den Metadaten aufrechtzuerhalten, sondern auch sicherzustellen, dass die im Forschungsradar veröffentlichten Daten interoperabel und mit den FAIR-Prinzipien vereinbar sind. Durch die Anwendung von Crossrefs Grant Linking System bekommt jetzt jedes vom FWF geförderte Projekt eine eindeutige, unveränderliche ID mit dazugehörigen Metadaten – und die Informationen zu FWF-Fördermitteln sind somit offen, interoperabel und nachhaltig verfügbar.

Können Sie uns mehr über Ihre Erfahrungen mit dem Grant Linking System erzählen?

Wir nutzen das Grant Linking System seit November 2023. Mit dem Launch der neuen FWF-Website und des Research Radar begannen wir damit, Crossref-Grant-IDs (DOIs) für alle in der Forschungsradar-Datenbank enthaltenen Förderungen zu registrieren. Dadurch sind nun alle FWF-geförderten Projekte seit 1995 eindeutig identifizierbar. Die Registrierung von Grant-Metadaten bei Crossref ist unkompliziert, und wir haben einen reibungslosen internen Workflow entwickelt, um DOIs nach der Förderentscheidung des FWF zu registrieren.

Es ist wichtig zu erwähnen, dass es für die Einführung von Crossref-Grant-IDs mehr als nur den Aufbau technischer Prozesse brauchte – wir haben auch neue interne Abläufe entwickelt und eine eigene Arbeitsgruppe für die Koordination von Crossref-Grant-DOIs gebildet. Im Zuge dieses Prozesses haben wir auch die Struktur der Projektnummern für FWF-geförderte Projekte (also der DOI-Suffixe) überarbeitet und somit ein nachhaltiges und zukunftssicheres System aufgebaut.

Welche Erfahrungen haben Sie damit gemacht, das Grant Linking System in Ihrer Forschungscommunity zu bewerben? Wie haben Sie Ihren Fördernehmer:innen die Wichtigkeit von Identifiern und Metadaten vermittelt?

Wir haben die Einführung der Grant-DOIs mit einer umfassenden Kommunikationsstrategie unterstützt, inklusive spezieller Online-Ressourcen (z. B. Neue Identifikationsnummern für FWF-Projekte), der Aktualisierung mehrerer Seiten auf der FWF-Website (z. B. Projekt durchführen) sowie Vorträgen bei diversen Veranstaltungen. Ziel dieser Kommunikationsstrategie war es, Zweck und Nutzen der „neuen Nummern“ zu erläutern und sicherzustellen, dass Forschende und Stakeholder verstehen, wie diese zu mehr Sichtbarkeit, Nachvollziehbarkeit und Offenheit der geförderten Forschung beitragen.

Als Förderorganisation verlangen wir von unseren Fördernehmer:innen, die Unterstützung durch den FWF in allen Forschungsergebnissen zu erwähnen, die aus dem Projekt resultieren. Mit der Integration der Grant-DOIs in die Metadaten des FWF haben wir den standardisierten Acknowledgement-Text aktualisiert, um sicherzustellen, dass die DOIs in den Ergebnissen erwähnt werden. Der neue erforderliche Wortlaut ist: „Diese Forschung wurde gänzlich oder teilweise durch den Wissenschaftsfonds FWF finanziert [Grant-DOI].“ und ist in jedem FWF-Fördervertrag festgeschrieben. Die Angabe von Grant-DOIs sowohl in den Metadaten als auch im Acknowledgement-Text von wissenschaftlichem Output verbessert die Rückverfolgbarkeit und ermöglicht eine genauere Analyse der vom FWF geförderten Ergebnisse.

Was finden Sie an der Registrierung von Fördermetadaten bei Crossref am hilfreichsten?

Einer der Hauptvorteile der Registrierung von Fördermetadaten ist die verbesserte Vernetzung und die eindeutige Identifizierung der Förderinformationen des FWF. Durch die Registrierung unserer Projekte bei Crossref werden Förderinformationen zu mehr als nur Informationen auf unserer Website – sie werden zu interoperablen Daten, die abrufbar und wiederverwendbar sind. Dies erhöht nicht nur die Sichtbarkeit, sondern ermöglicht uns auch eine bessere Analyse der Ergebnisse geförderter Projekte und stellt sicher, dass die Daten für die allgemeine Forschungsgemeinschaft zugänglich und (wieder-)verwendbar sind.

Neben der Vergabe von Crossref-Grant-IDs und der Registrierung von Fördermetadaten schreibt der FWF seit 2016 ORCID für Forschende sowie die Verwendung von ROR IDs für Institutionen vor. Die konsequente Verwendung persistenter IDs in den Metadaten gewährleistet die Interoperabilität der FWF-Förderinformationen und erleichtert die nahtlose Integration mit externen Datenquellen.

Was erhoffen Sie sich vom GLS und von mehr Transparenz bei Fördermetadaten im Allgemeinen?

Die FAIRness und Offenheit von Forschungsinformationen – einschließlich der Metadaten zu Förderinformationen, Forschungsergebnissen, Forschenden und Institutionen – sind für ein gut funktionierendes Forschungsökosystem wesentlich. Ich hoffe auf eine weiterreichende Anwendung von persistenten IDs in Metadaten, insbesondere in Förderinformationen, und auf ein größeres Engagement für den offenen Austausch von Forschungsinformationen, wie es zum Beispiel in der Barcelona Declaration on Open Research Information gefordert wird. Darüber hinaus sollte sichergestellt werden, dass die Metadaten bereits bei der Eingabe und damit bei ihrer Generierung möglichst korrekt sind. Das bedeutet unter anderem, dass die Metadaten von Publikationen die korrekten Fördermetadaten enthalten sollten.

Welche Herausforderungen sind bei der Einführung des GLS aufgetreten und wie haben Sie diese gemeistert?

Eine der größten Herausforderungen bestand darin, das Grant Linking System nahtlos in unsere bestehende IT-Infrastruktur und Arbeitsabläufe zu integrieren. Die „neue Nummer“ in die unterschiedlichen Systeme zu integrieren, bedeutete einen hohen Koordinationsaufwand. Gemeistert haben wir diese Herausforderung durch die Bildung einer eigenen Arbeitsgruppe für die Anwendung von Crossref-Grant-DOIs, in der auch IT-Expert:innen vertreten waren.

Eine weitere Herausforderung bestand in der Kommunikation und Verbreitung von Informationen zu Grant-DOIs, um Forschende und andere Stakeholder angemessen zu informieren. Das haben wir durch gezielte und umfassende Kommunikationsmaßnahmen erreicht.

Basierend auf Ihrer eigenen Erfahrung, welchen Ratschlag würden Sie Kolleg:innen bei anderen Fördergebern mitgeben?

Es ist wichtig zu verstehen, dass die Registrierung von Grant-IDs und Metadaten über eine bloße technische Umsetzung hinausgeht. Der Prozess bietet die Gelegenheit, mit verschiedenen Stakeholdern in Kontakt zu treten, Abläufe zu überdenken und den Wert offener Fördermetadaten für die gesamte Forschungsgemeinschaft zu unterstreichen.

Wir danken Katharina Rieck und dem FWF für ihre Bereitschaft, ihre Erkenntnisse und ihr Know-how so großzügig zu teilen. Ihr Erfahrungsbericht hat uns gezeigt, wie wichtig es ist, Metadaten nicht nur als Informationen zu betrachten, sondern als eine gemeinsame Ressource, die die gesamte Forschungsgemeinschaft vernetzen und stärken kann.

Scholarly blogs and their place in the research nexus

Lena Stoll — Tue, 24 Jun 2025 00:00:00 +0000

If you are reading this blog on our website, you may have noticed that alongside each post we now list a Crossref DOI link, which was not the case a few months ago (though we have retroactively added DOIs to all older posts too). You can find the persistent link for this post right above this paragraph. Go on, click on it, we’ll wait.

Are you back here? Good. As you probably expected, the DOI link for this post resolves to the post itself, and you should use it anytime you want to cite this post. But the DOI does more than just point readers to this page––it is part of a rich metadata record that includes the authors’ ORCID iDs, the publication date, and more. In other words, the posts on this blog are part of what we call the research nexus: the open network of relationships connecting research outputs, people, organisations, and actions.

Crossref research nexus vision

Why blogs deserve a place in the scholarly record

A blog post may not be the first thing that comes to mind when you think of scholarly outputs. But scholarly blogs have been around since at least the early 2000s and have carved out a niche for themselves as a type of “grey literature” that allows researchers to write about research in a way that may not fit neatly into more traditional, peer-reviewed publishing venues, but also is too long-form for social media. Science blogs can give readers a window into ongoing work that isn’t ready to publish yet, serve as a self-publishing venue, or allow researchers to comment on others’ work and recent developments in science and science communication. These kinds of perspectives add crucial context to the scholarly record that should not be overlooked.

However, as Martin Fenner explained at the #Crossref2023 annual meeting, blogs have largely not benefitted from the metadata and long-term archiving solutions that tend to be applied to more “traditional” forms of publishing. As a result, most blogs have been left out of the scholarly record. But in recent years, there have been some efforts in the community to change this. Earlier this year, ORCID added support for the work type blog post, among others, to align more closely with the Confederation of Open Access Repositories (COAR) vocabulary of resource types.

At our 2025 midyear community update, we asked our community what content types they saw as growing in importance. Blog posts were mentioned several times as a ‘trending’ record type, and as one that members would like to see support for in the Crossref system.

Eating our own dog food

We had already been thinking for a while about how our own blog should be a part of the research nexus. We started out by manually uploading XML files through our Admin tool for each post. We did this for a few months and quickly found, like many of our members do, that this can be a laborious and error-prone process.

In the product management world, the process of using the products you usually spend your time building and maintaining is often referred to as dogfooding. The idea is that firsthand experience makes it easier to understand your end users’ needs and feel their pain - and we have certainly found that registering metadata for our blog posts has reinforced the importance of making manual registration easier for our members, but also of supporting and enabling machine-to-machine integrations.

What did we do?

The Crossref website, which includes this blog, uses an open-source static site generator named Hugo. Rather than using a content management system (CMS), we edit the website content in Markdown format using code editors. Whenever we start working on a post for this blog, we not only write the content of the post itself, but also include some front matter for the page, which contains some key metadata about the post.

The front matter of a recent post on this blog

We wanted this metadata to be part of the research nexus. But then there was also the question of archiving. Our membership terms state that:

The Member shall use best efforts to contract with a third-party archive or other content host (an “Archive”) (a list of which can be found here) for such Archive to preserve the Member’s Content and, in the event that the Member ceases to host the Member’s Content, to make such Content available for persistent linking.

So we knew that if this blog was to be part of the scholarly record, we would need to ensure that it would be available in perpetuity, even if www.crossref.org were to go offline one day.

Doing this properly was starting to look like a sizeable project!

Fortunately, we knew that others had already done some great work in this field, so we would not have to start from scratch. After considering our options, we opted to integrate our blog with an established workflow for registering blog metadata: the Rogue Scholar service.

The Rogue Scholar was launched in 2023 by Martin Fenner as an archive for scholarly blog posts, hosted by Front Matter. Rogue Scholar improves science blogs in important ways, including full-text search, long-term archiving, and DOIs and metadata, such as versions and relationships along with identifiers such as ORCID iDs and ROR IDs. It provides the necessary tools to treat blog posts as research outputs through better attribution, preservation, and discoverability.

How did we do it?

Rogue Scholar works on the basis of consuming RSS and ATOM feeds (you may remember them from the days of getting headlines direct to your browser or feed reader). We created a new feed, including the proposed DOI as each entry’s id: and taking full advantage of the ATOM format by listing the post’s authors and including their ORCID iDs. We also provide the entire post as the entry’s <content> to allow for full-text indexing and archiving.

The XML feed entry for a recent post on this blog

For each post, we generate and assign a unique DOI under the Crossref prefix 10.64000. The Rogue Scholar integration then registers the DOI along with the metadata of the post as posted content. If you are interested in getting a similar workflow set up for your blog, you can read more in the Rogue Scholar blog and documentation.

What does the future hold for scholarly blogs?

Researchers are increasingly sharing their early work, or commenting on others’ work, in less formal ways, and if you look at the growth in the number of blogs covered in the Rogue Scholar platform in just a couple of years, it seems like science blogging is here to stay and will only increase. We believe that this practice is an integral part of a healthy scholarly ecosystem, and it needs to be represented in the research nexus.

The Crossref input schema does not include a blog work type, but we are planning to add it as a subtype of posted content in our next schema update. We will discuss this and other plans and ideas in the metadata advisory group that we are currently forming.

If you have thoughts on the role of blogs in the public discourse around science and science communications, or you would like to share your experience of registering metadata for your blog, let us know by commenting below. Your comments will be threaded in our community forum for discussion.

Sprinting to Progress: Behind the scenes of our first metadata sprint

Luis Montilla — Mon, 23 Jun 2025 00:00:00 +0000

If you take a peek at our blog, you’ll notice that metadata and community are the most frequently used categories. This is not a coincidence – community is central to everything we do at Crossref. Our first-ever Metadata Sprint was a natural step in strengthening both. Cue fanfare!. And what better way of celebrating 25 years of Crossref?

We designed the Crossref Metadata Sprint as a relatively short event where people can form teams and tackle short problems. What kind of problems? While we expected many to involve coding, teams also explored documenting, translating, researching—anything that taps into our open, member-curated metadata. Our motivation behind this format was to create a space for networking, collaboration, and feedback, centered on co-creation using the scholarly metadata from our REST API, the Public Data File, and other sources.

What have we learned in planning

The journey towards the event was filled with valuable lessons and learnings from our community. Our initial call received submissions from 71 people, which was exciting but presented the first challenge: we felt our event would work better with a relatively smaller group. An additional challenge we faced was the enthusiasm from people from different regions of the world who were eager to join, but needed support to attend in person. It reminded us how global our community is, and how important it is to think about different ways of making participation possible, especially in future events.

We also wanted to make sure that participation wasn’t limited by technical background. The selection process included a preliminary review by several members of our team to bring in a mix of perspectives and reduce bias. The event welcomed participants from all kinds of expertise levels, including colleagues who had never worked with APIs before. We sought to provide common ground for all with several group calls, where we presented introductions to our tools and used the opportunity to collect requests about tools, specific data, and questions from the participants that could enhance their preparation during the sprint.

At the Crossref Metadata Sprint

I’ve recently stumbled upon the following quote from a recognized data scientist:

Numbers have an important story to tell. They rely on you to give them a clear and convincing voice. (Stephen Few) ¹

It made me think that we can replace numbers for metadata and the idea still holds. Surrounded by the paleontological collections of the National Museum of Natural History, on 8th of April in Madrid, 21 participants and 5 Crossref staff came together to work on twelve different projects. These ranged from improvements to our Public Data file formats and exploring metadata completeness, to tackling multilingual metadata challenges, understanding citation impact for retracted works, and connecting Retraction Watch metadata with other knowledge graphs metadata.

The different teams that participated in the first Crossref Metadata Sprint.
The initial hours were the most energetic (but not chaotic!) as most of the participants had the chance to interact in person for the first time, ideas were exchanged, and pre-formed groups became more stable (however, one of the advantages of the format is that teams don't have to be rigid). Twelve coffee- and tea-powered projects started taking shape, a few of which are part of larger ideas under development. By the end of the second day, we saw:

Author changes between preprints and published articles.
Coverage of funding information by publisher.
Enriching citations with Crossref metadata.
Funding metadata completeness.
Improvement to the Public Data File.
Interoperability between Crossref DOIs and hash-based identifiers.
University of Tetova’s metadata coverage.
Retraction Watch data mash-up.
Perspective about AI-driven multilingual metadata.
Public Data File in Google Big Query.
Visibility of retractions across citations.
Visualising Crossref geographic member data.

Our team worked as part of some of these projects, providing valuable insights and feedback to the participants. We ended the first session with a group dinner and re-energised for the second day, which started with everybody fully immersed in their tasks. As we approached the conclusion, the groups started preparing some quick slides for a short presentation (that you can find here).

Our team and the participants left excited and looking forward to the next opportunity to collaborate. We certainly see the potential of recreating these spaces, and we’ll work on future editions in a different location. All of the project summaries and notes will remain stored in our metadata sprint Gitlab repo. Would you like to know more about any of these ideas? Let us know in the comments.

The first Crossref Metadata Sprint in a nutshell

Participants

None of this would’ve been possible without our enthusiastic participants. Huge thanks to everyone! Here is the full list of those who attended our inaugural Sprint:

Name
Blessing Abumere
Ana Bermejo
Robert Bianchi
Adam Buttrick
María de la Paz
Nicoleta Roxana Dinu
Jack Ekinsmyth
Castedo Ellerman
Álvaro Hontanar
Bianca Kramer
Anne L’Hôte
Cyril Labbe
Alexandra Malaga
Agon Memeti
Kaitlin Newson
Yağmur Öztürk
Dietrich Rordorf
Mohamed Selim
Sajad Sepehri
Ramazan Turgut
Iñaki Úcar

https://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/ ↩︎

Meet six winners of the first ever Crossref Metadata Awards

Kornelia Korzec — Wed, 07 May 2025 00:00:00 +0000

Marking our 25th anniversary, we launch the Crossref Metadata Awards to emphasise our community’s role in stewarding and enriching the scholarly record.

We are pleased to recognise Noyam Publishers, GigaScience Press, eLife, American Society for Microbiology, and Universidad La Salle Arequipa Perú with the Crossref Metadata Excellence Awards, and Instituto Geologico y Minero de España wins the Crossref Metadata Enrichment Award. These inaugural awards highlight the leadership of members who show dedication to the best metadata practices.

Crossref exists to make scholarly communications better by making research objects easy to find, cite, link, assess, and reuse. Our members weave the research nexus: a rich and reusable open network of connections between works resulting from the scholarly process and the people and institutions engaged in it.

Rich metadata improves discoverability of and trust in published works. Many institutions now strive to turn towards open research information in their reporting, assessment and evaluation. And so we believe it’s time to give credit to members that are doing the best work in supporting others across the scholarly ecosystem with their metadata.

The awards presented today will be followed by a series of blog interviews, where the winners will share how they achieved their high level of metadata completeness.

Starting in 2025, we will hold the awards every other year.

Read on to get more acquainted with the winners, learn about other high performing organisations and overall trends in metadata practices we see at Crossref.

Recognising Metadata Excellence

Noyam Publishers is based in Ghana. Colleagues had the pleasure of meeting them in person, during the Crossref Accra event this March. Striving for visibility motivates Noyam’s high performance when it comes to metadata. With 57% coverage of key metadata elements across their records, they are a leader among the members in our Global Equitable Membership (GEM) program.

Among other GEM members who show high participation in the research nexus, we see more than 40% coverage of key metadata elements for the records registered by University of Sierra Leone Teaching Hospitals Complex in Sierra Leone, Queen Arwa University in Yemen, Kathmandu University School of Education in Nepal, and International Journal for Innovation Education and Research in Bangladesh.

GigaScience Press, based in Hong Kong, is the leader among small members (organisations of less than USD 1 mln of publishing revenue or expenses). Discoverability drives their high metadata standards, and GigaSciencePress sees those having advantages in terms of service integrations and development too. They are quick to credit the expertise of their technology partner, River Valley Technologies as the strategic contributor to them achieving 82% coverage of key metadata elements across their records.

It’s worth highlighting that the competition among our small members was much closer than in any other category! Stichting SciPost (Netherlands) also show more than 80% coverage across their records, followed by Life Science Alliance, LLC (United States), National Institute for Health and Care Research (United Kingdom), and Universidad La Salle Arequipa (Peru), each of which achieved more than 70% metadata coverage across their registered works.

eLife leads among our medium members (organisations between USD 1 mln and 10 mln of publishing revenue or expenses) with 85% coverage of key metadata elements. They have shown dedication to metadata quality and consistently high performance over the years. They are also the first publisher to include Crossref grant IDs in their records, adopting the Grant Linking System.

Other medium-sized organisations to note are MDPI AG in Switzerland, and XMLink in South Korea – while there’s a significant gap to the leader, each of these organisations has more than 50% coverage of key metadata elements across their records.

It appears that large members (organisations with more than USD 10 mln of publishing revenue or expenses) struggle to achieve consistency in metadata quality across all of their records. Yet, we are delighted to recognise the American Society for Microbiology in the United States, who have embarked on a large metadata quality improvement project several years ago, and it continues to bear fruit as we see 56% of metadata coverage across ASM’s records. They’ve shared their experience on our blog already, so this time we’ll invite them to follow up with the latest updates on their metadata practices.

American Geophysical Union (AGU), Public Library of Science (PLOS), SAGE Publications, and Wiley, all based in the United States, are ASM’s closest runners up. While the gap is significant – still each of these organisations has more than 40% of metadata coverage across their records. PLOS has an impressive proportion of Crossmark-enabled works (99%), and American Geophysical Union and Wiley are registering a significant proportion of abstracts for their records (87% and 59% respectively).

It often takes time to hone new processes and learn about metadata practices, so we decided to recognise metadata excellence among our new members: organisations that joined Crossref within the past two years. Our inaugural award for excellence among new members goes to Universidad La Salle Arequipa Perú, who joined Crossref in May 2023, and have 71% metadata coverage across their records.

Rewarding Metadata Enrichment

Our members don’t just register their records with us – they also steward and maintain their metadata over time. As new technical capabilities and metadata elements become available, members have the ability to update their metadata. We decided to recognise the member who achieved the biggest transformation to their records in the past two years: Instituto Geologico y Minero de España, based in Spain, jumped from just over 1% to more than 40% metadata coverage for their records in the space of the past two years.

Others who made more than 30% jump in their metadata completeness in the past two years are Cabrera Research Lab (United States), Centro de Investigaciones Sociologicas (Spain), Bon View Publishing PTE (Singapore), Asociacion Colombiana de Neurologia (Colombia), Instituto Superior Tecnológico Almirante Illingworth (Ecuador), and Tashkent State University of Economics (Uzbekistan).

How did we select the winners?

Our Metadata Excellence Awardees have been selected on the basis of the overall highest coverage of metadata elements included in Participation Reports as of March 2025, and the Metadata Enrichment Award was based on the comparison between performance on the same criteria between March 2023 and March 2025. Participation Reports are openly available and provide information about the proportion of a given member’s records that include the following high-value metadata elements:

References
Abstracts
ORCID iDs
Affiliations
ROR IDs
Funder Registry IDs
Funding award numbers
Crossmark enabled
Text mining URLs
License URLs

The report also includes Similarity Check URLs. However, since Similarity Check is an optional service that attracts a separate fee – it wouldn’t be equitable to include it in our analysis.

We encourage all members to periodically monitor their participation reports, and we offer frequent drop-in metadata health-check sessions, where we review the reports together and offer advice on making improvements in areas where our members experience challenges.

In a membership of more than 22,000 organisations, it’s difficult to recognise just one organisation as a model of best practices. There are many nuances that influence the performance and we would like to be transparent about some considerations we made in our awarding process.

First of all, we considered volume of publishing as a key variable, and decided to qualify organisations with a minimum of 20 items of registered content.

We also recognise that size matters – and decided to award our Metadata Excellence Awards in four categories corresponding with organisational size and resourcing.

Beyond the winners – overview of good metadata practice across different types of works

The scholarly communications landscape is always evolving, and new types of content arise all the time. Crossref schema enables rich metadata collection about journal articles, books, book chapters, preprints, conference proceedings, technical reports, as well as grants, and more.

At this point, the most prolific way of sharing scholarship - at least judging by the number of records registered with Crossref – is a journal article. There are 112,982,290 journal articles in the Crossref database, and in 2024 alone our members created 6,747,031 journal articles records with us.

When it comes to books (2,212,221 total records) and book chapters (22,892,785 total records), publishers with the richest metadata records include Universitatsbibliothek Kiel (Germany) with more than 50% coverage of key metadata elements across their book records, and 70% for their book chapters. RTI Press (US) also has strong metadata for books (52%), while Firenze University Press (Italy) has 56% of metadata coverage across their book chapters. Incidentally, Universitatsbibliothek Kiel (Germany) are also leaders in metadata for conference proceedings (53% metadata coverage of those records).

Preprints and posted content (including preprints, eprints, working papers, reports) are relatively new on the scene and growing rapidly – Crossref has 1,683,351 preprint records (413,742 registered in 2024). The richest metadata records for preprints belong to eLife (UK) - they cover more than 50% of key metadata elements across their preprints records in Crossref. Springer Science and Business Media LLC (Netherlands) have 48% metadata coverage for their preprints, American Chemical Society (ACS; United States) with 46%, and UNISA Press (South Africa) and PeerJ (US) follow with 44% coverage.

The newest of record types that can be registered with us are grants. At present this is an early adopters domain, with 152,810 registered grants so far. The European Union (represented in Crossref by the Publications Office of the European Union) registered the most grants to date.

Beyond the winners – overview of coverage in key metadata elements

When speaking about key metadata elements reflected in our Participation Report, the coverage varies widely. For example, overall 21% of records in Crossref have abstract metadata; 2,000 members have a full coverage of their records with abstracts, while 1,000 don’t include any. Deposition of ORCID iDs is growing but still very low, with only 10% of records including ORCID iDs.

Affiliation metadata, broadly sought after by many stakeholders in the scholarly ecosystem - not least because of its role as a key marker of trust - is growing steadily but slowly: only 16% of records included it at the end of March 2025. With recent improvements in our helper tools (especially the latest version of the record registration form), and the upcoming developments in other publishing software (notably the upcoming 3.5 version of OJS), which support affiliation metadata better – we’re expecting a significant improvement in the coming months.

As with affiliations, when research integrity judgements are concerned, another key element is the funding information. The growing interest in metadata among funders further strengthens the case for increasing inclusion of funder information in this way, ideally including Crossref grant DOIs that funders are registering in the hope of using the Grant Linking System to help their assessment and evaluation work. At the moment the space for improvement is vast, with only 6% of Crossref metadata including funder IDs and award numbers.

We support ROR IDs in both affiliation and funding metadata, but adoption among our members is slow. So far the top five contributors of ROR IDs to Crossref are Fonds de recherche du Québec, eLife, American Physical Society (APS), Optica Publishing Group, and Wellcome.

Licence metadata is currently included for 43% of records in Crossref, and we see that thousands of members don’t include it. Not all members realise that this is a practical challenge for their authors, as it hinders institutions and funders who seek to monitor compliance with their openness mandates.

Finally, references metadata is the lifeblood of the research nexus, supporting transparency and discoverability of scholarship. We’ve got 44% coverage of reference metadata across records registered in Crossref. While reference linking is a member obligation, including references in the metadata is a recommended best practice. The way references are recognised and included in works varies by publication type and discipline, which makes it harder for some members to provide it.

There’s an ongoing need to raise awareness about the role of metadata among the wider community, including editors and researchers. We have collaborated with practitioners, supporters, and users of metadata to develop relevant resources as part of the Metadata 20/20 initiative.

We make efforts to educate our members about best practices when it comes to registering their metadata with us and offer a range of support options, including technical support on our Community Forum. Recognising the leaders in metadata participation is part of that process too. With the upcoming blog series from our awardees, we hope to spur peer-to-peer learning to facilitate widespread improvements and to raise the profile of metadata quality among the community.

Metadata Advisory Group call for applications

Patricia Feeney — Fri, 02 May 2025 00:00:00 +0000

We’ve been accelerating our metadata development efforts and recently released version 5.4 of our metadata schema, and are planning to release version 5.5 (including support for multiple contributor roles and the CRediT taxonomy) this summer. We will also extend our grants schema based on the Funders Advisory Group work, and make progress on other changes as set out on our new metadata development roadmap.

As we work towards the vision of the rich and reusable open network of relationships connecting research organisations, people, things, and actions, dubbed the Research Nexus, our schemas need to change to accommodate the evolving landscape of research processes and communications.

In the past we convened the Metadata Interest Group that helped shape the current set of updates we’re now working through, including changes to names, expansion of support for abstracts, dates, and multilingual metadata. As we’ll soon move into new territory (support for subjects, keywords, and other metadata essential to developing a robust research nexus), we want to further enlist the support of our community to help shape the metadata we collect and the metadata best practices we promote.

We are inviting Crossref members, metadata users, and others with an interest in shaping metadata development at Crossref to apply to join our new Metadata Advisory Group.

The purpose of the group is to contribute your advice and insight to help shape our metadata development as we broaden the metadata we collect and outputs we support to better align with the Research Nexus. Group participants will help shape metadata development at Crossref, and will discuss potential new metadata to adopt, best practices, and the overall needs of metadata providers and users.

We’re looking for participants with experience with XML, JSON, and other metadata formats. We’ll cover a range of topics but we would particularly like to engage with those of you with an interest in emerging content types.

The Metadata Advisory Group will meet quarterly and we’ll accommodate multiple time zones as needed as we want participation to reflect the regional diversity of our membership.

If you’re interested, please submit an application!

Request for proposals: Crossref website information architecture review

Lena Stoll — Thu, 17 Apr 2025 00:00:00 +0000

We are looking for an organisation to perform an audit of, and propose changes to, the structure and information architecture underlying our website, with the aim of making it easier for everyone in our community to navigate the website and find the information they need.

UPDATE, August 2025: We are partnering with Cazinc and Cactus AI Solutions on this work. Stay tuned for updates on the progress of this project over the coming months.

About Crossref

Crossref is a nonprofit membership organisation that exists to make scholarly communications better. We run open infrastructure to link research objects, entities, and actions, creating a lasting and reusable scholarly record that underpins open science and makes research outputs easy to find, cite, link, assess, and reuse.

Together with our 22,000 members in 160 countries, we drive metadata exchange and support nearly 2 billion monthly API queries, facilitating global research communication, for the benefit of society. Our members include research institutions, publishers, libraries, funders, government bodies, and other stakeholders in the scholarly communications ecosystem.

About the Crossref website

We launched the current website in 2016. A few years later, we custom-developed the current Documentation section, moving from a separate site (Zendesk, and prior to that HelpIQ). We subsequently launched a Discourse community forum and actively encourage self-service there. Despite these efforts, we still answered about 50,000 support emails in 2024.

We use the Hugo static site generator, and all the content, assets, and code are open in GitLab. We have dedicated staging and sandbox branches, and use staging for editing instead of the usual git merge requests, and sandbox for testing more substantial code or navigation changes.

We share the responsibility for editing across the teams, with a page owner/author denoted for each page. Most staff use VSCode for editing; we don’t have or need a CMS. We deploy changes to the live site around twice a week. Several custom shortcodes are in place, such as for tables and displaying related information based on tags, or for presentation elements like highlight boxes or columns. We host (many) images and files directly in the repository, rather than using a CDN. We use Algolia for site search, which was chosen because it can support multiple languages.

Current website structure

There are currently four main sections of the website:

Get involved: this landing page is the most up-to-date with our current positioning and messaging. The section includes how to join as a member and the ways you can participate, obligations and benefits; a welcome page for new members to get started; events and webinars like our annual meeting; special projects or campaigns that need landing pages; fees; programs such as for service providers and ambassadors; global equitable membership; code of conduct; and working groups (which are different from board committees).
Find a service: listing the purpose and value/benefits for each service, such as content registration, metadata retrieval/APIs/Search, Crossmark, Similarity Check, Grant Linking System, and some other quasi-services that require members to develop or enable something, like reference linking or the Open Funder Registry or ROR.
Documentation: following more-or-less our “managed member journey” pathway, this includes getting set up, how to create DOI suffixes, how to select the right tool for content registration, how to interpret the various reports that members receive, what to expect in terms of invoicing, schema library and best practices for metadata sharing incl. guidance on principles to follow and sample XML files to edit. Each ‘service’ then has it’s own documentation section too.
About: governance, including information about our board, committees, and bylaws. Financial information and annual reports. Staff pages, org chart, jobs, and policies incl. employee handbooks. History of Crossref and mission. Under the sub-heading “Operations & sustainability”, there is also detailed information about membership processes such as revocations, managing legal sanctions, member practices, and member offboarding.

Additionally, the website hosts our blog and allows users to sign up for our newsletter, which are two key ways in which we keep our community informed.

Project overview

End goal

We want to allow our community to self-serve with information about what Crossref does, how to become a member, how to use our tools, and how to participate in our programs and services. The Principles of Open Scholarly Infrastructure are central to how we operate, and we want the information about the how, what, and why of Crossref to not only be openly available, but also easy to discover and reuse.

Visitors to www.crossref.org should be offered the information that they are looking for quickly and intuitively. A reduction in the number of help-desk tickets we receive (in 2024 we answered 50,000 of them) would be an indication of an improved self-service website, as would lower bounce rates.

Scope and deliverables

At the end of this information architecture review project, we expect to have agreed on a set of recommendations for tackling the problem statements laid out in the appendix of this document, as well as a plan for how the recommendations should be implemented. This plan will form the basis for an implementation project in 2026. We encourage applications both from organisations who would also be comfortable taking on the implementation project and from those who feel their expertise is specific to the review project described herein.

Specifically, we expect the following deliverables:

Assessment of key user needs (through analytics and/or user interviews incl. editors)
Audit and analysis of current site structure and how it serves key user pathways
Recommendations for content re-architecture, navigation and search improvements
Strategy for taxonomy and/or tagging system
Strategy for documentation site setup
Strategy for information pathways between website, docs, community forum, ticketing systems
Recommended roadmap for 2026 implementation project
Nice to have: Wireframes or annotated sitemaps for future site layout

Problem statements

It is difficult to find information about our services. Even Crossref staff often use search engines to find a page on our website rather than navigating to it or using the built-in search on the website. It’s often not clear whether the information you are looking for is on the “Find a service” page or the “Documentation” page for a given service, and there is no consistent cross-linking between the two groups of pages. There is a search bar prominently placed on the home page, but the search currently only looks for direct matches between the search terms and page contents (with some declensions, stopwords, and fuzziness to allow for typos). We have limited tracking available in Algolia, but can see that in a 7-day span in March 2025, a large portion of searches (78%) returned no results.
It is difficult to navigate our website. The home page contains some quick links to key pages, but they are not very visible. In order to navigate the website from the home page, users have to expand a hamburger menu which takes up the whole page, and are then presented with an overwhelming amount of options. Once users have left the home page, the way they navigate depends on which section of the website a user finds themselves in: all pages have breadcrumbs going back to Home, while only Documentation pages have a hierarchical sidebar. In order to switch between the basic groups of pages (Get involved, Find a service, Documentation, About us), users have to use the global hamburger menu.
Our home page doesn’t do a very good job of explaining who we are and what we do. A lot of real estate is taken up by images and recent news items without much context. Bounce rates from the home page are high (65% as of March 2025).
Our user interfaces and reports are not easily accessible from our website. While we are not a SaaS organisation, there is an established pattern of being able to access an organisation’s services directly from its website (often via a login button at the top right). This is complicated by the fact that we don’t have one single frontend “platform”. In fact we don’t have a single page linking out to the various frontends and interfaces, nor do we have a consistent pattern of linking out to an interface from the documentation page describing how to use it.
Some of the pages and grouping of pages are outdated and don’t reflect our current priorities or ways of working anymore. For example, the Get involved section still features Special programs and Service providers quite prominently, but the cross-functional programs that shape most of our strategic work now (Co-creation and Community Trends, Contributing to the Research Nexus, Open and Sustainable Operations, Metadata Development) are not represented. Find a service strongly suggests we’re a service provider, whereas most of our services are enabling infrastructure, requiring members to build or act on something. Some more recently created pages don’t fit neatly into any of the current groupings: e.g., API Learning Hub can be found under Get involved and in the home page footer, but doesn’t really belong in either. We also have time-limited, special projects or campaigns like the 25th anniversary of Crossref or the Resourcing Crossref for Future Sustainability project, for which there isn’t a great home. Lastly, we want to host additional content on our website in future, such as our own staff publications; instructions on how to find our codebases and how to contribute to them; how to build technical integrations; how to report bugs; and general best practices in scholarly communications (e.g. in the context of our work on the integrity of the scholarly record), which is not really part of the documentation of our services.

Project budget and timeline

We have a maximum budget of $20,000 allocated to the information architecture review project. The projected timeline is as follows:

RFP issued: April 17, 2025
Final deadline for proposals: May 15, 2025
Shortlisted applicant interviews: May 2025
Appointment made: June 2025
Project kick-off: July 2025
Final deliverables due: October 2025

If you are interested in applying but don’t think this timeline is deliverable for you, please contact us to suggest what would be realistic for you or your organisation before applying.

Proposal submission requirements

Proposals, as well as any questions, should be submitted to Lena Stoll by 15 May 2025.

Please include the following in your proposal:

Company background and relevant experience with open-source static sites and mission-driven communications
Case studies or examples of comparable work
Your approach to the proposed project and how you would structure it
Team bios and roles incl. typical timezones
Timeline and milestone estimates
Proposed budget, including breakdown
Proposed cadence of check-ins, communications, milestones, and deliverables
Contact information

Proposal evaluation criteria

We will evaluate proposals based on:

Demonstrated understanding of our mission and community needs
Proven experience designing for multilingual and multinational audiences
Expertise in mission-driven business-to-business communications and information architecture
Quality of previous work and case studies
Value for money

We look forward to hearing from you!

Version 5.4.0 metadata schema update now available

Patricia Feeney — Wed, 19 Mar 2025 00:00:00 +0000

This year, metadata development is one of our key priorities and we’re making a start with the release of version 5.4.0 of our input schema with some long-awaited changes. This is the first in what will be a series of metadata schema updates.

What is in this update?

Publication typing for citations

This is fairly simple; we’ve added a ‘type’ attribute to the citations members supply. This means you can identify a journal article citation as a journal article, but more importantly, you can identify a dataset, software, blog post, or other citation that may not have an identifier assigned to it. This makes it easier for the many thousands of metadata users to connect these citations to identifiers. We know many publishers, particularly journal publishers, do collect this information already and will consider making this change to deposit citation types with their records.

Support for version numbering

Members can now supply a version number across all relevant record types, including journal articles, book chapters, conference papers, posted content/preprints, datasets, reports, standards, and dissertations. The versioning update also includes an optional description field.

Members who version content are encouraged to register a new DOI with each version and supply the isVersionOf’ relationship to connect versions to each other, facilitating the Research Nexus and allowing members to avoid additional content registration fees, which don’t apply for versions.

Preprint status

This is specific to the ‘posted content’ record type and comes as a result of the recommendations of the Preprints Advisory Group. The new status field allows repositories to flag a preprint as ‘withdrawn’ or ‘removed,’ a situation specific to posted content.

There are some other minor updates as well, including:

An expansion of the language codes supported by a language attribute.
Additions to the archive locations we collect. Our membership terms ask members to archive their content where possible, ensuring their DOIs are able to resolve to the content persistently, and we ask that the archive(s) they use are identified in the metadata records registered with us.
We’ve increased the number of ISBNs supported per item from 6 to 100.

If you would like to begin using this schema, a brief transition guide is here. A full set of schema files are in our GitLab repository, and more information is available in our website documentation for schema 5.4.0.

What’s next?

We’ve already begun working on our next update, which will be an expansion of contributor roles. We’ll allow multiple contributor roles instead of the single role we currently support, we’ll add ‘corresponding author’ and ‘other’ to the Crossref role vocabulary. We will be also adding full support for CRediT.

We’re also hoping to fit in a remodeling of our group contributor (currently labeled ‘organisation’ in our input schema) in the next update, and I would appreciate feedback on this planned update.

More changes are planned, including an update to our grants schema, and expanded support for abstracts. We’ll be circulating details about those updates soon.

Join us for the Mid-year Community Call on 7th May to hear more!

2025 public data file now available

Martyn Rittman — Wed, 12 Mar 2025 00:00:00 +0000

Every year we release metadata for the full corpus of records registered with us, which can be downloaded for free in a single compressed file. This is one way in which we fulfil our mission to make metadata freely and widely available. By including the metadata of over 165 million research outputs from over 22,000 members worldwide and making them available in a standard format, we streamline access to metadata about scholarly objects such as journal articles, books, conference papers, preprints, research grants, standards, datasets, reports, blogs, and more.

Our metadata is used by thousands of services, researchers, and other organisations. We make it openly available through our APIs, which can be used to obtain a subset of records. If you want to work with our full corpus, the best way is to get a copy of the public data file and update it via the REST API with any new records created or changed since its release.

By providing an annual copy of the full corpus, we also expand the ways in which the metadata can be used and interrogated. It is ideal for groups using large samples of the scholarly record, such as metaresearchers or research integrity experts. You can find examples of the public data file used in research on journal editorial practices and in projects investigating gaps in the scholarly record.

How to access the public data file

The total size of the file is 197 GB and it is available in JSON-lines format. We also provide an experimental tool to convert the file to an Sqlite database. Before downloading the full dataset, you may wish to download the sample dataset containing 100 files (with 100 records in each, around 24 MB). This is a randomly sampled subset of metadata records and can be used for prototyping and development.

To get a copy of the annual data file you can access it directly via https://doi.org/10.13003/87bfgcee6g, or get the sample dataset and previous public data files from Academic Torrents. We make a donation to Academic Torrents to support their work, which allows the data to be accessible in this way. Some organisations have reported policies that prevent access to torrents, so we provide a copy that can be downloaded from AWS, which requires an AWS account and a small payment to cover the data transfer costs. You can find the details about access here.

We have some tips for working with the public data file. If you would like to have access to monthly snapshots of the whole corpus, along with higher API rate limits and other benefits, you can subscribe to Metadata Plus.

What’s different this year?

This year’s public data file contains an additional 9 million records, and many updates to previously deposited records. The formats and method of access are the same as last year, except that it uses JSON lines, meaning that each metadata record is on a single line and the file suffix is jsonl instead of json. The records have been sorted by DOI, meaning it should be easier to navigate.

A change this year is that the file does not contain aliased DOIs, which are DOI that are redirected to another DOI. Aliasing is necessary on rare occasions, for example when two DOIs are registered for the same content. Previously we haven’t indicated aliasing in the REST API and public data files; this year only the prime DOIs (the ones to which they are redirected) are included. This makes statistical analysis of the metadata more accurate, but beware that it may give different results in cases where many aliased DOIs were previously counted. See this community forum post for more details.

The file also contains retractions from the Retraction Watch database, which was acquired by Crossref in September 2023 and recently integrated into the REST API.

If you have questions, want to let us know how you will use the metadata, or want to discuss anything on the topic of retrieving Crossref metadata, head to our community forum. From there, you can also keep updated about changes to our schema and APIs.

Come ROR with us: Using ROR IDs in place of Funder IDs

Patricia Feeney — Wed, 05 Mar 2025 00:00:00 +0000

Today, we’re delighted to let you know that Crossref members can now use ROR IDs to identify funders in any place where you currently use Funder IDs in your metadata. Funder IDs remain available, but this change allows publishers, service providers, and funders to streamline workflows and introduce efficiencies by using a single open identifier for both researcher affiliations and funding organisations.

As you probably know, the Research Organization Registry (ROR) is a global, community-led, carefully curated registry of open persistent identifiers for research organisations, including funding organisations. It’s a joint initiative led by the California Digital Library, Datacite and Crossref launched in 2019 that fulfills the long-standing need for an open organisation identifier.

In 2023, we shared our plan to transition the Open Funder Registry into ROR. More recently, we announced that we were planning to update our schema so that it is possible to collect ROR IDs where we currently collect Funder IDs such as in the funding metadata section for works and funder section for grants. Now that we have completed this work, Crossref members can start depositing ROR IDs where they would normally deposit Funder IDs. This update also means that the community, including funders, service providers, researchers, and data scientists can retrieve this metadata via our API.

So come and ROR with us and start depositing ROR IDs for both researcher affiliations and funding organisations.

Open Funder Registry-ROR transition

This is of course a significant first step in the Open Funder Registry to ROR transition.

We’ve always said that we would continue supporting Funder IDs in our schema and in our tools and services until the community is ready to transition - and we will. In the last year, Crossref and ROR conducted a series of Open Funder Registry user interviews to help us understand how it was being used and identify practical challenges to this transition in our members’ workflow (thank you to those who took part, it was incredibly useful!).

One major takeaway from this consultation was around the pivotal role that peer review management systems played in the Open Funder Registry-ROR transition. We look forward to seeing more service providers integrating with ROR in the future. If you are a service provider and are ready to integrate with ROR, drop support@ror.org an email.

Including ROR IDs in Crossref metadata

If you are ready to begin including ROR IDs in your funding metadata, you only need to include the ROR itself to identify a funder.

For example:

<fr:program name="fundref">
 <fr:assertion name="ror">https://ror.org/00fq5cm18</fr:assertion>
 <fr:assertion name="award_number">10.3030/725840</fr:assertion>
</fr:program>

Examples of more complex combinations of funding information are available in our documentation. This update has been made across all schema that support funding metadata.

Our grants schema has recently been updated to version 0.2.0 to support ROR IDs in place of funder identifiers as well. As with funding metadata, only the ROR ID needs to be supplied within the record:

<funding amount="750" currency="USD" funding-percentage="75" funding-type="APC">
 <ROR>https://ror.org/02twcfp32https://ror.org/02twcfp32</ROR>
 <funding-scheme>Sofa Lending Programme</funding-scheme>
</funding>

Although previously a funder name was collected with the funder identifier, for both grants records and funding data in an attempt to avoid redundant, incorrect or conflicting metadata, now we’re accepting an identifier only as the ROR ID has an existing metadata record. The organisation name exists within the record in the ROR registry and the ROR record is the authoritative source of the name.

ROR IDs in JSON outputs

We have an existing legacy practice of representing Open Funder Registry IDs as just a DOI, but ROR IDs are represented in the JSON outputs as a full URL with id-type “ROR”, for example:

Funding metadata


 "funder": [
 {
 "award": [
 "10.3030/725840"
 ],
 "id": [
 {
 "id": "https://ror.org/02twcfp32",
 "id-type": "ROR",
 "asserted-by": "publisher"
 }
 ]
 }
 ],

Grant funder information


"funding": [
 {
 "type": "infrastructure",
 "award-amount": {
 "amount": 750.0,
 "currency": "USD",
 "percentage": 75
 },
 "funder": {
 "id": [
 {
 "id": "https://ror.org/02twcfp32",
 "id-type": "ROR",
 "asserted-by": "publisher"
 }
 ]
 }
 }
 ]
 }
 ],

If you have any questions or feedback, get in touch with us support@crossref.org !

Looking ahead: the Research Nexus and the state of metadata in 2050

Ed Pentz — Tue, 04 Mar 2025 00:00:00 +0000

Looking Ahead: The Research Nexus and the State of Metadata in 2050

Published in Science Editor (Vol. 48, No. 1, March 2025), this feature article uses 25 years of scholarly metadata history as a lens to look forward. The authors trace the journey from Crossref’s first DOIs in 2000 — when records carried little more than journal title, author, volume, issue, and page number — to today’s Research Nexus of 30+ output types and rich relationships between works, people, organisations, and funders. They then sketch what scholarly metadata might look like in 2050.

Strategists

Understand where scholarly metadata is heading. A long-view perspective on how the Research Nexus reshapes what gets counted, assessed, and valued in scholarship over the next 25 years.

Decision-makers

Plan for richer assessment beyond publication counts. The authors anticipate research evaluation shifting toward practices, broader impact, and the wider set of activities around research — not just papers.

Practitioners

Prepare for new output types and tighter relationships. Computational notebooks, AI-assisted research, and immersive scholarly outputs will need persistent identifiers and structured relationships if they are to participate in the record.

What this article covers

Looking back to look forward — how Crossref metadata grew from a handful of bibliographic fields in 2000 to over 30 research output types and rich relationship data today
The Research Nexus concept — the “complex, evolving network of objects, along with descriptions of how they relate”, and why this framing now underpins scholarly infrastructure
PIDs as the backbone — how DOIs, ORCID iDs, ROR IDs, and other persistent identifiers make the Research Nexus tractable at scale
Research Nexus in 2050 — emerging output types (computational notebooks, virtual and augmented reality experiences, AI-assisted research) and what they require from metadata infrastructure
Beyond publication counts — a future where assessment recognises research practices, broader impact, and activities alongside research, not just published papers
Challenges ahead — cultural resistance to open-data defaults, the financial sustainability of open infrastructure, and the importance of globally inclusive systems that resist regionalisation and fragmentation

Read the article

Read on Science Editor

Metadata matching: beyond correctness

Dominika Tkaczyk — Wed, 08 Jan 2025 00:00:00 +0000

In our previous entry, we explained that thorough evaluation is key to understanding a matching strategy’s performance. While evaluation is what allows us to assess the correctness of matching, choosing the best matching strategy is, unfortunately, not as simple as selecting the one that yields the best matches. Instead, these decisions usually depend on weighing multiple factors based on your particular circumstances. This is true not only for metadata matching, but for many technical choices that require navigating trade-offs. In this blog post, the last one in the metadata matching series, we outline a subjective set of criteria we would recommend you consider when making decisions about matching.

Openness

Matching tools come in many different shapes and sizes: web applications, APIs, command-line tools, sometimes even enchanted crystal balls showing matched identifiers emerging from a mysterious mist! No matter what form they take, an important consideration is whether the source code and all the related resources for the matching are openly available.

Matching strategies that are either closed-source, or rely on closed-source services for their matching logic, make it difficult to fully understand and explain matching processes. This lack of transparency also makes it impossible to adjust or improve the matching logic, since we cannot understand or improve code we cannot see.

Users are similarly impeded from identifying flaws or suggesting improvements to processes they are unable to examine. By blocking this community participation, we also lose the proven cycle of real-world testing, refinement, and validation that has strengthened myriad of open source projects. The cumulative impact of both minor and major community-driven refinements over time is incredibly valuable and should not be underestimated.

Using open source matching will also help build trust in the matching workflows and results. This is one reason why open source is one of the tenets of the Principles of Open Scholarly Infrastructure, adopted by Crossref, DataCite, ROR, and other organisations who build and maintain open scholarly infrastructure.

When evaluating matching strategies, we strongly recommend prioritizing those that are fully open source. This not only ensures their transparency and trustworthiness, but also allows for the kind of continuous improvement that results from this visibility and community engagement.

Explainability

In terms of our ability to understand and improve a matching strategy, using an open source model is only the first step. What typically matters most in the context of building and maintaining matching services is that we are able to understand their underlying code and have a clear model of how matches are derived from their corresponding inputs. Even if the matching code itself and all of the resources used in the matching are open, if they are poorly documented, lack reproducibility or tests, or are otherwise opaque, there is no guarantee that it will be possible to understand or improve the strategy. Striving for a high level of interpretability in our matching plays a determinative role in how well we can understand and modify our strategies in the future.

Being able to explain the behaviour of the matching will also help you to respond to and incorporate user feedback. When users encounter errors, you will be able to do things like advise them on how to modify or clean their inputs so that the results are better. Conversely, examining the behaviour of the strategy relative to user inputs and feedback can provide you with ideas for improving the matching.

Typically, heuristic-based strategies, such as those that use forms of search or string similarity measures, like edit distance, are easier to explain than, say, machine learning models. If a strategy uses machine learning, at least some internal decisions might be made by passing data through a complex network of algebraic equations. Those can be mysterious, non-deterministic, and are famous for being hard to interpret. This doesn’t mean they should be avoided entirely - we have built and use many machine-learning based tools ourselves! Instead, it is a good idea to weigh how their inherent lack of explainability could affect your ability to continue work on the strategy and respond to user needs, relative to all the available options.

Complexity

Complexity is another aspect that can greatly affect how easy it is to maintain the strategy. Complexity is related to how many different components the strategy has and how difficult they are to use and maintain. When a strategy has multiple interconnected parts, each component becomes a potential failure point that requires discrete assessment and maintenance.

Consider, for example, two different approaches to a matching strategy: one that uses a single machine learning model versus another that uses an ensemble of models. A single model requires maintaining one set of training data, a single training pipeline, and one deployment process. If the model’s performance unexpectedly deteriorates, whether because of an issue with the training data, a configuration error, or the need for additional input sanitization, the source of the problem is easier to isolate and fix.

The ensemble, by contrast, combines multiple, specialized models, each requiring its own training data, tests, updates, and deployments. If one model in the ensemble is found to reduce the performance of the strategy, the interdependence between models can cause this degradation to cascade through the entire system and undermine its overall reliability. Correcting for these errors becomes more challenging. If fixing one model’s performance requires retraining or adjusting its outputs, this could require recalibrating the entire ensemble to maintain the balance between models, identify regressions, and prevent new errors from emerging.

In general, preferring simpler strategies not only reduces operational overhead, but also makes it easier to diagnose issues, test changes, and iterate on user feedback. When problems arise, having fewer moving parts means less places to look for the root cause and fewer components that could be affected by any fixes.

Flexibility

The metadata to which we match grows and changes over time. New records are created, existing ones are updated, with schemas changing and evolving alongside. The resources that underlie our matching are also not static. The libraries we depend on may deprecate features between versions or the taxonomies we used to categorize results might undergo significant revisions. We thus rarely have the luxury of deploying a matching strategy once and using it forever without any changes. A good strategy has to be flexible enough to adapt to such changes, with this adaptation also being both technically feasible and practical to implement.

Much of this flexibility is also determined by a matching strategy’s ability to incorporate new data. Strategies that use continuously updated databases or indices can immediately match against new metadata as it appears in the system. By contrast, some machine learning-based approaches require training on target matches and can thus be limited in flexibility and face more constraints. While some models can be incrementally updated to recognize new matches, others require retraining from scratch to incorporate these changes - a process that can be both time-consuming and resource-intensive.

Paying close attention to a strategy’s flexibility and favoring this aspect, when possible, can significantly impact its long-term viability. When comparing different matching strategies, flexibility should thus be a primary concern in your decision-making process.

Resources

Matching strategies can vary significantly in their resource requirements, including things like CPU and GPU utilization, memory consumption, storage capacity, and network bandwidth. These requirements are directly related to infrastructure costs and energy consumption, so when evaluating a matching strategy, it is necessary to assess its resource demands across all phases of the matching lifecycle. This includes things like initial model training, re-training, index construction, updates and management for all aspects of the strategy, as well as the real-world processing of matching requests. It is a good idea to measure and monitor resource usage carefully in considering which strategies to use, as the best performing strategy may also be too resource intensive to run as a service or might grow to this state over time with additional utilization.

Speed

Matching strategies can operate at a wide range of speeds, from milliseconds to minutes per match. Since the overall response time of a strategy can affect both system scalability and user experience, we should always assess the strategy’s performance for different usage scenarios and scales of data. While some strategies might perform adequately with small datasets, they can also exhibit exponential slowdowns as data volume and complexity increases or as concurrent requests grow in number. We should therefore consider carefully how requirements for matching speed might evolve with increased usage, data complexity, and total anticipated growth. The fastest matching strategy might not always be the best choice if it comes at the cost of reduced accuracy or requires large amounts of resources, but unacceptable latency can make an otherwise excellent strategy unusable in practice for many use cases.

Putting it all together

The typical life cycle of developing a metadata matching strategy is as follows:

Scoping: we define the matching task, along with its inputs and outputs.
Research: we research what existing strategies are available for our task and/or we develop our own.
Evaluation: we evaluate all available strategies, internally or externally-developed, exploring all of the aspects described above.
Decision: we choose which strategy (if any) we want to use in our production system.
Production setup: we prepare the production models, indexes, and other resources needed for the matching.
Maintenance: we monitor and adapt the strategy relative to changing data, user feedback, and new resource requirements.

In practice, these phases do not happen all at once, nor in this strict order. Often we need to proceed through multiple iterations of them to arrive at the best strategy. For example, if initial evaluation of a strategy yields poor results, we might return to the research phase to investigate other strategies or refine our understanding of the task. Often, during the maintenance phase, we receive feedback from users that indicates potential areas of improvement and then pursue them with a new round of research and evaluation.

As we cycle through these phases, ideally all the aspects described in this entry, along with the results of the evaluation, would be taken into account. Of course, this means that these decisions have to be based on multiple criteria and by making trade-offs between their performance and all other considerations. In making these complex and difficult choices, it is useful to consider two primary questions:

Are any of the considered matching strategies good enough for our use case?
Out of all the considered strategies that are sufficient for our use case, which would be the best?

The first question requires us to create clear and quantifiable criteria that allow for eliminating some of the potential strategies. As we have indicated, these could include things like the strategy being open source, minimum performance baselines using measures like precision or recall, and operational thresholds, like the strategy being able to return results quickly, relative to user expectations or the volume of data to be processed. It should be fairly easy to test these requirements and eliminate any strategies that fall short of them. If the strategies are difficult to assess, that is likely a mark against them.

If no strategies meet these criteria, we have two options: either to abandon matching entirely or to reassess and relax our criteria to align with the available options. While the former is always an option, adopting a more pragmatic lens, framing in terms of potential value (or harm) to the users, might be beneficial. Sometimes we approach matching tasks with too high expectations and a dose of realism helps us to re-center our perspectives. After more consideration, you might decide that your criteria were too stringent or realize that you need to better define and decompose the tasks to fit the available options.

When multiple strategies appear viable, the selection process becomes more nuanced. When evaluating strategies across these various dimensions, we should try to avoid placing undue weight on minor performance differences. Evaluation metrics are useful estimates of performance, but do not always translate to real-world applications and changing data. In cases where a more complex strategy offers only marginal improvements over a simpler alternative, the maintenance and operational benefits of the simpler solution often outweigh small performance gains.

This concludes our series on metadata matching, where we described the conceptual, product, and technical aspects of matching and its applications. We hope this overview was instructive and helps you to make better decisions about the use of matching in your own tools and services!

Metadata beyond discoverability

Ginny Hendricks — Tue, 03 Dec 2024 00:00:00 +0000

Metadata is one of the most important tools needed to communicate with each other about science and scholarship. It tells the story of research that travels throughout systems and subjects and even to future generations. We have metadata for organising and describing content, metadata for provenance and ownership information, and metadata is increasingly used as signals of trust.

Following our panel discussion on the same subject at the ALPSP University Press Redux conference in May 2024, in this post we explore the idea that metadata, once considered important mostly for discoverability, is now a vital element used for evidence and the integrity of the scholarly record. We share our experiences and views on the metadata significance and workflows from the perspective of academic and university presses – thus we primarily concentrate on the context of books and journal articles.

The communication of knowledge is facilitated by tiny elements of metadata flitting around between thousands of systems telling minuscule parts of the story about a research work. And it isn’t just titles and authors and abstracts – what we think of as metadata has really evolved as more nuance is needed in the assessment and absorption of information. Who paid for this research and how much, how exactly did everyone contribute, what data was produced and is it available for me to reuse it, as well as, increasingly, things like post-publication comments, assertions from “readers like me”, who has reproduced this research or refuted these conclusions.

Different types of published works are described by different types of metadata – journal articles, book chapters, preprints, dissertations. And those metadata elements can be of varying importance for different users. In this article, we will talk about metadata from the perspectives of four personas highlighted by the Metadata 20/20:

Metadata Creators, who provide descriptive information (metadata) about research and scholarly outputs.
Metadata Curators, who classify, normalise and standardise this descriptive information to increase its value as a resource.
Metadata Custodians, who store and maintain this descriptive information and make it available for consumers.
Metadata Consumers, who knowingly or unknowingly use the descriptive information to find, discover, connect, and cite research and scholarly outputs.

Our approach delineates the metadata lifecycle, from authorship, through production, discovery and through continuous curation. Though some of the metadata is generated outside of that linear process, and much happens before the authorship step, we see it as a clear and useful breakdown of how metadata contributes to a new piece of content.

Authorship

The first stage in the metadata lifecycle, authorship, is just the beginning of a dynamic process with many collaborators. A formative piece of the puzzle, authorship involves the authors or contributors, the editorial team and/or the marketing team and this is when the shape of the project and its metadata takes form. During this stage, the book or journal’s metadata exists only between the originators and the publisher, allowing the most opportunity for creativity and enhancement. Once the metadata reaches the next checkpoint along the lifecycle and is sent out externally, it’s more difficult and riskier to make major changes to the key metadata elements. In scholarly monograph publishing especially, we have the advantage of longer production lead times during which to amend and manipulate metadata during this stage.

At this stage, authors may have ideas of titles, subtitles and descriptions and it is up to the editors and other team members at the publisher to think strategically about how this can be optimised. The marketing and sales teams may be thinking about how the abstracts, keywords, and classifications can be best optimised for the web, leading to increased sales. Discoverability and interoperability of metadata for a book or journal, especially the use of persistent identifiers, is beneficial both for the author – in that their book is easily discovered, used, and cited – and for the publisher – increased visibility, sales, and usage.

Current challenges at the authorship stage include changing goalposts for metadata standards and accessibility requirements, which also have knock-on effects in subsequent stages in the metadata lifecycle. One of the key challenges with these is that they require buy-in from multiple players to keep up with and amend, and publishers must think closely about how these changes may affect metadata workflows for books at different stages of publication.

Production

As a book or journal article comes into production, it’s time to update and release the metadata to retailers, libraries, data aggregators and distributors. The metadata should be updated and checked to make sure that it’s still a good reflection of the product or the content that it describes and complete enough to release, including a final cover image in the case of books. This is still very much a collaborative effort with multiple roles involved. Technical details, such as spine width, page extents, and weight, are added, capturing the final specification. The editorial team may update metadata entered into systems earlier in the process. For example reviewing the prices, updating subject classification codes or amending the chapter order. If any of the content is to be published open access, appropriate licensing and access metadata need to be included, so that users of the content are clear about what they can (and can’t!) do with it. Metadata that’s not yet captured upstream can be added or enhanced. For example, vendors already involved in the production process can verify that persistent identifiers (PIDs) are present and correct in funding metadata.

More and more metadata elements are being requested by supply chain partners. For example, new requirements being introduced to provide commodity codes, spine width, carton quantities, gratis copy value and country of manufacture. There may be differences in metadata depending on the methods of production. For example, country of manufacture will be supplied differently when using traditional print methods where the whole print run is carried out at a location, or where a title is manufactured print on demand and the location of printing is determined by the delivery address.

In an XML-first workflow, metadata can be captured with the content files to aid with discovery. This usually requires multiple systems, both internal and external. These systems need to be able to work together to ensure that only up-to-date metadata is used. Metadata will change throughout the production process, whether it’s the publication of an accepted manuscript through to the final version of record, or pre-order information to the published version, so updates need to feed out regularly.

The right metadata needs to go to the right recipient. Some is not useful or cannot be processed by certain recipients. For example, a printer, retailer, librarian or data aggregator each have their own needs and use cases and may receive and process metadata in different formats or require different fields.

Discovery

Discovery is the series of actions taken by an end user to retrieve and access relevant content they do not know about. Discovery can happen everywhere: Google (a search engine), a library catalog, a publisher platform, etc. However, Discovery is associated with using Discovery systems in the academic sector.

The technological landscape of libraries has developed in the last 15 years. Discovery systems are tools libraries subscribe to in order to allow their end users to have one search experience within their library holdings. It is paramount for librarians that library collections are used; hence, it is very important for them that the discovery system of their choice contains all the relevant metadata. Libraries expect their discovery service to include their content coverage as comprehensively as possible. Content items not represented or misrepresented in a discovery system create challenges to libraries in how they might otherwise ensure that these materials are discovered and accessed.

Libraries’ adoption and usage of discovery systems are surrounded by the belief that the great benefits of this technology are the one search box and the configuration flexibility, which are the most important benefits. Libraries invest a significant amount of money in discovery services. The increase in usage is the success indicator of this adoption and a positive return on investment.

The backbone of discovery systems is formed by three crucial elements: a user interface, a metadata index, and a link resolver or Knowledge Base. These elements, along with a back-end control panel for librarian configuration, are the key components that enable the discovery process.

The discovery index, a database storing descriptive data from various content providers, data sets, and content types, is a testament to the collaborative efforts of content providers and discovery systems vendors. Their work under the Discovery Metadata Sharing partnership agreements, which establish the format, scope, frequency, and support of the collaboration, is instrumental in meeting librarians’ expectations.

Format

The discovery metadata integration processes have settled down for most cases in these two metadata delivery workflows.

Metadata for the index of discovery: Discovery systems have traditionally made efforts to work with various metadata formats like MARC, proprietary templates, etc., but the preferred format is XML. This metadata could include all the bibliographic information data, including index terms and full text at the article and chapter level.

Metadata for link resolvers and Knowledge bases: Knowledge bases are tools that contain information about what is included in a product, packages, and/or databases. KBART is the preferred format in this area. It includes a set of basic bibliographic descriptions at the publication level and linking information for direct and OpenURL syntaxes.

Frequency

The delivery channels vary, and the frequency could vary daily to yearly, depending on the publication schedule.

Scope

Library collections include various content types, including archival materials, open access, and multimedia alongside the more traditional books and periodicals. Different content types will require different metadata elements to make a comprehensive discovery-friendly description, and the metadata elements will impact the formats in use.

Discovery services will receive this data and prioritise uploading. They will select and manipulate the required metadata elements according to their system requirements. These metadata tweaks and selections are not always communicated to the content providers and/or libraries. Ultimately, librarians decide which metadata will be visible on their discovery tool and the linking methods of their choice.

As described, Discovery is a complex area where the activities of its main stakeholders are interconnected. The success of the end users’ discovery journey from search to access depends on the successful integration, implementation, and maintenance of the discovery systems. This necessitates a combined effort from the three discovery stakeholders: content providers, discovery system providers, and libraries. Their collaborative work is not just crucial, but integral to supporting discovery and fulfilment in the most efficient manner possible. Your active involvement in this process is what makes it successful.

How do we ensure discoverability?

Electronic resources do not exist in isolation but are assessed and used depending on their level of integration in the discovery landscape where libraries and patrons are active. From a content provider’s perspective, discoverability is about the number and efficiency of entry points to our products created in third-party discovery products.

The level of discovery integration has a direct impact on sales and upsell opportunities. Products that are not discoverable are difficult to work with, and the opposite is true for products that are considered discoverable. Your role in ensuring discoverability directly influences the user experience and sales, making your work crucial and impactful. The term ‘Discoverability’ is critical in discovery library systems. It refers to the extent to which eResources are searchable in a discovery system, and it directly influences the ease with which users can find the information they need, thereby enhancing their overall experience. In practical terms, the degree of discoverability will be impacted by the quality of the metadata supplied, the transformations the metadata suffers in the integration process to discovery systems, and the configuration’s maintenance.

The general principles of metadata quality also apply in this area: accuracy, completeness, and timely delivery. Your attention to these principles is crucial to contributing to the effectiveness of the discovery process. Metadata enrichment practices like identifiers and standards are also applicable. Your meticulous attention to detail in maintaining metadata quality ensures the effectiveness of the discovery process.

Discovery as a mindset in the publishing process will increase discoverability, as it will be influenced by product designs (whether the content is linkable) and which metadata outputs are possible. For example, author-generated index terms will be more effective for meeting research search terms, and detailed article titles will probably be more discoverable than general titles. Finally, all the integration, descriptive metadata, configurations, etc., leave much room for errors. The flow is complex; on occasion, the products and content are more complicated to describe than tools can handle, and there are millions of holdings per library to manage. Constant maintenance and troubleshooting are crucial elements to maintaining and increasing discoverability.

Metadata beyond publication

In the lead-up to publication, finalising rich complete metadata can seem like establishing a fixed set of information. Post-publication, however, the metadata workflow should be dynamic, able to evolve to keep pace with new demands and opportunities. Think of metadata as a journey rather than a one-time destination, and look at ways to futureproof your metadata by actively adapting to some of the following types of change.

Changing Publisher Goals and Product Needs

Metadata should align with changing priorities for a publisher. Developing new formats, shifts in commissioning focus or building new distribution partnerships may require metadata updates. For instance, re-releasing content in audiobook form or digitising a backlist title warrants a metadata review to ensure current and prospective readers find accurate, relevant information.

Changing Technology and Metadata Standards

Advances in technology, from artificial intelligence to emerging metadata standards, offer enhanced possibilities for capturing and updating metadata. AI, for example, can help enrich metadata with more precise subject tagging, while new metadata formats may offer greater compatibility across platforms and discovery services. Staying current with these tools can help publishers manage metadata more efficiently and enhance discoverability.

Changing Societal Values

As society evolves, so do expectations for inclusive and socially responsible metadata. Utilising new categorisation codes, such as those for the United Nations Sustainable Development Goals, can align metadata with emerging social goals. Similarly, publishers may need to revisit keywords and category codes to reflect language changes, balancing the integrity of historic records with the need for current, appropriate terminology.

Changing Industry Priorities

Commitments to accessibility and sustainability have prompted developments in metadata. Increasingly, publishers need to be able to use metadata to build a record of sustainable production methods, such as paper sources, printing methods or ink types. New metadata fields for accessibility specifications will also support more inclusive reader experiences going forward. Metadata will play an increasingly vital role in meeting industry standards for accessibility, EUDR and EAA compliance, and environmental transparency.

Changing Customer and Librarian Expectations

Finally, as the metadata expectations of customers grow and the nature of roles and responsibilities in library and collection management professions develops, teamwork and making good use of available resources are essential. Publishers don’t have to tackle this alone. Working with organisations such as Crossref or Book Industry Communication (BIC), signing up to newsletters and webinars, and forming an in-house discovery group are all great ideas for sharing ideas and best practice, and ensuring your metadata workflow is adaptable and responsive. Be part of the conversation now rather than struggling to keep up down the line!

What are some challenges and opportunities with metadata?

JM: Metadata that establishes permanence is a real opportunity in a digital landscape where content can move or be taken down, links can rot, website certificates can expire. Persistent identifiers like ORCiDs for people and DOIs for content are key examples of metadata that establish enduring routes to, and provenance of, published digital content.

KM: Metadata creation, maintenance and change has long been seen as a manual process. AI tools offer a real opportunity for metadata creation and review, especially for keywords and classification codes, at a scale and speed that has the potential to transform metadata workflows. Especially for backlist transformation, AI could offer real opportunities in this area. A challenge we face for monograph metadata more specifically is that much of the scholarly metadata infrastructure is built around the journal article, and it can be difficult to fit longer form content into these systems of discovery.

MT: Metadata is crucial. Good metadata (complete, accurate, and timely) is the base for smooth integrations and easy discovery interactions with eResources. Bad metadata (inaccurate, incomplete, late) will be the main reason for undiscovered content. At this point, the eResources industry is still based on different versions of the same metadata, which is the leading cause of problems. It is probably time to start considering a unique record approach. This unique record, which will be complete and accurate, could be used by different systems for different purposes. I know there are many details to define here, but if you think about it, it is not impossible and could solve the many known issues.

How do you ensure the quality and completeness of your metadata? Do you have ways of auditing it?

SP: Validation of data is really important, so choosing or building a system that’s set up to do this is an important foundation. It’s straightforward to check for completeness of fields and I run daily checks on our book metadata to make sure there’s nothing missing in the files feeding out. Quality can be more challenging to monitor. Feedback from data recipients is key, and accreditation schemes such as the BIC Metadata Excellence Award are a great way to benchmark progress. Good training and clear documentation help to make sure that everyone involved in creating and updating metadata understands exactly what they need to do and the standards they need to meet.

KM: Earlier this year we completed a year-long data cleansing project as part of our move to a new title management database. This gave us the time to address gaps in backlist metadata as well as to identify any inconsistencies across records for the same book, and enrich key metadata fields like classification codes, keywords and PIDs. For frontlist titles, each person owns a number of fields to ensure they are complete before a book’s metadata is distributed – some of these have validation tools which will prevent a book’s metadata from being sent out unless it is complete.

MT: Strict and consistent internal processes are essential to ensure quality and completeness. Following the different standards and industry recommendations helps to keep the quality at high standards. Random manual checks and system-based checks help to ensure everything is good. We carry out projects where we work with specific aspects of the metadata. This building-blocks approach ensures the different data layers are as good as possible. As with any project, metadata projects should have specific goals, outcomes, resources, and documentation.

How do you know if (and how much) metadata helps achieve your goals?

JM: Take any available opportunities to find out what people think of your metadata – via library conferences, institutional customer feedback, and by working with the library team at our home institution, we’ve had some really useful and interesting conversations about MUP’s metadata and where we can improve it to make it as relevant as possible for different stakeholder needs.

MT: Customers and Discovery partners will inform us if something is incorrect. Usage data is also a good indicator of how healthy our metadata is. Following industry standards is another good reference point for assessing the metadata. Finally, the metadata is only good when we know what we want to use it for. So, always considering what we are trying to achieve helps us understand how effective the metadata is.

KM: As the others have noted here, and we represent a range of different types and sizes of publishers, measuring the direct impact of metadata is an ongoing challenge. We think about the different end users who might encounter our metadata further down the supply chain – retail customers searching on Amazon, librarians filtering results on purchasing platforms, researchers finding our books and journals through citations on popular online search engines – and consider what elements of our metadata might help reach those people in the right ways.

JM: Ideally, you’ll see an uplift in sales or usage for every metadata element that you add, review or expand, although it can be challenging to quantify and prove a direct correlation between richer metadata and higher revenue or discoverability, as there are will be other factors involved. For my Operations team, what is certain is that richer, more comprehensive metadata means fewer errors are thrown up by the distribution systems and feeds we use, which means colleagues save time and gain productivity by not having to resolve and rerun failed jobs, chase missing information from other teams, or manually send information to third parties. My job is also made easier because things like size and weight of every printed product are recorded in our bibliographic database as standard, easy to report on and analyse, which helps with forecasting costs for inventory storage or shipping. Metadata can be powerful.

How good is your matching?

Dominika Tkaczyk — Wed, 06 Nov 2024 00:00:00 +0000

In our previous blog post in this series, we explained why no metadata matching strategy can return perfect results. Thankfully, however, this does not mean that it’s impossible to know anything about the quality of matching. Indeed, we can (and should!) measure how close (or far) we are from achieving perfection with our matching. Read on to learn how this can be done!

How about we start with a quiz? Imagine a database of scholarly metadata that needs to be enriched with identifiers, such as ORCIDs or ROR IDs. Hopefully, by this point in our series this is recognizable as a classic matching problem. In searching for a solution, you identify an externally-developed matching tool that makes one of the below claims. Which of the following would demonstrate satisfactory performance?

It is a cutting-edge, state-of-the-art, intelligent-as-they-come, bullet-proof technology! All the big players are using it. You won’t find anything better!
The tool was tested on the metadata of 10 articles we authored, and many identifiers were matched.
The quality of our matching is 98%.

Okay, okay, trick question. The correct answer here is to opt for secret answer #4: “I wouldn’t be satisfied by any of these claims!” Let’s dig in a bit more to why this is the correct response.

The importance of the evaluation

Before we decide to integrate a matching strategy, it is important to understand as much as possible about how it will perform. Whether it is used in a semi or fully automated fashion, metadata matching will result in the creation of new relationships between things like works, authors, funding sources, and institutions. Those relationships will then, in turn, be used by the consumers of this metadata to guide their understanding and perhaps even to make important decisions about those same entities. As organisations providing scholarly infrastructure, we must therefore take it as our paramount responsibility to understand any caveats or shortcomings of the scholarly metadata we make available, including that resulting from matching.

Proper evaluation is what allows us to do this, as it is impossible to know how well a given matching strategy will perform in its absence. This is true no matter how simple or complex a matching strategy may seem. Complex methods can be tailored to data with specific characteristics and might fail when faced with something different from this. Simple methods might be only appropriate for clean metadata or a narrow set of use cases.

Beyond complexity, matching strategies themselves vary widely in character, inheriting biases from their design, training data, or how a problem has been formulated. Some prioritise avoiding false negatives, while others focus on minimising false positives. Even a generally high-performing strategy might not be perfectly aligned with your specific needs or data. In some cases, the task also itself might be too challenging, or the available metadata too noisy, for any matching strategy to perform adequately.

Evaluation is, again, how we understand these nuances and make informed decisions about whether to implement matching or avoid it altogether. By now, it should also be clear that the notion “we don’t need to evaluate” is far from ideal! Given its importance, let’s explore how evaluation is actually done.

Evaluation process

In general, a proper evaluation procedure should follow the following steps:

Preparation of an evaluation dataset containing many examples of matching inputs and the corresponding expected outputs.
Applying the strategy to all inputs from the dataset and recording the responses.
Comparing the expected outputs with the outputs from the strategy.
Converting the results of the above comparison into evaluation metrics.

From this accounting, we can see that there are two primary components for the evaluation process: an evaluation dataset and metrics.

Evaluation dataset

It’s useful to conceive an evaluation dataset as the specification for an ideal matching strategy, describing what would be returned from our forever-elusive perfect matching. When creating such a dataset, what this means in practice is that it should contain a number of real-world, example inputs, along with the corresponding ideal or expected outputs, and that all data should be in the same format as the strategy is expected to process. The outputs should themselves also confirm the strategy’s overall requirements, for example, by being consistent with its cardinality, meaning whether zero, one, or multiple matches should be returned and under what circumstances. In terms of size, it’s generally useful to calculate the ideal number of evaluation examples using a sample size calculator or using standardised measures, but as a quick rule of thumb: less than 100 examples is probably insufficient, more than 1,000 or 2,000 is generally acceptable.

It is also important that the evaluation dataset be representative of the data to be matched in order to ensure reliable results. Using unrepresentative data, even if convenient, can lead to biassed or misleading evaluations. For example, if matching affiliations from various journals, building an evaluation dataset solely from one journal that already assigns ROR IDs to authors’ affiliations might be tempting. The data, having been already annotated, allow us to avoid the tedious work of labelling, and we might even know that it is produced by a high-quality source. This is still, unfortunately, a flawed approach. In practice, such datasets are unlikely to represent the entire range of affiliations to be matched, potentially leading to a significant discrepancy between the evaluated quality and the actual performance of the matching strategy, when applied to the full dataset. To assess a matching strategy’s effectiveness, we have to resist shortcuts and instead do our best to create truly representative evaluation datasets to be confident that we’ve accurately measured their performance.

Evaluation metrics

Evaluation metrics are what allow us to summarise the results of the evaluation into a single number. Metrics give us a quick way to get an estimation of how close the strategy was to achieving perfect results. They are also useful if we want to compare different strategies with each other or decide whether the strategy is sufficient for our use case, removing the need to compare countless evaluation examples from different strategies against one another.

The simplest metric is accuracy, which can be calculated as the fraction of the dataset examples that were matched correctly. While a commonsense benchmark, accuracy can be misleading, and we generally do not recommend using it. To understand why, let’s consider the following small dataset and the responses from two strategies:

Input	Expected output	Strategy 1	Strategy 2
string 1	ID 1	ID 1	ID 1
string 2	ID 2	ID 3	Empty output
string 3	Empty output	Empty output	Empty output

Both strategies achieved the same accuracy, 0.67, making one mistake each on the second affiliation string. However, a closer examination reveals that these error types are distinct. The first strategy matched to an incorrect identifier, while the second refused to return any value illustrating the limitation of accuracy as a measure: it generally fails to capture important nuances in strategy behaviour. In our example, the first strategy appears more permissive, returning matches even in unclear circumstances, while the second is more conservative, withholding them when uncertain. Although using such a small dataset would preclude drawing any definitive conclusions, it highlights how relying on accuracy alone can obscure differences in performance.

For evaluating matching strategies, we instead recommend using two metrics: precision and recall. To recap from our previous blog post:

Precision is calculated as the number of correctly matched relationships resulting from a strategy, divided by the total number of matched relationships. It can also be interpreted as the probability that a match is correct. Low precision indicates a high rate of false positives, which are incorrect relationships created by the strategy.
Recall is calculated as the number of correctly matched relationships resulting from a strategy, divided by the number of true (expected) relationships. It can also be interpreted as the probability that a true (correct) relationship will be created by the strategy. Low recall means a high rate of false negatives, which are relationships that should have been created by the strategy but were not made.

Applying these measures to our prior example, the strategies achieved the following results:

Strategy 1: accuracy 0.67, precision 0.5, recall 0.5
Strategy 2: accuracy 0.67, precision 1.0, recall 0.5

As we can see, while both strategies have the same accuracy, using precision and recall better describes the difference between the two sets of results. Strategy 1’s lower precision indicates it made false positive matches, while Strategy 2’s perfect precision shows that it made none. The identical recall scores show both identified half of the possible matches.

Of course, results calculated using such a small dataset are not very meaningful. If we obtained these scores from a large, representative evaluation dataset, it would indicate to us that Strategy 1 risks introducing many incorrect relationships, while Strategy 2 would be unlikely to do so. In both cases, we would still expect approximately half of the possible relationships to be missing from the strategies’ outputs.

Which one is more important to prioritise, precision or recall? It depends on the use case. As a general rule, if you want to use the strategy in a fully automated way, without any form of manual review or correction of the results, we recommend paying more attention to precision. Privileging precision will allow you to better control the number of incorrect relationships added to your data. If you want to use the strategy in a semi-automated fashion, where there is a manual examination of and a chance to correct the results, pay more attention to recall. Doing so will guarantee that enough options are presented during the manual review stage and fewer relationships will be missed as a result.

To get a more balanced estimation of performance, we can also consider both precision and recall at the same time using a measure called F-score. F-score combines precision and recall into a single number, with variable weight given to either aspect. There are three commonly used types, each calculated as the weighted harmonic mean of precision and recall:

F0.5: Precision is weighted more heavily. It can be understood as a score that is 50% more sensitive to precision than recall. A high F0.5 score indicates a measure of performance that minimises false positives.
F1: Equal weight is given to both precision and recall. It can be interpreted as the most balanced score in this set. High F1 indicates good overall performance, with both false positives and false negatives being minimised equally.
F2: Recall is weighted more heavily. It can be understood as a score that is 50% more sensitive to recall than precision. A high F2 score indicates a measure of performance where false negatives are minimised.

Each of these variants allows for fine-tuning the evaluation metric to align with your expectations for a specific matching task. Choose whichever reflects the relative importance of precision versus recall for your use case.

To summarise, to avoid falling prey to misleading sales pitches or silly quizzes, it is important to have a good understanding of the performance of any strategies you are building or integrating. With thorough evaluation, including a representative dataset and carefully considered metrics, we can estimate the quality of matching and, by extension, its resulting relationships.

Now that we’ve covered how to evaluate effectively, we can move on to some other aspects of metadata matching. Our next blog post will take a final, more holistic view of matching, exploring some complementary considerations to all of the preceding. Stay tuned for more!

Scholarly metadata as trust signals: Opportunities for journal editors

Madhura Amdekar — Mon, 04 Nov 2024 00:00:00 +0000

Scholarly metadata as trust signals: opportunities for journal editors

Published in Science Editor (Vol. 47, No. 4, December 2024), this article reframes scholarly metadata as a practical trust signal in the fight to protect research integrity — and sets out specific, actionable opportunities for journal editors to use Crossref metadata to detect, deter, and respond to integrity threats.

Strategists

Understand why metadata is integrity infrastructure. The presence and richness of metadata — not the DOI itself — is what carries trust signals across the scholarly record.

Decision-makers

Know which metadata to require and check. A practical framework for journal editors making policy decisions on contributor identifiers, affiliations, funding, peer review, and update notices.

Practitioners

See where to act in editorial workflows. Concrete opportunities to use Crossref metadata, Crossmark, and Cited-by to detect paper mills, citation cartels, and other integrity threats.

What this article covers

The integrity landscape — paper mills, citation cartels, fabricated peer reviews, fake papers, and AI-generated images as emerging threats to the scholarly record
Metadata as trust signal — why the DOI alone does not signal quality, and how the presence (or absence) of associated metadata acts as evidence of trustworthiness
Crossref’s role — how open, machine-readable metadata across member deposits enables downstream services and editors to assess research outputs at scale
ROR IDs — how organisation identifiers help connect problematic manuscripts to their institutional context
Crossmark — how update notices, retractions, and corrections strengthen the integrity of the scholarly record after publication
Cited-by — how citation context can surface citation patterns worth attention
A call to journal editors — concrete opportunities to enrich the metadata you deposit and to draw on the metadata others have deposited

Read the article

Read on Science Editor

The myth of perfect metadata matching

Dominika Tkaczyk — Wed, 28 Aug 2024 00:00:00 +0000

In our previous instalments of the blog series about matching (see part 1 and part 2), we explained what metadata matching is, why it is important and described its basic terminology. In this entry, we will discuss a few common beliefs about metadata matching that are often encountered when interacting with users, developers, integrators, and other stakeholders. Spoiler alert: we are calling them myths because these beliefs are not true! Read on to learn why.

If you have stuck with us this far in our series, hopefully, you are at least a bit excited about the possibility of creating new relationships between the works, authors, institutions, preprints, datasets, and myriad other objects in our existing scholarly metadata. Who would not want all of these to be better connected?

We have to pause for a moment and be honest with you: metadata matching is a complex problem, and doing it correctly requires significant effort. What is worse, even if we do everything right, our matching won’t be perfect. This may be counterintuitive. Perhaps you’ve heard that matching is not a hard problem, or have encountered people surprised that a matching strategy returned a wrong or incomplete answer. Sometimes, it is obvious to a person from looking at some specific example that a match should (or should not) have been made, so they naturally assume that a change to account for this has to be simple.

Misconceptions like these can be problematic. They create confusion around matching, drive users’ expectations to unreasonable levels, and make people drastically underestimate the effort needed to build and integrate matching strategies. So let’s dive right in and debunk a few common myths about metadata matching.

Myth #1: A metadata matching strategy should be 100% correct

Anyone who has built or supported a matching strategy has likely encountered the following belief: it is possible to develop a perfect strategy, meaning one that always returns the correct results, no matter the inputs. The unfortunate truth is that while one’s aim should always be to design matching strategies that return correct results, once we move beyond the simplest class of problems or artificially clean data, no strategy can achieve this outcome. In thinking through why this is the case, some inherent constraints become obvious:

The inputs to matching are often strings in human-readable formats, which can vary wildly in their structure, order and completeness. Since they’re intended to be parsed by people, instead of machines, they’re inherently lossy and frequently unstructured, anticipating that a person can infer from the source context what is being referenced. Matching strategies, although built to make sense of unstructured data, unfortunately, don’t have the luxury of this flexibility. A strategy has to account for translating a messy, partial, or inconsistent input into a correct and structured match.

Consider, for example, the following inputs to an affiliation matching strategy:

“Department of Radiology, St. Mary’s Hospital, London W2 1NY, UK”
“Saint Mary’s Hospital, Manchester University NHS Foundation Trust”
“St. Mary’s Medical Center, San Francisco, CA”
“St Mary’s Hosp., Dublin”
“St Mary’s Hospital Imperial College Healthcare NHS Trust”
“聖マリア病院”

In order to correctly identify the organisations mentioned here, the matching strategy must be able to distinguish between different ways of representing the same institution, disambiguate multiple institutions that have similar names, and handle variant forms for the parts of each name (Saint/St./St), identify the same name in different languages (“聖マリア病院” is Japanese for “St. Mary’s Hospital”), and make assumptions about partial or ambiguous locations translating to more precise references. While a person reviewing each of these strings might be able to accomplish these tasks, even here there are some challenges. Does “St Mary’s Hosp., Dublin” refer to the hospital in Ireland or a separate hospital in one of the many cities that share this name? Should we presume that because “聖マリア病院” is in Japanese, this refers to a hospital in Japan? Would someone, by default, be aware that St. Mary’s Hospital in London is part of the Imperial College Healthcare NHS Trust, such that inputs one and five refer to the same organisation?

An additional challenge lies in the quality of the data, which in the context of matching, encompasses both the input and the dataset being matched against. In real world circumstances, no dataset is fully accurate, complete, or current and certainly not all three. As a result, there will always be functionally random differences between inputs to the strategy and the entities to be matched. A theoretically perfect matching strategy would thus need to distinguish between inconsequential discrepancies resulting from gaps, errors, and variable forms of reference and actual, meaningful differences indicating an incorrect match. As one might imagine, this would require near total knowledge of the meaning and context for all inputs and outputs, a nigh-on impossible task for any person or system!

As a consequence, no metadata matching strategy will ever be perfect. It is unreasonable for us to expect them to be. This does not mean, of course, that all strategies are equally flawed or destined to forever return middling results. Some are better than others and we can improve them over time. Which brings us to the next myth:

Myth #2: It is always a good idea to adapt the matching strategy to a specific input

Matching strategies are not static. They can - and should - be improved. There is, however, a deceptive trap that one can fall into when attempting to improve a matching strategy. Whenever we encounter an incorrect or missing result for a specific input, we treat this problem like a software bug and try to adapt the strategy to work better for it, without considering all other cases.

The more complicated reality is that the quality of matching results is controlled through a complex set of trade-offs between precision and recall that determine the kind and number of relationships created between items:

Precision is calculated as the number of correctly matched relationships resulting from a strategy, divided by the total number of matched relationships. It can also be interpreted as the probability that a match is correct. Low precision indicates a high rate of false positives, which are incorrect relationships created by the strategy.
Recall is calculated as the number of correctly matched relationships resulting from a strategy, divided by the number of true (expected) relationships. It can also be interpreted as the probability that a true (correct) relationship will be created by the strategy. Low recall means a high rate of false negatives, which are relationships that should have been created by the strategy but were not made.

The diagram depicts false negatives and false positives. The ideal outcome would be that the ellipses are identical, matched relationships are exactly the same as true relationships, and there are no false negatives or false positives. In practice, we try to make the intersection as big as possible.

The tradeoff between precision and recall roughly means that modifying the strategy to improve recall will decrease precision, and vice versa.

Imagine, for example, we received a report about a relationship that was missed by matching because of a partial, noisy, or ambiguous input. We might be tempted to resolve this issue by relaxing our matching criteria. Unfortunately, this will have a cost of a higher overall rate of false positive matches.

Conversely, if we encounter a case where the matching has returned an incorrect match, we might attempt to make the matching strategy stricter to avoid this result. We should remember, however, that this may have the consequence of causing the strategy to skip many perfectly valid matches.

The tradeoff between precision and recall. (a) A strict strategy prioritises precision over recall resulting in more false negatives. (b) A relaxed strategy prioritises recall over precision resulting in more false positives.

Striking this balance becomes even more difficult when attempting to address multiple issues at once, or considering constraints like the time and resources consumed by each aspect of the strategy. Each choice can compound the individual effects in unanticipated and expensive ways. The aim of matching ultimately then can’t be to achieve perfect results for every single case. Fixing one particular situation might not be desirable, as it can result in breaking multiple other cases. Instead, we have to find a locally optimal balance that optimises the strategy’s utility, relative to these inherent limitations. This means accepting some level of imperfection as not just inevitable, but necessary for implementing a workable strategy. When you consider all this, you might conclude that…

Myth #3: We shouldn’t do large-scale, unsupervised matching

Imperfect matching strategies, when applied automatically to real-world large datasets, might:

Fail to discover some relationships (false negatives), an outcome that may not be terribly problematic. In the worst case scenario, we have wasted a great deal of effort developing matching strategies that do not improve our metadata.
Create incorrect relationships between items (false positives), what seems like a potentially larger problem, where we have added incorrect relationships to the metadata.

Many have the instinct to avoid false positives at any cost, even if this means missing many additional correct relationships at the same time. They might come to the conclusion that if we cannot have 100% precision (see our previous myth), we simply should not allow matching strategies to act in an automated, unsupervised way on large datasets. While there might be circumstances where this belief is rational, in the context of the scholarly record, this notion is seriously flawed.

First, if you are dealing with any medium to large-sized dataset, it almost certainly contains errors, even before you apply any automated processing to it. Even if data is submitted and curated by users, they can still make mistakes, and might themselves be using automated tools for extracting the data from other sources, without your knowledge. It is thus not entirely obvious that applying an (imperfect) matching strategy to create more relationships would actually make the data quality worse.

Second, while we cannot eliminate all matching errors, we can place a high priority on precision when developing strategies, with the aim of keeping the number of incorrectly matched results as low as possible. We can also make use of additional mechanisms to easily correct for incorrectly matched results, for example doing so manually, in response to error reports.

Finally, the results of matching should always contain provenance information to distinguish them from those that have been manually curated. This way, the users can make their own decisions about whether to use and trust the matching results, relative to their use case.

By applying those additional checks, we can minimise the negative effects of incorrect matching, while at the same time reap the benefits of filling gaps in the scholarly record.

Myth #4: We can only ever guess at the accuracy of our matching results

In attempting to determine the correctness of our matching, we immediately encounter a number of inherent limitations. The sheer amount of entries in many datasets prevents a thorough, manual validation of the results, but if instead, we use too few or specific items as our benchmarks, these are unlikely to be representative of overall performance. The unpredictable nature of future data adds another wrinkle: will our matching always be as successful as when we first benchmarked it or will its performance degrade relative to some change in the data?

With so many unknowns, are we then doomed? No! We have rigorous and scientific tools at our disposal that can help us estimate how accurate our matching will be. How do we use them? Well, that is a big and fairly technical topic, so we will leave you with this little cliffhanger. See you in the next post!

Re-introducing Participation Reports to encourage best practices in open metadata

Lena Stoll — Thu, 25 Jul 2024 00:00:00 +0000

We’ve just released an update to our participation report, which provides a view for our members into how they are each working towards best practices in open metadata. Prompted by some of the signatories and organizers of the Barcelona Declaration, which Crossref supports, and with the help of our friends at CWTS Leiden, we have fast-tracked the work to include an updated set of metadata best practices in participation reports for our members. The reports now give a more complete picture of each member’s activity.

What do we mean by ‘participation’?

Crossref runs open infrastructure to link research objects, entities, and actions, creating a lasting and reusable scholarly record. As a not-for-profit with over 20,000 members in 160 countries, we drive metadata exchange and support nearly 2 billion monthly API queries, facilitating global research communication.

To make this system work, members strive to provide as much metadata as possible through Crossref to ensure it is openly distributed throughout the scholarly ecosystem at scale rather than bilaterally, thereby realizing the collective benefit of membership. Together, our membership provides and uses a rich nexus of information— known as the research nexus—on which the community can build tools to help progress knowledge.

Each member commits to certain terms, such as keeping metadata current, updating links for their DOIs to redirect to, linking references and other objects, and preserving their content in perpetuity. Beyond this, we also encourage members to register as much rich metadata as is relevant and possible.

Creating and providing richer metadata is a key part of participation in Crossref; we’ve long encouraged a more complete scholarly record, such as through Metadata 20/20, and through supporting or leading initiatives for specific metadata, like open citations (I4OC), open abstracts (I4OA), open contributors (ORCID), and open affiliations (ROR).

Which metadata elements are considered best practices?

Alongside basic bibliographic metadata such as title, authors, and publication date(s), we encourage members to register metadata in the following fields:

Example participation report for Crossref member University of Szeged

References

A list of all the references used by a work. This is particularly relevant for journal articles but the references can include any type of object, including datasets, versions, preprints, and more. Additionally, we encourage these to be added into relationships, where relevant.

Abstracts

A description of the work. These are particularly useful for discovery systems that will promote the work, and are often used in downstream analyses such as for detecting integrity issues.

Contributor IDs (ORCID)

All authors should be included in a work’s metadata, ideally alongside their verified ORCID identifier.

Affiliations / Affiliation IDs (ROR)

Members are able to register contributor affiliations as free text, but we are encouraging everyone to add ROR IDs for affiliations as the recommended best practice, as this differentiates and avoids mistyping. These two fields have newly been added to the participation reports interface in the most recent update.

Funder IDs (OFR)

Acknowledging the organisation(s) that funded the work. We encourage the inclusion of Open Funder Registry identifiers to make the funding metadata more usable. This will evolve into an additional use case for ROR over time.

Funding award numbers / Grant IDs (Crossref)

A number or identifier assigned by the funding organisation to identify the specific award of funding or other support such as use of equipment or facilities, prizes, tuition, etc. The Crossref Grant Linking System includes a unique persistent link that can be connected with outputs, activities, people, and organisations.

Crossmark

The Crossmark service gives readers quick and easy access to the current status of a record, including any corrections, retractions, or updates, via a button embedded on PDFs or a web article. Openly adding corrections, retractions, and errata is critical part of publishing, and the button provides readers with an easy in-context alert.

Similarity Check URLs

The Similarity Check service helps editors to identify text-based plagiarism through our collective agreement for the membership to access to Turnitin’s powerful text comparison tool, iThenticate. Specific full-text links are required to participate in this service.

License URLs

URLs pointing to a license that explains the terms and conditions under which readers can access content. These links are crucial to denote intended downstream use.

Text mining URLs

Full-text URLs that help researchers in meta-science easily locate your content for text and data mining.

What is a participation report?

Participation reports are are a visualization of the data representing members’ participation to the scholarly record which is available via our open REST API. There’s a separate participation report for each member, and each report shows what percentage of that member’s metadata records include 11 key metadata elements. These key elements add context and richness, and help to open up members’ work to easier discovery and wider and more varied use. As a member, you can use participation reports to see for yourself where the gaps in your organisation’s metadata are, and perhaps compare your performance to others. Participation reports are free and open to everyone - so you can also check the report for any other members you are interested in.

We first introduced participation reports in 2018. At the time, Anna Tolwinska and Kirsty Meddings wrote:

Metadata is at the heart of all our services. With a growing range of members participating in our community—often compiling or depositing metadata on behalf of each other—the need to educate and express obligations and best practice has increased. In addition, we’ve seen more and more researchers and tools making use of our APIs to harvest, analyze and re-purpose the metadata our members register, so we’ve been very aware of the need to be more explicit about what this metadata enables, why, how, and for whom.

All of that still rings true today. But as the research nexus continues to evolve, so should the tools that intend to reflect it. For example, in 2022, we removed the Open references field from participation reports after a board vote to change our policy and update the membership terms meant that all references deposited with Crossref would be open by default. And now we’ve expanded the list of fields again, adding coverage data for contributor affiliation text and ROR identifiers.

Putting it in practice

To find out how you measure up when it comes to participation, type the name of your member organisation into the search box. You may be surprised by what you find—we often speak to members who thought they were registering a certain type of metadata for all their records, only to learn from their participation report that something is getting lost along the way.

You can only address gaps in your metadata if you know that they exist.

More information, as well as a breakdown of the now 11 key metadata elements listed in every participation report and tips on improving your scores, is available in our documentation.

And if you have any questions or feedback, come talk to us on the community forum or request a metadata Health Check by emailing the community team.

Metadata schema development plans

Patricia Feeney — Mon, 22 Jul 2024 00:00:00 +0000

It’s been a while, here’s a metadata update and request for feedback

In Spring 2023 we sent out a survey to our community with a goal of assessing what our priorities for metadata development should be - what projects are our community ready to support? Where is the greatest need? What are the roadblocks?

The intention was to help prioritize our metadata development work. There’s a lot we want to do, a lot our community needs from us, but we really want to make sure we’re focusing on the projects that will have the most immediate impact for now.

Several projects were proposed, based on community demand over time. All are projects we intend to support long-term.

Projects

The projects included in the survey were:

Alternate names - We proposed adding a repeatable ‘name’ element to allow for names that aren’t separated by given/family/surname.
Updates to funding data -this update will be released in the near future and includes:
- Expand ROR support - Allow members to supply ROR ID instead of funder ID in funding data and grant records.
- Include Grant DOIs in funding metadata.
Publication typing in citations - Support citation type in citation metadata (for example article, preprint, data, software, etc.).
Expand contributor role support - Allow multiple contributor roles to be provided per contributor and add support for external vocabularies (like CRediT)
Expand abstract support - We currently require all abstracts to be formatted using JATS. We will be adding new abstract formats, including BITS and ONIX (which have been requested), as well as a generic abstract format (non-JATS).
Statements - Add support for free text statements such as data availability, acknowledgments, funding, and conflict of interest.
Contributor identifiers - Accept contributor identifiers such as ISNI (in addition to ORCID, which is already supported).
Conference event IDs - Identifiers for conference events.

What’s next?

There is a clear preference for publication types in citations and abstract markup, expanded support for multilingual metadata, followed by expanding contributor roles to support multiple roles and the CRediT taxonomy. The results have helped us prioritize our work and we’re advancing several projects soon based on our readiness to move forward.

First up is publication typing in citations and statements - we hope to be able to make this ready for registration in the coming months, but want to confirm a few things first, primarily the list of ‘types’ to apply to citations, so please review and comment: Metadata updates in need of feedback July 2024

We also have been discussing expansions to our support for preprints metadata with our Preprints Advisory Group and have a number of preprint-specific updates that will be rolled out in the coming months as well, including support for versions and status. These proposed changes are also available for comment.

And finally, we will be expanding support for contributor roles to include multiple roles per contributor, as well as adding support for the CRediT taxonomy. This update is yet to be scheduled but we do have the inputs and output planning done and welcome any comments on this as well.

We will also be continuing work on other projects highlighted in the survey that aren’t quite ready to go:

Multilingual metadata: Support for multilingual metadata in particular is very important and will require a fairly significant technical effort, so we want to be sure we get this right - at minimum we need to include repeatable fields flagged with language metadata for most items, there may be other considerations as well such as the scope of languages supported.

As we develop new metadata segments we’re keeping language metadata in mind, but I’d like to form a short-term working group to help shape this update - this group will be focused on the details of supporting multilingual metadata in our inputs and outputs, so conversations will be very XML and JSON heavy. If you are interested and available please contact pfeeney@crossref.org.
Abstract markup: we are currently in the research phase of this project but will be proposing updates and asking for input this fall. At the moment support for BITS and ONIX abstracts have been requested, as well as an agnostic format.
Expansion of name and contributor ID support: work is under way for this as well, and I should have inputs and outputs for feedback in the coming months.

We anticipate more developments and requests for feedback in the future as we still have other projects from the list above to get to. I’ve opened up a ‘Metadata Development’ section in our Community Forum to invite discussion and will be kicking off a renewed Metadata Interest Group in the fall.

Celebrating five years of Grant IDs: where are we with the Crossref Grant Linking System?

Kornelia Korzec — Mon, 01 Jul 2024 00:00:00 +0000

We’re happy to note that this month, we are marking five years since Crossref launched its Grant Linking System. The Grant Linking System (GLS) started life as a joint community effort to create ‘grant identifiers’ and support the needs of funders in the scholarly communications infrastructure.

The system includes a funder-designed metadata schema and a unique link for each award which enables connections with millions of research outputs, better reporting on the research and outcomes of funding, and a contribution to open science infrastructure. Our first activity to highlight the moment was to host a community call last week where around 30 existing and potential funder members joined to discuss the benefits and the steps to take to participate in the Grant Linking System (GLS).

Some organisations at the forefront of adopting Crossref’s Grant Linking System presented their challenges and how they overcame them, shared the benefits they are reaping from participating, and provided some tips about their processes and workflows.

The funding organisations whose experiences were shared included Wellcome, FCT (Foundation for Science and Technology, Portugal), and NWO (Dutch Research Council). They were joined by a new group of foundations, research councils, and private research funders from around the world—from Kenya to Singapore to Estonia—to have a first introduction to the GLS and connect them with colleagues who are further along on their journey.

We also heard about tools such as a new open source Crossref plugin for the Fluxx platform, grant management systems with in-built Crossref integrations such as ProposalCentral, Europe PMC GrantFinder which was first to implement the GLS on Wellcome’s behalf and hosts their grants, and one of the first publishers, eLife to start referencing Crossref grant links in their publications both online and in the open metadata for others to retrieve.

Read on for further information or watch the recording of the event.

What is the Crossref Grant Linking System?

The Crossref Grant Linking System, conceptualised in 2017, and launched in 2019, captures and helps clarify funding relationships for scholarly outputs. Thanks to interconnectedness with the 160 million metadata records collected and curated by Crossref members, it enables funders as well as scholars to track and analyse funding patterns and evaluate programmes, and it supports assertions about the integrity of scholarly records.

Features of the GLS

Globally unique persistent link and identifier for each grant
Connected with 160 million published outputs
Funder-designed metadata schema, including project, investigator, value, and award-type information
Programmatic or no-code methods to send metadata
- Thanks to the Gordon and Betty Moore Foundation who funded development of the online grant registration form
Open search and API for all to discover funding outcomes; all metadata is distributed openly to thousands of tools and services
Crossref-hosted landing pages
A global community of ~50 funder advisors and 35+ funders already in the Grant Linking System
Membership of Crossref; influence the foundational infrastructure powering open research

The last five years has seen the GLS grow through membership, metadata, and community contributions.

The momentum for this programme is building - as illustrated by increasing numbers of metadata records (and related relationships we’re seeing). The 35 funder members represent over 100 funding programmes and have created 125,000 grant records already.

During last week’s call, it was helpful to hear from the community what they see as key benefits of the Crossref Grant Linking System:

Meaningfully delivering on and supporting Open Science policies and mandates, and contributing ‘their bit’ to the transparency of the evidence trail in the scholarly ecosystem.
Reporting and evaluating the funding programmes, essential for the public funders who need to demonstrate the value for money in allocating their funds and other support.
Supporting a more holistic assessment of scholarship and scholars, especially as and when metadata becomes included with a full array of outputs, not limited to books and articles.

How the Crossref Grant Linking System supports Open Science policy

Since 2020, all the grant records are openly available through our REST API which is queried more than 1.8 billion times every month so these metadata records are distributed to thousands of systems across the research enteprise. In a 2022 blog, Ed Pentz and Ginny Hendricks laid out guidelines for research funders to meet open science guidelines using existing open infrastructure such as Crossref, ORCID, and ROR. Syman Stevens, a grantmaking and private philanthropy consultant, highlighted on the call that the funders he works with are increasingly interested in ways to deliver on their open science policy and that participation in the GLS is a tangible thing they can do to meet this goal.

As part of its open science policy, NWO will start participating in the Crossref Grant Linking System from July 2025. Research funders are a part of the scholarly communications system; we not only provide the funding to do the actual research but can also be the authoritative source of data about the projects we have funded and the outputs arising from that funding. Increasingly, all these elements – grants, researchers, outputs - are linked with metadata and unique identifiers to ensure that research is findable and accessible.

– Hans de Jonge, Director of Open Science NL, part of the Dutch Research Council (NWO)

How funders leverage the Grant Linking System in their reporting and assessment

Looking back to the origins of the system, it’s important to recognise the work of the initial working groups. Through their contribution, funders helped design the initial metadata schema for grants as well as establish the governance and fees for this service, and our Advisory Group continues to inform further developments. In this way, the Grant Linking System enables the needs and wishes of funders to contribute and see their data as part of the wider ecosystem.

An excellent example of that synergy in action is the use case presented by Cátia Laranjeira, manager of the PTCRIS programme at the Foundation for Science and Technology, Portugal (FCT). PTCRIS is the Foundation’s integrated national information ecosystem that supports scientific activity management. Cátia reflected on the relative fragmentation of spaces where the scientific outputs are found, and PTCRIS’s ambition for aggregating metadata in one place to be able to trace and evaluate programmes in light of the related outputs. At the start of the programme, they identified lack of a persistent identifier for grants as a major shortcoming of the system. Crossref GLS naturally fits in with their goals.

The initiative by FCT to assign unique DOIs to national public funding through Crossref is a game-changer for open science, linking funding directly to scientific outcomes and boosting transparency. Join us in this effort—let’s make every grant count and ensure open access to research information!"

– Cátia Laranjeira, PTCRIS Program Manager at Fundacao para a Ciencia e a Tecnologis (FCT Portugal)

FCT initially piloted a small subset of their grants (approximately 6,000 recent awards) at the end of 2023. Cátia pointed to researchers’ keen participation in this programme as one of its successes – and thanks to the word of mouth, FCT has already been approached by researchers requesting unique Crossref links for their grants! This appetite for grant IDs will soon be more fully satisfied, as FCT is readying to register all of their grants with Crossref, to enable further insights into funding and outcome flows, supporting them in demonstrating the value for money for the public resources they manage. Via interfaces for grant management and standardised online CVs, the system is also enabling researchers to use the system in their own future reporting and career development.

In the ensuing discussion, Rachel Bruce of UKRI mentioned that she’s hopeful that GLS will help funders ‘close the loop’ on more holistic reward and recognition, allowing for inclusion of evidence for a broader set of outputs in those processes.

How the community is working to integrate open infrastructure

Melissa Harrison, Team Leader at EMBL-EBI, manages Europe PMC and a complementary data science team, who were part of the initial FREYA project – supporting infrastructure delivery for unique identifiers for grants. The team has been adding grant records to Crossref on Wellcome’s behalf since 2019. Melissa highlighted the shortcomings of internal award numbers, which don’t tend to be understood outside of the ecosystem where they are produced (that is the funder’s administrative system), are almost certainly not unique, and don’t resolve to or connect with anything in the wider ecosystem. Therefore internal award numbers can’t signify relationships with other outputs or assets in the wider world. By contrast, Crossref’s Grant IDs are unique, persistent, resolvable, and interrelated with other Crossref metadata, whilst being retrievable for other systems to link to too.

Persistent identifiers for grants was the next logical step after identifiers for funders - open metadata registered with a PID in a central service like Crossref is invaluable to build the full picture of the research enterprise.

– Melissa Harrison, Team Leader, Literature Services at EMBL-EBI)

Ease of execution is important for scaling the Grant Linking System, and enabling its use in a diverse set of circumstances in the open science ecosystem. Altum was the trailblazer, first integrating its grant management platform Proposal Central with GLS. It was good to hear that others are now joining the integration efforts. Syman Stevens talked about the recent work initiated by Joe McArthur at OA Works, to develop a simple, open-source plug-in for any of the major grant management systems, to enable funders to deposit their grant metadata with Crossref GLS with a click of the button. Syman demonstrated the resulting interface in Fluxx, that allows for creating a record and sending grant metadata to Crossref as part of the regular grant management within the platform. He pointed out that, while this integration was developed for Fluxx, all code and documentation is openly available on GitHub and this can potentially be forked or adapted as necessary for reuse in other grant management systems.

It is heartening that others in the community are seeing such a need for this that they’re funding and creating their own tools to advance participation and use of the GLS.

Finally, Fred Atherden, Head of Production Operations at eLife, presented how they include Crossref grant identifiers in publication metadata for the version of record of the works published on their platform. eLife is the first publisher to fully integrate Crossref grant identifiers both within the article display and in the metadata. Fred shared that in addition to collecting the data from the authors, eLife also attempts matching, albeit using very restrictive methodology, to enable more grant metadata in their publication records. They recognise that so far there are very few publishers including persistent links for grants in this way, and talked about plans to start collecting and including this data further upstream, and including them in the future for reviewed preprints.

Acknowledgements and how to participate in the GLS

Reflecting on the last five years, thanks must go to the >35 funders who are already participating (see logo mashup below), to our current volunteers and to those partners working to promote and make use of the Grant Linking System. We also acknowledge that the GLS would not have been possible without the Crossref board members at the time, our staff including alumni Josh Brown, Jennifer Kemp, Rachael Lammey, and Geoffrey Bilder, or without the early dedicated time and input from the following people and organisations on our working groups for governance and fees, and for metadata modelling:

Yasushi Ogasaka and Ritsuko Nakajima, Japan Science & Technology Agency
Neil Thakur and Brian Haugen, US National Institutes of Health
Jo McEntyre and Michael Parkin, Europe PMC
Robert Kiley and Nina Frentop, Wellcome
Alexis-Michel Mugabushaka and Diego Chialva, European Research Council
Lance Vowell and Carly Robinson, OSTI/US Dept of Energy
Ashley Moore and Kevin Dolby, UKRI (Research Councils UK / Medical Research Council)
Salvo da Rosa, Children’s Tumor Foundation
Trisha Cruse, DataCite

To learn more about the Crossref Grant Linking System, the best place to start is our service page. And for the next step, please reach out to us for a conversation about any questions specific to your organisation and any questions that may need to be addressed in order to enable your full participation.

Grant DOIs enhance the discovery and accessibility of funded project information and are one of the important links in a connected research ecosystem. I’m grateful and proud to contribute to the robustness and interconnectedness of the research infrastructure. Few funders are currently participating in the Crossref Grant Linking System, and I encourage others to consider doing so. This adoption follows the “network effect,” where the value and utility increase as more people participate, encouraging even wider adoption.

– Kristin Eldon Whylly, Senior Grants Manager and Change Management Lead at Templeton World Charity Fund (TWCF)

You can email me via feedback@crossref.org or set up a call with me when it suits you (you can overlay your own calendar using the toggle at the top right). We look forward to welcoming even more funders and to see those relationships in the open science infrastructure grow even further in the coming years.

The anatomy of metadata matching

Dominika Tkaczyk — Thu, 27 Jun 2024 00:00:00 +0000

In our previous blog post about metadata matching, we discussed what it is and why we need it (tl;dr: to discover more relationships within the scholarly record). Here, we will describe some basic matching-related terminology and the components of a matching process. We will also pose some typical product questions to consider when developing or integrating matching solutions.

Basic terminology

Metadata matching is a high-level concept, with many different problems falling into this category. Indeed, no matter how much we like to focus on the similarities between different forms of matching, matching affiliation strings to ROR IDs or matching preprints to journal papers are still different in several important ways. At Crossref and ROR, we call these problems matching tasks.

Simply put, a matching task defines the kind or nature of the matching. Examples of matching tasks are bibliographic reference matching, affiliation matching, grant matching, or preprint matching.

Every matching task has an input, which is all the data that is needed to perform the matching. Input data can come in many shapes and forms, depending on the matching task. For example, all of the following could be inputs to a matching task:

Department of Molecular Medicine, Sapporo Medical University, Sapporo 060-8556, Japan

<fr:program xmlns:fr="http://www.crossref.org/fundref.xsd" name="fundref">
<fr:assertion name="fundgroup">
<fr:assertion name="funder_name">
European Union's Horizon 2020 Research and Innovation Program through Marie Sklodowska Curie
<fr:assertion name="funder_identifier">http://dx.doi.org/10.13039/501100000780</fr:assertion>
</fr:assertion>
<fr:assertion name="award_number">721624</fr:assertion>
</fr:assertion>
</fr:program>

Everitt, W. N., & Kalf, H. (2007). The Bessel differential equation and the Hankel transform. Journal of Computational and Applied Mathematics, 208(1), 3–19.

{
"title": "Functional single-cell genomics of human cytomegalovirus infection",
"issued": "2021-10-25",
"author": [
{"given": "Marco Y.", "family": "Hein"},
{"given": "Jonathan S.", "family": "Weissman", "ORCID": "http://orcid.org/0000-0003-2445-670X"}
]
}

Every matching task also has an output. For our purposes, this is almost exclusively zero or more matched identifiers. In the context of a specific matching task, output identifiers may be of a specific type (e.g. we might match to a ROR ID, and never to an ORCID ID). In some cases, there can be a certain target set as well (i.e. matching only to DataCite DOIs). The output identifiers can have different cardinality depending on the task, meaning that the matching task might allow for zero, one, or more identifiers as a result of matching to a single input.

A matching strategy defines how the matching is done. Multiple strategies can exist for a specific matching task. Compound strategies can run other strategies and combine their outcomes into a single result.

In some cases, we may also want the matching strategy to output a confidence score for each matched identifier. A confidence score represents the degree of certainty or likelihood that the matched identifier is correct, typically expressed as a value between 0 and 1. This score may help with post-processing or further interpretation of the results.

To summarise, the anatomy of the matching task can be diagrammed as follows:

How to specify a matching task

Whenever we plan the development or integration of a matching solution, it is good to begin by answering a few basic questions:

What problem do we plan to solve with our matching task? What would we call our matching task and how would we describe it?
What do we expect as the input for this matching task? Which input formats do we need to be able to accept? What information do we expect to find in this input?
What kind of identifiers should be output? Is there a target set of identifiers? Can our matching output zero/one/or multiple identifiers, and under what conditions might that occur?

These sound fairly simple, but the answers to these questions can be remarkably complex. Once one tries to apply these concepts to real-world problems, they might encounter several non-obvious challenges.

For example, one common concern is at what level we should define each matching task. Consider the following problems:

Matching bibliographic reference strings to DOIs. Example input:

Everitt, W. N., & Kalf, H. (2007). The Bessel differential equation and the Hankel transform. Journal of Computational and Applied Mathematics, 208(1), 3–19.

Matching structured bibliographic reference to DOIs. Example input:

{
volume: "208",
author: "Everitt",
journal-title: "J. Comput. Appl. Math.",
article-title: "The Bessel differential equation and the Hankel transform",
first-page: "3",
year: "2007",
issue: "1"
}

Are those discrete matching tasks (unstructured reference matching vs. structured reference matching), or are they the same task (reference matching) that can accept different types of inputs (unstructured or structured)?

Similarly, let’s compare the following tasks:

Matching affiliation strings to ROR IDs. Example input:

Department of Molecular Medicine, Sapporo Medical University, Sapporo 060-8556, Japan

Matching funder names to ROR IDs. Example input:

Alexander von Humboldt Foundation

Are these different matching tasks (affiliation matching vs. funder matching), or the same task with different inputs (organisation matching)?

Defining the boundaries of a matching task can also be difficult. Consider, for example, the need to obtain ROR IDs for organisations mentioned in the acknowledgements section of a full-text academic paper. To begin, one may first extract the acknowledgement section from the full text, then run something like a named entity recognition (NER) tool to isolate the organisation names from the extracted text, and finally match these names to ROR IDs. Is this entire process matching, with the input being the full text of a paper? Or perhaps matching starts with the acknowledgement section as the input? Instead, is it only the last phase, where we try to match the extracted name to the ROR ID, that constitutes the matching task, with the extraction phases being completely separate processes?

There are also important questions related to the expected behaviour of a matching strategy. Consider, for example, developing an affiliation matching strategy where we define our input as “an affiliation string”. What should happen when the strategy gets something else on the input, for example, song lyrics? Perhaps the strategy should simply return no matches, or an error, or we could say that in such a situation the behaviour is undefined and it simply doesn’t matter what is returned. But what should happen if in this input we have the lyrics of Street Life by Roxy Music, a song that mentions the names of a few universities that happen to have ROR IDs?

It is likewise important to consider what should happen if different parts of the input match to different identifiers, like in the following example:

Department of Haematology, Eastern Health and Monash University, Box Hill, Australia

Here, “Eastern Health” matches to https://ror.org/00vyyx863 and “Monash University” to https://ror.org/02bfwt286. Should the matching strategy return all the identifiers, one of them (if so, which one?), or nothing at all?

Similar questions arise when it is possible to match to multiple versions (or duplicates) in the target identifier set. This can happen, for example, in the context of bibliographic reference matching or preprint matching. Multiple matches may occur when there are different editions, reprints, or variations of the same publication in the target dataset, each with its own unique identifier.

If you are waiting for an answer to these questions, we unfortunately must disappoint you here. These can only be answered in the context of a specific problem, considering who the users are and what it is they need and expect.

Did you notice any other subtleties related to metadata matching and its concerns? Are there other non-obvious questions that should be considered when planning to develop or integrate metadata matching strategies? Let us know—we’d love to hear from you!

Metadata matching 101: what is it and why do we need it?

Dominika Tkaczyk — Thu, 16 May 2024 00:00:00 +0000

At Crossref and ROR, we develop and run processes that match metadata at scale, creating relationships between millions of entities in the scholarly record. Over the last few years, we’ve spent a lot of time diving into details about metadata matching strategies, evaluation, and integration. It is quite possibly our favourite thing to talk and write about! But sometimes it is good to step back and look at the problem from a wider perspective. In this blog, the first one in a series about metadata matching, we will cover the very basics of matching: what it is, how we do it, and why we devote so much effort to this problem.

What is metadata matching?

Would you be able to find the DOI for the work referenced in this citation?

Everitt, W. N., & Kalf, H. (2007). The Bessel differential equation and the Hankel transform. Journal of Computational and Applied Mathematics, 208(1), 3–19.

We bet you could! You might begin, for example, by pasting the whole citation, or only the title, into a search engine of your choice. This would probably return multiple results, which you would quickly skim. Then you might click on the links for a few of the top results, those that look promising. Some of the websites you visit might contain a DOI. Perhaps you would briefly compare the metadata provided on the website against what you see in the citation. If most of this information matches (see what we did there?), you would conclude that the DOI from that website is, in fact, the DOI for the cited paper.

Well done! You just performed metadata matching, specifically, bibliographic reference matching. Matching in general can be defined as the task or process of finding an identifier for an item based on its structured or unstructured “description” (in this case: finding a DOI of a cited article based on a citation string).

But matching doesn’t have to just be about citations and DOIs. There are many other instances of matching we can think of, for example:

finding the ROR ID for an organisation based on an affiliation string,
finding the ORCID ID for a researcher based on the person’s name and affiliation,
finding the ROR ID for a funder based on the acknowledgements section of a research paper,
finding the grant DOI based on an award number and a funder name.

Matching doesn’t have to be done manually. It is possible to develop fully automated strategies for metadata matching and employ them at scale. It is also possible to use a hybrid approach, where automated strategies assist users by providing suggestions.

Developing automated matching strategies is not a trivial task, and if we want to do it right, it takes a great deal of time and effort. This brings us to our next question: is it worth it?

Why do we need matching?

In short, metadata matching gives us a more complete picture of the research nexus by discovering missing relationships between various entities within and throughout the scholarly record:

These relationships are very powerful. They provide important context for any entity, whether it is a research output, a funder, a research institution, or an author. Imagine for a moment the scholarly record without any such relationships, where all bibliographic references, affiliations (institution names and addresses), and funding information (funder names and grant titles) are provided as unstructured strings only. In such a world, how would you calculate the number of times a particular research paper was cited? How would you get a list of research outputs supported by a specific funder? It would be incredibly challenging to navigate, summarise, and describe research activities, especially considering the scale. Thankfully, these and many other questions can be answered thanks to metadata matching that discovers relationships between entities in the scholarly record.

There are two primary ways we can use metadata matching in our workflows: as semi-automated tools that help users look up the appropriate identifiers or as fully automated processes that enrich the metadata in various scholarly databases.

The first approach is quite similar to the example we described at the beginning. If you are submitting scholarly metadata, for example of a new article to be published, you can use metadata matching to look up identifiers for the various entities and include these identifiers in the submission. For example, with the help of metadata matching, instead of submitting citation strings, you could provide the DOIs for works cited in the paper and instead of the name and address of your organisation, you could provide its ROR ID. To make this easier for people, metadata submission systems and applications sometimes integrate metadata matching tools into user interfaces.

The second approach allows large, existing sources of scholarly metadata to be enriched with identifiers in a fully automated way. For example, we can match affiliation strings to ROR IDs using a combination of machine learning models and ROR’s default matching service, effectively adding more relationships between people and organisations. We can also compare journal articles and preprints metadata in the Crossref database by calculating similarity scores for titles, authors, and years of publication to match them with each other and provide more relationships between preprints and journal articles. This automated enrichment can be done at any point in time, even after research outputs have been formally published.

There are fundamental differences between these two approaches. The first is done under the supervision of a user, and for the second, the matching strategy makes all the decisions autonomously. As a result, the first approach will typically (although not always) result in better quality matches. By contrast, the second approach is much faster, generally less expensive, and scales to even very large data sources.

In the end, no matter what approach is used, the goal is to achieve a more complete accounting of the relationships between entities in the scholarly record.

This blog is the first one in a series about metadata matching. In the coming weeks, we will cover more detail about the product features related to metadata matching, explain why metadata matching is not a trivial problem, and share how we can develop, assess, compare, and choose matching strategies. Stay tuned!

2024 public data file now available, featuring new experimental formats

Patrick Polischuk — Tue, 14 May 2024 00:00:00 +0000

This year’s public data file is now available, featuring over 156 million metadata records deposited with Crossref through the end of April 2024 from over 19,000 members. A full breakdown of Crossref metadata statistics is available here.

Like last year, you can download all of these records in one go via Academic Torrents or directly from Amazon S3 via the “requester pays” method.

Download the file: The torrent download can be initiated here. Instructions for downloading via the “requester pays” method, along with other tips for using these files, can be found on the “Tips for working with Crossref public data files and Plus snapshots” page.

In January, Martin Eve announced that we had been experimenting with alternative file formats meant to make our public data files easier to use by broader audiences. This year’s file will be published alongside the tools that can be used on the public data file to produce two experimental formats: JSON-lines and SQLite (and a bonus Rust version). You can read more about our thinking behind this work in Martin’s blog post, and we are keen to hear your thoughts on these alternatives.

Our annual public data file is meant to facilitate individuals and organisations interested in working with the entirety of our metadata corpus. Starting with the majority of our metadata records in one file should be much easier than starting from scratch with our API, but because Crossref metadata is always openly available, you can use the API to keep your local copy up to date with new and updated records.

If you’re curious about what you’ll get with the public data file, we’ve also published a sample version so that you can take a peek before committing to downloading the ~212 gb file. This file includes a random sample of JSON files and is available exclusively via torrent here.

We hope you find this public data file useful. Should you have any questions about how to access or use the file, please see the tips below, or share your questions below (you will be redirected to our community forum).

Tips for using the torrent and retrieving incremental updates

Use the public data file if you want all Crossref metadata records. Everyone is welcome to the metadata, but it will be much faster for you and much easier on our APIs to get so many records in one file. Here are some tips on how to work with the file.
Use the REST API to incrementally add new and updated records once you have the initial file. Here is how to get started (and avoid getting blocked in your enthusiasm to use all this great metadata!).
While bibliographic metadata is generally required, because lots of metadata is optional, records will vary in quality and completeness.

Questions, comments, and feedback are welcome at support@crossref.org.

Common views and questions about metadata across Africa

Johanssen Obanda — Wed, 24 Apr 2024 00:00:00 +0000

This past year has been a captivating journey of immersion within the Crossref community, a mix of online interactions and meaningful in-person experiences. From the engaging Sustainability Research and Innovation Conference in Port Elizabeth, South Africa, to the impactful webinars conducted globally, this has been more than just a professional endeavour; it has been a personal exploration of collaboration, insights, and a shared commitment to pushing the boundaries of scholarly communication.

Working collaboratively with research funders and research organisations

Cocreation activity in smaller groups at the SRI conference.

The adventure began with a significant in-person event, the Sustainability Research and Innovation Conference. In the coastal city of Port Elizabeth, South Africa, I had the honour of hosting a parallel co-creation session titled “Connecting Science to Society: A Network Approach to Improving Science Communication in the Global South.” The co-creation session addressed research discoverability and accessibility among early-career researchers. Apart from some immediate feedback from the researchers in the room about how they might use co-creation beyond the conference to improve their research experience and outcome, I also had conversations with research funders from the Belmont Forum, Future Earth, and National Research Foundation - South Africa and the National Research Foundation - Mozambique about connecting their grants and grantees with their published outputs referencing Crossref’s Open Funder Registry and research grants registration. A different side conversation was about a community organisation in Botswana that is interested in registering patents with Crossref for proper referencing and protecting the intellectual property of their research on the indigenous communities’ innovations and the associated published work. These conversations are ongoing, unveiling a new understanding of unique needs and opportunities to pursue with research funders and research organisations working on indigenous knowledge and innovations.

Learning from organisations in GEM-eligible countries

The journey extended globally through a series of webinars conducted in Bangladesh, Tanzania, Nepal, and Ghana. Collaborating with dedicated Ambassadors and my colleagues leading the Global Equitable Membership (GEM) program, we witnessed an increase in Crossref membership from the GEM countries and initial metadata registration. The GEM Program offers relief from both Crossref membership and Crossref content registration fees for organisations in the least economically advantaged countries in the world, based on the World Bank’s IDA list. Susan, in her blog post, “The GEM Program: Year One”, elaborated on the significance of these efforts and their impact on fostering equitable access to scholarly resources and communication through the expansion of Crossref’s membership base in underrepresented regions, such as Bangladesh, Tanzania, Nepal, and Ghana. Specific concerns encountered while presenting the GEM program included feedback expressing reservations about the program’s approach, particularly in deciding on eligible countries, and advocating eligibility for the program to be extended to all the non-GEM countries in Africa. Additionally, a conversation with some organisations brought up concerns regarding the program’s sustainability, with inquiries about whether GEM was merely a free trial or freemium service, and seeking assurances against future fees. The audience found these sessions helpful, acknowledging that joining fees were no longer going to be a barrier, yet questions about the program’s longevity brought out the need for sustained support.

Discussing how The Research Nexus can support the community

My journey then led me to Makerere University in Uganda for the Consortium of Uganda University Libraries (CUUL 2023) conference and the Forum for Open Research in MENA (FORM 2023) in Abu Dhabi. In Uganda, I noticed the synergy between university libraries, institutional repositories, and the research and education network service provider formed a consortium that played a crucial role in bridging the digital gap and supporting the adoption of open infrastructure. The event was mainly attended by librarians from different universities in Uganda. Most of those I connected with needed more information about Crossref and had questions about how Crossref DOIs are different from ARKs, which they commonly use in their publishing workflows. At FORM 2023, in my presentation titled, “The Research Nexus: A Rich and Reusable Open Network of Relationships in the Scholarly Record,” I shared Crossref’s vision for a connected research ecosystem with the audience that comprised of researchers, research administrators, and funders, and a good number of big publishers like IEEE and Taylor & Francis. The Research Nexus seeks to reveal relationships beyond persistent identifiers, utilising rich metadata to connect various scholarly components. I also took the opportunity at both events to share about The Publishers Learning And Community Exchange (PLACE), an online forum promoting best practices in scholarly publishing. The goal was to show attendees how they can actively contribute to and benefit from this vision, fostering a robust and interconnected research community through Crossref’s open infrastructure.

Photo with Dr. Salwan Abdulateef, rossref Ambassador - Iraq

I enjoyed the opportunity to join the National Open Science Dialogue by TCC Africa, which provided crucial insights, emphasising the need for assessing awareness, implementing comprehensive policies, and fostering collaboration around Open Science. Higher education institutions were recognized as influencers in the global Open Science movement, while a call for an inclusive research environment was underscored through open access and data sharing. The dialogue emphasized a collective effort involving policymakers, educators, researchers, and institutions, focusing on inclusivity and collaboration to advance Open Science in East Africa.

Exploring how rich metadata can provide trust signals with members in Kenya

Reflecting on the Crossref Nairobi event that happened in February 2024, it was an enriching experience exploring key issues shaping scholarly publishing in Kenya. The discussions also touched on the role of metadata as a trust signal and a tool for the persistence of the scholarly record, particularly in regions where data protection challenges persist. This is exemplified by concerns raised during the event about the fear of data theft, misuse, or loss, especially in places with comparatively weaker data protection laws. The presence of robust metadata, particularly with detailed provenance information, becomes crucial in such contexts, as it enables better identification and handling of potential misuse. Thus, through effective metadata implementation and the persistence facilitated by identifiers, the management of data risks can be significantly improved.

The insights from existing Crossref members pointed out contextual challenges, regional differences, and the importance of effective post-publication processes. The conference served as a valuable platform for dialogue, emphasising the collective commitment to continuous improvement of scholarly communication in the country, and the need for continuous awareness and training on making the most of Crossref services. The roundtable discussions during the Crossmark service consultation brought to light various reflections and considerations regarding post-publication changes in publishing workflows. The Crossmark service was a new discovery for most participants, with potential value recognized in facilitating current updates on articles. However, there are existing barriers such as a lack of awareness and technical expertise, suggesting the need for further education to facilitate adoption. Overall, the consultation provided a platform for introspection and exploration of avenues for improving post-publication practices in scholarly publishing.

Crossref Nairobi group photo

We organised the Crossref Nairobi event with the help of colleagues from the community team and local Ambassadors, Mercury Shitindo of Kenya, Baraka Ngussa of Tanzania and our Board Members in Kenya, Oscar Donde. It was the first time I saw both my colleagues and Ambassadors in action and working closely together - making presentations and accommodating last-minute facilitation changes to the program. Compared to attending or speaking at an event, organising one was a unique experience requiring a lot of planning in advance for logistics and the event program, identifying and keeping in touch with important stakeholders, ushering guests and being on standby for any matters that come up about the event. All of that went very well thanks to the team on the ground and cooperative participants.

Exploring the role of open infrastructure for African universities

Attending the recent WACREN 2024 conference was an eye-opening experience, unfolding the role of open infrastructure in addressing challenges faced by African universities. A focus on open access systems and advocacy for decolonizing knowledge were voiced too, including challenges of affordability of DOIs and questions of local ownership amidst global initiatives. Global persistent identifier providers, including ORCID and DataCite too, had a presence at the conference, alongside passionate advocates for more locally managed, decentralised infrastructure. These are concerns that Crossref needs to understand better, as we seek to find effective ways of supporting equitable participation in the Research Nexus. The conference resonated with a call for continued work in fostering accessibility, sharing, and leveraging resources to accelerate research and innovation in Africa.

Photo with our Ambassadors from West Africa at WACREN 2024 event: Blessing Abumere - Nigeria, Audrey Kenni Nganmeni - Cameroon, Richard Lamptey - Ghana and Oumy Ndiaye - Senegal.

Conversations with Crossref Ambassadors brought about a shared narrative across universities in some African countries. These institutions are actively embracing digital shifts, setting up institutional repositories using platforms like DSpace and OJS. However, challenges persist, particularly in funding and technical capacity. It’s heartening to see how national and regional research and education networks step in to help in internet connectivity, opening up collaboration opportunities with other interoperable infrastructure, setting up repositories, providing hosting services and event managing content identifiers.

Deceptive publishing practices remain a shared concern, and we’ve had requests at these meetings for stricter inclusion criteria for membership of Crossref to ensure quality and trustworthiness of articles accessible through Crossref metadata.

We’ve explained to those we’ve met that Crossref doesn’t (and can’t) assess the quality of content or the integrity of the research process. We don’t have the people or the skills, and it isn’t our mission to be the gatekeepers of research quality. A DOI record is just an indication that something was published, it isn’t an indication of quality.

However, we do still have a vital role in preserving the integrity of the scholarly record. We provide the infrastructure which enables those who produce scholarly outputs to provide metadata (effectively evidence) about how they ensure the quality of content and how the outputs fit into the scholarly record. The scholarly record - that network of published outputs, inputs, relationships and contexts - is captured through the metadata records that our members register with us, and that we then distribute freely and openly through our API. The richer and more comprehensive Crossref records are, the more context there is for our members and for the whole scholarly research ecosystem to make their own decisions around trustworthiness. Blocking access to the infrastructure creates gaps in the scholarly record, but also potentially blocks legitimate newcomers.

“Crossref is focused on enriching metadata to provide more and better trust signals while keeping barriers to membership and participation as low as possible to enable an inclusive scholarly record.” Read more about Crossref’s role in preserving the integrity of the Scholarly record in the blog post by Amanda Bartell.

While the landscape of digital scholarly publication witnesses significant strides, a crucial need persists, the importance of preserving and interconnecting metadata to the global scholarly record. It’s not just about discoverability, a theme resonating strongly within the community, but about enabling reproducibility, upholding research and editorial integrity, and facilitating reporting and assessment.

The path forward

As I reflect on this year of immersing myself within the Crossref community, building awareness in new communities, and learning more about the different perceptions across the region, it feels like a personal progression of growth and discovery. From the captivating in-person moments to the global webinars and collaborative efforts to address challenges in scholarly communication, this journey is not just a professional pursuit; it’s a personal exploration. The path forward involves continued support, intensified awareness-building, and sustained dialogue, ensuring that the scholarly ecosystem continues to thrive, evolve, and leave a lasting impact.

Subject codes, incomplete and unreliable, have got to go

Patrick Polischuk — Wed, 13 Mar 2024 00:00:00 +0000

Subject classifications have been available via the REST API for many years but have not been complete or reliable from the start and will soon be deprecated. dfdfd

The subject metadata element was born out of a Labs experiment intended to enrich the metadata returned via Crossref Metadata Search with All Subject Journal Classification codes from Scopus. This feature was developed when the REST API was still fairly new, and we now recognize that the initial implementation worked its way into the service prematurely.

While subject classifications in Crossref metadata could be very useful, the current implementation in the REST API is problematic for three primary reasons:

They are misleadingly exposed in the API as a property of the work, when in fact they are a property of the container (e.g. a journal or conference proceeding). Just because a journal’s broad topic category is “X” doesn’t mean that a particular article in the journal is about “X.”

Existing works may have outdated subjects. Originally, subject codes were not updated periodically. However, subjects exposed in the /journals route are now updated once a day. Those exposed via the /works endpoint are indexed along with works, and so when a new subject list is ingested, new DOIs start getting new subjects, but existing works may have outdated subjects. We don’t have a mechanism for forcing updates when incorrect subject values are returned via the REST API, so this data can be stale and incorrect.

They are not applied to everything. This is because the Scopus list does not cover all the journals that Crossref has (conversely, the Scopus list contains some journals Crossref does not have), and does not contain other container types.

The Labs team investigated options for improving subject classification coverage but ultimately concluded that there are insufficient solutions to the coverage problem. For more, please see Esha Datta’s findings published at Force11’s Upstream: https://doi.org/10.54900/n6dnt-xpq48

Where does that leave us? Rather than continuing to supply unreliable and misleading subject category metadata, we will be deprecating this feature in the coming weeks. To minimize disruption and avoid breaking changes at this time, we will be removing this data from our index, so the subject element will simply be empty. We may remove the subject element in the future.

We know that the community’s desire for subject-based analysis of metadata is very strong, and we have supported efforts to establish a multidisciplinary taxonomy. Inaccurate codes in the meantime do not help but actually hinder these efforts, giving the false impression that they are correct.

We aim to deprecate the subject codes in April of this year.

Please let us know if you have any questions or concerns by leaving a comment below, which will start a thread in our community forum.

Frequently asked questions

Q. Will the subject field continue to be available and functional?
A. The subject metadata element will continue to be included in the JSON response but will not return any values.

Q. Will new subject codes be added in the future?
A. We do not have any current plans to add new subject codes in the future.

Q. I received a notification about this, but we don’t use subject codes. Do I need to do anything?
A. No, if you do not currently use the subject element, you do not need to do anything about this change.

Q. I noticed that wrong or inaccurate subject codes were assigned to my works. Is this a solution?
A. Yes. Until we can identify an accurate and sustainable system for assigning subject codes to Crossref metadata records, we want to stop assigning inaccurate subject codes and remove all existing assignments.

RORing ahead: using ROR in place of the Open Funder Registry

Rachael Lammey — Tue, 30 Jan 2024 00:00:00 +0000

A few months ago we announced our plan to deprecate our support for the Open Funder Registry in favour of using the ROR Registry to support both affiliation and funder use cases. The feedback we’ve had from the community has been positive and supports our members, service providers and metadata users who are already starting to move in this direction.

We wanted to provide an update on work that’s underway to make this transition happen, and how you can get involved in working together with us on this.

Overall, we are building more comprehensive support for ROR into Crossref’s services. Some of this work is specifically to support using ROR to identify funding organisations in place of funder registry IDs. We have a number of parallel, complementary projects underway to support different elements of this work:

We are evolving our metadata schema so that we can collect ROR IDs in places where we currently support the collection of Funder IDs.
We are analysing the coverage of Funder ID to ROR ID mappings and testing the way we expose them in our APIs.
We are developing new matching strategies to match text strings to ROR IDs.

1. Schema updates

Everything flows from being able to get ROR IDs into the Crossref metadata!

We are evolving our metadata schema so that we can collect ROR IDs in places where we already support the collection of Funder IDs – for instance, in the funding section of the metadata for works and in the funder section for grants.

We’re working with members and service providers so that they can try sending us this data via a pipeline our Labs team has built to test schema updates before they go live. We are actively recruiting members to help us test our new pipeline by providing sample XML for registration. Planned metadata inputs and outputs are detailed in Including ROR as a funder identifier in your metadata (metadata prototyping instructions), we’d encourage you to provide feedback on these in the document, ideally in the next two weeks. We’re aiming to release an updated schema that supports these changes in Q1 2024.

2. Modelling ROR ID/Funder ID mappings in our metadata model

We have integrated the ROR registry into our evolving metadata model, and we have started work to integrate the Funder Registry. The aim is to create more flexibility in how Crossref’s metadata can be supplemented and queried, and give more clarity as to which party asserted or created a metadata element.

We’re working on an early iteration of how the model handles ROR IDs, funder IDs and their equivalencies. Once we have something to share, we’ll welcome community feedback on this approach and on the metadata model in general.

3. Developing new matching strategies to match text strings to ROR IDs

Ideally, everyone would always use persistent identifiers to exchange information about contributor and awardee affiliations, organisations related to works, as well as funders supporting the research. In practice, this information is often exchanged as data without identifiers, such as affiliation strings (e.g. “University of Virginia, Charlottesville, VA”), funder names, or even funding acknowledgements (e.g. “Funding and support generously provided by the Ford Foundation”). In such situations, a good metadata matching strategy can help map these to persistent identifiers.

Currently, we are focused on developing reliable strategies for matching affiliation strings to ROR IDs. In the future, we will adapt the strategies to support funder names and funding acknowledgements as well. All the strategies will be rigorously evaluated using real-life data. We will make the strategies, as well as the evaluation datasets and evaluation results, publicly available for anyone to use. If you are interested in collaborating on the development or the evaluation of the matching strategies, please get in touch!

In the future, we might also apply some of the new matching strategies at Crossref, to the metadata our members send us. This would allow us to insert matched identifiers to the metadata to better connect organisations with other items in the scholarly record. We already have a process that matches the names of funders supporting research against the Funder Registry and enriches the metadata with matched Funder Registry IDs. Developing and evaluating reliable matching strategies will allow us to modify this process to use ROR IDs instead, and extend it to support other use cases, such as contributor affiliations.

What will the transition mean for you?

We do recommend that you begin looking at what it will take to integrate ROR into your systems and workflows for identifying funders. Talk to your service providers about this to ready them for this change. To reiterate the point from the earlier post, in the short term, and even in the medium term, Funder IDs aren’t going away and the Funder IDs will continue to resolve – they are persistent, after all. Eventually, however, the Funder Registry will cease to be updated, so any new funders will only be registrable in Crossref metadata with ROR IDs. Legacy Funder IDs and their mapping to ROR IDs will be maintained, so if Crossref members submit a legacy Funder ID, it will get mapped to a ROR ID automatically. Note, too, that Crossref is committed to maintaining the current funder API endpoints until ROR IDs become the predominant identifier for newly registered content. We also know that there are questions that we’ll want to tackle with the community as we all make progress, some we know and some we don’t know. With that in mind:

Tell us what you need!

We want to hear from you! We have set up several channels of communication meant to ensure that you can tell both ROR and Crossref what will make this transition easier for you and that you can get answers to your questions.

First, we are conducting a series of Open Funder Registry user interviews designed to deepen our understanding of where Funder IDs are being used in workflows and systems. Write community@ror.org if you’d like to participate in these interviews to show and tell us how you’re using Funder IDs.

Second, in 2024, we will be running a follow-up to the funding data workshop we ran in June 2023. Please get in touch if your organisation would be interested in participating in the discussion.

Increasing Crossref Data Reusability With Format Experiments

Martin Eve — Fri, 19 Jan 2024 00:00:00 +0000

Every year, Crossref releases a full public data file of all of our metadata. This is partly a commitment to POSI and partly just what we do. We want the community to re-use our metadata and to find interesting ends to which they can be put!

However, we have also recognized, for some time, that 170GB of compressed .tar.gz files, spread over 27,000 items, is not the easiest of formats with which to work. For instance, there’s no indexing capacity on these files, meaning that it is virtually impossible simply to pull out the record for a DOI. Decompressing the .tar.gz files takes a good three hours or more even on high-end hardware, without any additional processing.

To that end, the Crossref Labs team has been experimenting with different formats for trial release that might allow us to reach broader audiences, including those who have not previously worked with our metadata files. The two new formats, alongside the existing data file format, with which we have been experimenting, are JSON lines and SQLite.

JSON-L

The first format with which we’ve been experimenting is JSON-L (JSON lines). With one JSON entry per line, as opposed to one giant JSON file/block, JSON-L lends itself to better parallelisation in systems such as SPARC, because the data can easily be partitioned.

This data format also has the benefit of being appendable, one line at a time. Unlike conventional JSON, which requires the entire structure to be parsed in-memory before an append is possible, JSON-L can simply be written to and updated. It’s also possible to do multi-threaded write operations on the file, without each thread having to parse the entire JSON structure and then sync with other threads.

In our experiments, JSON-L came with substantial parallelisation benefits. Our routines to calculate citation counts can be completed in ~20-25 minutes. Calculating the number of resolutions per container title takes less than half an hour.

SQLite

SQLite is a library written in C with client bindings for Python, Java, C#, and many other languages that produces an on-disk, portable, single-file SQL database. You can produce the SQLite file using our openly available Rust program, rustsqlitepacker. We also have a Python script that can produce the final SQLite file, for those happier working in this language.

The resultant SQLite file is approximately 900GB in size, so it requires quite a lot of free disk space to create in the first place (alongside storage of the data file that is needed to build it). However, queries are snappy when looking up by DOI and other indexes can be constructed (the indexing part of the procedure takes about 1.5 hours per field).

The database structure, at present, is the bare minimum that will work. It contains a list of fields for searching/indexing – DOI, URL, member, prefix, type, created, and deposited – and a metadata field that contains the JSON response that would be returned by the API for this value.

This allows for the processing and extraction of individual JSON elements using SQLite’s built-in json_extract method. For example, to get just the title of an item, you can use:

SELECT json_extract(metadata, ‘$.title’) from works WHERE doi=“10.1080/10436928.2020.1709713”;

The balance that we have had to strike here is between flattening the JSON so that more fields are indexable and searchable, as against the trade-off in time and processing that this takes to create the database in the first place. The first draft version of our experiment was wildly ambitious in flattening all the records and using an Object Relation Mapper (ORM) to present Python models of the database. Like painting the Forth Bridge, this initial attempt would not finish in any sane length of time. Indeed, by the time we’d created this year’s data file, we’d need to begin work on the next.

What are the anticipated use cases here? When people need to do an offline metadata search on an embedded device, for instance, the portability and indexed lookup of the SQLite database can be very appealing. One of our team has even got the database running on a Raspberry Pi 5. You can also load the database into Datasette if you want to explore it visually.

Where do we go from here with this? It would be good to flatten a few more fields, but we would welcome feedback on use cases that we haven’t anticipated for SQLite and we’d love to hear whether this is already too unwieldy (at 900GB).

Data Files

As usual, we will be releasing the annual data file in the next few months. As an experiment this year, we will also be releasing the tools that can be used on that file to produce these alternative file formats. We will consider releasing the final data files for each of these formats, too.

What we would like to hear from the community is whether there are other data file formats that you might wish to use. Are there use cases that we haven’t anticipated? What would you ideally like in terms of file formats?

Open Funder Registry to transition into Research Organization Registry (ROR)

Amanda French — Thu, 07 Sep 2023 00:00:00 +0000

There is some overlap between the Open Funder Registry and the Research Organization Registry (ROR), and funders and publishers have been asking us whether they should use Open Funder Registry IDs or ROR IDs to identify funders when they appear in both registries. We aim to merge the two registries over time. We will ensure Crossref members can use ROR to simplify persistent identifier integrations, to register better metadata, and to help connect research outputs to research funders.

Just yesterday, we published a summary of a recent workshop between funders and publishers on funding metadata workflows that we convened with the Dutch Research Council (NWO) and Sesame Open Science. As the report notes, “open funding metadata is arguably the next big thing” [in Open Science]. That being the case, we think this is the ideal time to strengthen our support of open funding metadata by beginning the transition to ROR.

Comparing the features of ROR and the Open Funder Registry

Let’s look at some of the similarities and differences between the two registries, including their history, features, scope, and usage, since there are important nuances and distinctions that are helpful to understand.

Overview

ROR	Open Funder Registry
Launched in 2019	Launched in 2013
Primary use case is contributor affiliation	Primary use case is funding acknowledgement
105k+ records	35k+ records
CC0 data	CC0 data
REST API	REST API
Free to use	Free to use
Entire registry downloadable as JSON and CSV	Entire registry downloadable as RDF; funder names and IDs downloadable as CSV
Records contain mappings to other IDs	Records do not contain mappings to other IDs
few organisation relationships and hierarchy	multiple organisation relationships and hierarchy
organisation level with no funding programs/schemes	organisation level with some funding programs/schemes
8 organisation types	2 funder types, 8 funder subtypes
Open source code and multiple open-source tools available	Open source code
Web-based registry search	Web-based search for works in Crossref associated with each Open Funder Registry ID
Web-based landing pages for each ROR record	JSON landing pages for each Open Funder Registry record
Updated monthly	Updated bimonthly
Public curation process	Private curation process
Anyone can request changes and additions	Anyone can request changes and additions
Stable financial support (Crossref, DataCite, CDL)	Stable financial support (Crossref, Elsevier)
Beginning to be supported in funding and publishing workflows	Well supported in most funding and publishing workflows
Currently used by 260+ Crossref members ¹	Currently used by 2100+ Crossref members ²

History

The Open Funder Registry was launched as FundRef over a decade ago to enable the community to cite research funding and support and assert it within the scholarly record, acknowledging the organisations granting their support. Elsevier generously donated the seed data for the Open Funder Registry and has managed its curation for the last ten years, while we have maintained the technical operations and promoted community adoption of the Open Funder Registry.

The Research Organization Registry (ROR) was introduced in 2019 by the California Digital Library, DataCite, and Crossref to enable the community to cite contributor affiliations and assert them within the scholarly record, acknowledging the organisations that housed or performed the research. Digital Science generously donated the seed data for the Research Organization Registry from its Global Research Identifier Database (GRID) initiative, and Crossref, DataCite, and the California Digital Library have contributed labour and resources to turn ROR into a mature, independent, freely available service.

Scope

One key difference between the registries is that ROR has always included funding organisations, and ROR records have always included mappings to Funder IDs where available, while the reverse is not true: the Open Funder Registry includes only funding organisations, not other kinds of organisations, and Open Funder Registry records do not currently include mappings to ROR IDs or other identifiers. It therefore makes sense to expand our initial contributor affiliation use case for ROR to include the identification of organisations that fund and support research.

Usage

More Crossref members use Funder IDs than use ROR IDs, to be sure. You can see from the table above that the number of Crossref members using Funder IDs in Crossref records is higher by almost a factor of 10 than the number of Crossref members using ROR IDs in Crossref records. But note too that the current rate of adoption is far higher for ROR than it is for the Open Funder Registry. Since January of 2022, we’ve seen a gratifying number of publishers and service providers beginning to use ROR identifiers for contributor affiliations in Crossref. In the last year, the number of Crossref members depositing ROR IDs has increased by 356%, while the number depositing Funder IDs has increased only by 12%. As evidenced by its ballooning API traffic, too, with more than 20 million requests last month,³ ROR is clearly being used by many scholarly research systems for many purposes. The more systems that use an identifier, the more valuable that identifier becomes as a vehicle for exchanging information.

ROR’s primary use case is to identify contributor affiliations and is already being used by funders. Nineteen funding organisations are depositing ROR IDs in their grant records with Crossref to denote principal investigator affiliations,⁴ and, following a meeting of the our Funder Advisory Group last month, all eighty funder members are primed to start using ROR IDs to identify themselves in grant records.

Tools and services

Both the Open Funder Registry and ROR have open data and open source code, but we think that our suite of free and open source utilities for ROR gives it an advantage. We know that publishers and their service providers have ongoing challenges in collecting and matching funding information from authors and in validating Funder IDs. With our extensive ROR toolkit, publishers and their technology providers who adopt ROR will be in a better position to improve the accuracy of funding acknowledgements in metadata, which can in turn enable the development of reliable analytics, tools, and services for funders, regulators, research facilities, and the public.

Crossref has built tools based on OpenRefine for both the Open Funder Registry and ROR: the Open Funder Registry Reconciliation Service and the ROR Reconciler are both useful ways to clean messy data. ROR, however, also offers a much-used API endpoint that helps match organisation names to ROR IDs, and several third parties have also developed and shared open source matching tools and services for ROR. Crossref is also collaborating on new strategies for affiliation matching that will improve connections for funding acknowledgements.

Community engagement models

The Open Funder Registry has been curated for over a decade through time and expertise generously donated by Elsevier and is community-governed by Crossref and it’s membership and board. ROR offers more transparent community involvement and is jointly governed by Crossref, DataCite, and the California Digital Library. ROR is openly curated and is aided by a global Curation Advisory Board of volunteers.

What will this mean for you?

The many organisations whose tools, services, and workflows have been architected to use Open Funder Registry (OFR) IDs will find this transition a challenge, and we don’t want to make light of that issue. Over the last ten years, we have encouraged the community to adopt Funder IDs, and the community has demonstrably recognized the benefits of doing so. Publishers have put a great deal of time, thought, and effort into collecting funder data and including it in Crossref metadata, and they have built internal reports and workflows around the Open Funder Registry. Crossref is committed to making the transition from the Open Funder Registry to the Research Organization Registry as simple as possible for the community.

If you are not already using the Open Funder Registry and are planning to begin standardizing funding data, we recommend that you use ROR to identify funders. If you are currently using the Open Funder Registry in your systems and workflows, don’t worry! In the medium term, Open Funder Registry IDs aren’t going away. Eventually, however, the Open Funder Registry may cease to be updated. Funder IDs and their mapping to ROR IDs will be maintained, so if Crossref members submit a Funder ID, it will get mapped to a ROR ID automatically. Note, too, that Crossref is committed to maintaining the current funder API endpoints.

In short, if you are already using Funder IDs, you can and should continue to do so. However, we do recommend that you begin looking at what it will take to integrate ROR into your systems and workflows for identifying funders as well as affiliations.

We face challenges in this transition, too. Of these, we think the largest will be (1) completing the reconciliation work involved in mapping Funder IDs to ROR IDs, and (2) updating Crossref’s schemas, APIs, and deposit tools to support ROR IDs in many the ways we currently support Funder IDs. We’ll discuss both of these challenges in future blog posts.

Tell us what you need?

We want to hear from you. You can use our Community Forum talk to us about the Crossref Open Funder Registry or contact ROR staff at Crossref via our request form. You can attend online Crossref events, including ROR-specific webinars to get updates from us and ask us your questions.

One of the major messages we’re already hearing from funders and publishers is expressed in yesterday’s post on open funding metadata: “While many concluded that there was still a long way to go to solve the many technical challenges related to funding metadata, attendees were unanimous on its importance.” We look forward to beginning this important work together.

Guide for funders to support FAIR workflows & enable research tracking

Helena Cousijn — Tue, 29 Aug 2023 00:00:00 +0000

Guide for funders to support FAIR workflows & enable research tracking

Published in August 2023 as part of the Implementing FAIR Workflows project, this Guide is a joint publication by three open scholarly infrastructure organisations—Crossref, DataCite, and ORCID. It introduces the role of persistent identifiers (PIDs) and open metadata in facilitating open and FAIR research, and walks funders through concrete ways to engage: committing resources, enacting congruent policies, and providing support around grant application, management, and reporting.

Strategists

Understand why funder participation in the PID and metadata infrastructure matters. Persistent identifiers and open metadata are what connect grants to the research outputs, people, and organisations they support—enabling assessment, discovery, and long-term stewardship of the record.

Decision-makers

See what policy and resourcing decisions align a funder with the wider ecosystem. The Guide sets out recommendations funders can adopt—from PID and metadata requirements in grant conditions, to committing to the community-owned infrastructure that maintains those records.

Practitioners

Apply the recommendations across grant application, management, and reporting. Concrete workflow guidance for embedding Crossref grant IDs, DataCite dataset/software IDs, and ORCID researcher IDs across the funder’s own systems and reporting pipelines.

What this guide covers

Why PIDs and metadata matter for funders—from grant lifecycle tracking to open-science impact assessment
The three infrastructure organisations’ complementary roles—Crossref for scholarly works and grant records, DataCite for data and software, ORCID for researchers and contributors
Policy recommendations funders can adopt to align with the wider open scholarly ecosystem
Practical workflow steps for grant application, management, and reporting
Community investment—how funders can support the community-owned infrastructure that makes end-to-end research tracking possible

About the Implementing FAIR Workflows project

Implementing FAIR Workflows is a three-year project delivering exemplar FAIR workflows in cognitive neuroscience research, built on the existing PID and metadata infrastructure. This Guide is one of the project’s community-facing outputs, developed by the DataCite project team in collaboration with Crossref and ORCID.

Read the guide

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Metadata connects the global community – summary of our Community update 2023

Kornelia Korzec — Fri, 12 May 2023 00:00:00 +0000

We were delighted to engage with over 200 community members in our latest Community update calls. We aimed to present a diverse selection of highlights on our progress and discuss your questions about participating in the Research Nexus. For those who didn’t get a chance to join us, I’ll briefly summarise the content of the sessions here and I invite you to join the conversations on the Community Forum.

You can take a look at the slides here and the recordings of the calls are available here.

TL;DR

The membership is growing, including that in the GEM programme countries, and we focus on adding new Sponsors in areas where we have insufficient coverage to support prospective members
The grant registration form is available for funders who don’t use XML, and we’re working to expand to other record types
The preview of the Relationship API endpoint is available – start exploring relationships between different records and record types, from citations to funding, and more
Usefulness of metadata records for inferring integrity of the content or publisher relies on all members of the community contributing to this effort. Crossref will continue to enrich our schema to capture new types of relevant information and to promote the best metadata practices.
Cited-by is now open for everyone to use 🎉 – no need for additional authorisation steps – Registering your references will have even greater impact now!
The Labs participation report is available and it’s been a hit. Please note that this tool is still underdevelopment – new functionalities can be added but there might also be bugs that we are yet to resolve, so don’t hold off with feedback.
We’ve received close to 1,000 responses in our first ever Metadata Priorities Survey. It’s still open until 18th of May and we encourage all members to take it. So far we’ve learnt that majority of our respondents are keen to deposit as much metadata as possible – and some would like to register more than we currently enable.

Metadata completeness and integrity

A key theme of the call was encouraging greater participation in the Research Nexus and the importance of complete metadata. One particular benefit of a rich and transparent metadata network is the opportunity to infer judgments on the integrity of the scholarly record (ISR). Amanda Bartell, Head of Member Experience, highlighted that the community agrees that availability of information about relationships between research outputs, institutions and other elements of the scholarly ecosystem together provide essential context for deciding about trustworthiness of organisations and their published content. Conversely, it can make it harder for parties to pass off information as trustworthy when that context is missing. Amanda summarised community feedback related to Crossref’s role in the integrity of the scholarly record in her recent blog post.

Our members can contribute to that rich network of relationships by curating their metadata and providing contextual information – especially the highly sought for elements highlighted in the presentation.

Our community

Since LIVE22, we have had 1,130 new members join us. That includes 51 organisations from countries included in our Global Equitable Membership (GEM) programme. You can find out more in the latest news about the programme on our Community Forum from Susan Collins, Community Engagement Manager.

We see great opportunities with enriching our metadata corpus with works carried out in some of the least economically-advantaged regions of the world. Registering their content with us will increase its discoverability for the global scholarship, while adding important relationships into the Research Nexus. We’re glad at the new members joining us under the auspices of the Global Equitable Membership (GEM) programme and we’re reaching out to existing and new communities with our Ambassadors, to encourage more metadata registrations.

Our Sponsors and Ambassadors, alongside our Outreach and Membership Team, support members to participate as effectively as possible in the Research Nexus. We’re delighted to see both programmes growing, with eight new Sponsors and seven new Ambassadors having joined us since October.

Simultaneously, we’re working with like-minded organisations to provide useful resources for the growing and changing scholarly communications community. The recent launch of the online forum for new publishers seeking to learn about best practices in the industry, The PLACE, is another way in which we hope to support wider participation in the Research Nexus, and promote open and sustainable practices.

With our growing community, there’s always interest in We have planned a webinar later this month to provide an overview of Crossref – including the members benefits and obligations, and how to use our services.

Service news

References metadata is essential for connecting works with one another. It enables provision of citation information, aids discoverability for researchers, as well as assessment and evaluation for institutions and funders. It’s almost a year since all the references metadata deposited with Crossref has been made openly available. At the moment, 52.0% of journal articles, and 44.5% of all works have references. Martyn Rittman, Product Manager for the Cited-by service says “It’s not bad, but we can do better!”

With three different mechanisms for doing it available to our members, we hope that all have a suitable tool to fit with their needs. You can register references with XML via HTTPS POST (structured or unstructured), with the dedicated OJS Plugin if you’re an OJS user, or with our Simple Text Query (unstructured text) – this is especially relevant to the Web Deposit Form users. We find that journal articles with deposited references seem to be cited more than those without, and by a lot: 21.8 vs. 6.1 incoming citations on average!

We have now made our Cited-by service open to all. To realise its full benefit, it is essential to register your references.

There were concerns in the community about references ‘lost’ as part of supplementary material that may not be registered in its own right. Colleagues advised that if the data has an identifier, such as a DataCite DOI, you can add a relationship to say that it’s supplementary material (see https://www.crossref.org/documentation/schema-library/markup-guide-metadata-segments/relationships/) or add them as a reference. Martyn is curious to hear from others in the community on this topic. There is an increasing focus on data citations and we’d like to see how we can better support them.

Many members have questions related to plans for replacing Metadata Manager. Rachael Lammey, Director of Product, explained that we’re working on broadening our new Grant Registration Form to include more record types over the course of 2023. It has a few advantages over the current Web Deposit Form. It allows you to save a local copy once you first register a piece of content. It makes updating your records easier, as you can drop that file onto the form to add the metadata so that you can update it and redeposit rather than having to fill out the information all over again, and we have started adding automatic lookup fields to help users populate information on affiliations using ROR IDs more accurately. We will keep you posted on the progress with new developments and ask for beta testers for new record types as they are added.

Metadata information about individual work is not as useful as the opportunity to interrogate the relationships between works and within the global scholarly output. [The preview of the Relationship API endpoint](https://community.crossref.org/t/relationships-are-here/3523, modest as it is at this stage – with only 1% of our relationship metadata included (or 10 mln relationships) – offers a powerful demonstration of the way in which metadata contextualises research outputs within the entangled network of ever-progressing scholarship.

We’ve also mentioned the recent transition of our website to GitLab, which allows everyone to contribute by creating merge requests and issues. Through this open collaboration, which supports our commitment to meet the Principles of Open Scholarly Infrastructure, we aim to cultivate a sense of ownership among contributors and make our information and documentation more useful and efficient for everyone.

Labs participation report

For organisations who wish to keep a close eye on their metadata – to understand what they deposit, how that compares with other members, and what could be improved, can start using our Lab participation reports. We encourage you to test this not-yet-finished tool and let us know your feedback. Participants at our updates found it very informative, with the opportunity to preview contents of recent deposits, see the participation breakdowns by a prefix, and improved data visualisation. We had questions about how data citation counts are generated in the report. Martyn Rittman explained that: “This is a prototype and that’s one of the issues we need to tidy up! We know via Event Data and our Scholix endpoint what is a dataset, but that hasn’t yet been incorporated to the Labs Reports”. There was also a suggestion of enabling export of simple lists of all member’s DOIs with respective URLs from the report and the team might look into that. Yet, lists of DOIs missing specific metadata types are already downloadable.

To learn more about the reports, try them out, and to provide feedback, please take a look at the information shared recently by Paul Davis, Tech Support Specialist & R&D Support Analyst.

Metadata priorities

Patricia Feeney, Head of Metadata, shared some updates about the current metadata corpus registered with Crossref, and some recent trends.

She then went on to summarise some preliminary results of our ongoing metadata priorities survey, which all members are encouraged to take part in by 18th of May. So far, we’ve received close to 1,000 responses. We’ve learnt that majority of our respondents are keen to deposit as much metadata as possible – and some would like to register more than we currently enable. Close to a half of the respondents who did not express an interest in sharing all metadata are still interested to learn more about the value of their metadata.

She then went on to summarise some preliminary results of our ongoing metadata priorities survey, which all members are encouraged to take part in by 18th of May. So far, We’ve received close to 1,000 responses. We’ve learnt that majority of our respondents are keen to deposit as much metadata as possible – and some would like to register more than we currently enable. However, close to a half of the respondents are interested to learn more about the value of their metadata.

The survey consults our members about their preferences for developing any of the potential projects under consideration:

Contributor IDs
Contributor roles/ CRediT
Alternate names
Multilingual metadata
Expand abstract support
Citation types (content)
Conference event IDs

It appears that support for citation types is the strongest among our respondents, while very polarised views have been shared about multilingual metadata and expanding support for abstracts. Among other suggestions, we received a lot of comments related to keywords. Overall, support for all projects was strong.

The verdicts are not in yet – still time to respond to the survey and make your metadata priorities known!

Thank you and keep in touch

With much of the content shared ahead of the time through our Community Forum, the sessions were bubbling with questions and valuable comments from the community. We look forward to continuing the conversations asynchronously on the Community Forum. Please don’t hesitate to share your thoughts and ask further questions. We’d also love to hear suggestions for topics of the most interest for our future updates.

The more complete the metadata we collect together, the more connections in the ecosystem become transparent. This creates opportunities for discovery and collaborations, and greater insights about the scholarly process. Our community is growing in numbers, diversity, and technical capacity for building the Research Nexus together. We welcome your questions and suggestions of initiatives that support the fullest participation possible.

2023 public data file now available with new and improved retrieval options

Patrick Polischuk — Tue, 02 May 2023 00:00:00 +0000

We have some exciting news for fans of big batches of metadata: this year’s public data file is now available. Like in years past, we’ve wrapped up all of our metadata records into a single download for those who want to get started using all Crossref metadata records.

We’ve once again made this year’s public data file available via Academic Torrents, and in response to some feedback we’ve received from public data file users, we’ve taken a few additional steps to make accessing this 185 gb file a little easier.

First, we’re proactively hosting seeds in a few locations around the world to improve torrent download performance in terms of both speed and reliability.

And second, we’ve added an option to download this year’s public data file directly from Amazon S3 for a small transaction fee paid by the recipient, bypassing the need to use the torrent altogether. The fee just covers the AWS cost of the download. Instructions for downloading the public data file via the “Requester Pays” method are available on the “Tips for working with Crossref public data files and Plus snapshots” page.

The 2023 public data file features over 140 million metadata records deposited with Crossref through the end of March 2023, including over 76,000 grant records. Because Crossref metadata is always openly available, you can use our API to keep your local copy of our metadata corpus up to date with new and updated records.

In previous years, closed and limited references were removed from the public data file. Since we updated our membership terms to make all deposited references open in 2022, the 2023 public data file for the first time includes all references deposited with us.

We hope you find this public data file useful. Should you have any questions about how to access or use the file, please see the tips below, or bring your questions to our community forum.

Tips for using the torrent and retrieving incremental updates

Use the public data file if you want all Crossref metadata records. Everyone is welcome to the metadata, but it will be much faster for you and much easier on our APIs to get so many records in one file. Here are some tips on how to work with the file.
Use the REST API to incrementally add new and updated records once you have the initial file. Here is how to get started (and avoid getting blocked in your enthusiasm to use all this great metadata!).
While bibliographic metadata is generally required, because lots of metadata is optional, records will vary in quality and completeness.

Questions, comments, and feedback are welcome at support@crossref.org.

Start citing data now. Not later

Geoffrey Bilder — Thu, 23 Mar 2023 00:00:00 +0000

Recording data citations supports data reuse and aids research integrity and reproducibility. Crossref makes it easy for our members to submit data citations to support the scholarly record.

TL;DR

Citations are essential/core metadata that all members should submit for all articles, conference proceedings, preprints, and books. Submitting data citations to Crossref has long been possible. And it’s easy, you just need to:

Include data citations in the references section as you would for any other citation
Include a DOI or other persistent identifier for the data if it is available - just as you would for any other citation
Submit the references to Crossref through the content registration process as you would for any other record

And your data citations will flow through all the normal processes that Crossref applies to citations. And it will be distributed openly to the community (including DataCite!) via Crossref’s services and APIs. All data citations deposited with Crossref will be exposed in the (soon-to-be launched) Data Citation Corpus.

And then, you can sit back and congratulate yourself for making your publication more useful to researchers who want to be able to reuse the data underlying your publications.

Background

You might ask, “So if submitting Data Citations to Crossref has long been possible, why do you have to write this?”

Historically, authors did not cite data in the way they cited publications. Instead, they would often refer to the data in the main text of the article. This has made it hard to determine what data lay behind the research and/or access the data.

But the research community has increasingly recognized that data is a first-class research output and that we should treat it as such. In short, we should formally cite data.

But because citing data is a comparatively new practice, it has been subject to a lot of new analysis. And unsurprisingly, people analyzing data citation have discovered that there is a lot of nuance to citation of any kind.

There are lots of reasons for citing something. There are lots of internalized conventions for citing things. And there are different conventions for citation for different research objects. And SSH citation practice differs from STEM. And legal citation practices are different from scholarly citation practices. And citation practices even vary by subdiscipline and by journal.

Those who have been looking at what it means to “cite data” have naturally stumbled into a thicket of divergent practices - some of which are historical holdovers, some of which are stylistic preferences, and some of which are clearly adaptations to deal with the specific needs of certain research objects/containers or different disciplines.

The temptation has been to try and rationalize this before extending the practice of citation to data.

“Maybe because data is a distinct record type, we should include the fact that it is a data citation in the citation itself?”

“Maybe because people cite data for different reasons, we should include a typology of citation types in all data citations?”

And so you may hear some people say, “hold off on data citation - we don’t have an optimal way to do it yet, and it can be very complicated.”

But guess what?

We currently don’t label citations to monographs as “citation to monograph.”

And we don’t currently include the reason for citation when we are citing a journal article.

It would be very cool if we did. And it would likely make citations even more useful if we did.

But citations are already useful even without these features. And so, to delay citing data indefinitely because we have an opportunity to improve the act of citation is just perverse. Our community has always opted for progress over perfection.

For one thing - the efforts are not mutually exclusive. We can start citing data with the current limitations of citation practices and simultaneously propose mechanisms for making citation more useful in the future, including new guidelines to deal with the unique issues that citing data poses.

But in the meantime, we will be doing researchers a giant favour if we at least include our imperfect and ambiguous, and unconventional references to data in the references section of an article so that they can be accessed and processed along with all the other imperfect, ambiguous and variant citations that we find so useful.

Some of our members are already doing this. They have been for a long time. And they haven’t found it any more complicated than managing non-data references in the past.

Join them and make your metadata more useful.

Cite data now. Don’t put it off.

And Crossref will continue to work with DataCite and the rest of the community to make the distribution even easier and more useful.

So who is already citing data?

Top 10 members depositing data citations from November-May 2022

(broken down by DOI prefix, which is why you see some publishers listed twice):

Prefix	Member name	Data citations deposited
10.1038	Springer Science and Business Media LLC	7174
10.1016	Elsevier BV	6527
10.1007	Springer Science and Business Media LLC	4748
10.5194	Copernicus GmbH	3017
10.1080	Informa UK Limited	2346
10.1177	SAGE Publications	2082
10.1002	Wiley	2048
10.1111	Wiley	1888
10.1108	Emerald	1876
10.3390	MDPI AG	1827

Top 10 data citations per deposited work

(again, broken down by prefix)

Member name	Prefix	Data citations deposited	Data citations per work
Consortium Erudit	10.7202	580	1.149
SLACK, Inc.	10.3928	462	0.646
S. Karger AG	10.1159	1653	0.532
Proceedings of the National Academy of Sciences	10.1073	973	0.502
American Academy of Pediatrics (AAP)	10.1542	486	0.397
F1000 Research Ltd	10.12688	552	0.341
American Association for the Advancement of Science (AAAS)	10.1126	952	0.317
Springer Science and Business Media LLC	10.1038	7174	0.231
JMIR Publications Inc.	10.2196	864	0.187
American Geophysical Union (AGU)	10.1029	692	0.166

These are for the prefixes with the most data citations deposited (>500 in 6 months) so there might be smaller members doing better than this.

Summaries are great, but I want to see some actual examples!

Here are some examples showing how data is cited by our members:

This eLife article: https://doi.org/10.7554/eLife.26410 cites this dataset in Dryad https://doi.org/10.5061/dryad.854j2.
This Copernicus article: https://doi.org/10.5194/acp-22-7105-2022 cite to this dataset https://doi.org/10.24381/cds.bd0915c6
This Sciendo article: https://doi.org/10.2478/plc-2021-0008 cites this APA-hosted language competence test https://doi.org/10.1037/t15159-000
This De Gruyter article: https://doi.org/10.1515/opth-2020-0160 cites this bibliography at Oxford Bibliographies: https://doi.org/10.1093/OBO/9780195396584-0012

And here are some example API requests for discovering more metadata citations. You can use these API requests as examples and adapt to your own needs.

Shooting for the stars – ASM’s journey towards complete metadata

Kornelia Korzec — Tue, 14 Mar 2023 00:00:00 +0000

At Crossref, we care a lot about the completeness and quality of metadata. Gathering robust metadata from across the global network of scholarly communication is essential for effective co-creation of the research nexus and making the inner workings of academia traceable and transparent. We invest time in community initiatives such as Metadata 20/20 and Better Together webinars. We encourage members to take time to look up their participation reports, and our team can support you if you’re looking to understand and improve any aspects of metadata coverage of your content.

In 2022, we have observed with delight the growth of one of our members from basic coverage of their publications to over 90% in most areas, and no less than 70% of the corpus is covered by all key types of metadata Crossref enables (see their own participation report for details). Here, Deborah Plavin and David Haber share the story of ASM’s success and lessons learnt along the way.

Could you introduce your organisation?

The American Society for Microbiology publishes 16 peer-reviewed journals advancing the microbial sciences, from food microbiology, to genomics and the microbiome, comprising 14% of all microbiology articles. Six of those are open-access journals, and 56% of ASM’s published papers are open access. Together, our journals contribute 25% of all microbiology citations.

Would you tell us a little more about yourselves?

DH: David Haber, Publishing Operations Director at the American Society for Microbiology. I live in a century-old house that is in a perpetual state of renovation due to my inability to stop starting new projects before I complete old ones.

DP: Deborah Plavin, Digital Publishing Manager at the American Society for Microbiology. Following David’s example, my apartment in Washington D.C. is just up the block from one of the homes Duke Ellington lived in https://www.hmdb.org/m.asp?m=142334.

What value do society publishers in general see in metadata in your view?

DP: In my view, robust metadata allows publishers to look at changes over time, do comparative analysis within and across research areas, more easily identify trends, and plan for future analysis (e.g., if we deposit data citation information and we change our processes to make it more straightforward, do we see any change in the percentage of articles that include that information, etc.).

DH: To echo Deborah’s point, to be able to name something distinctly and clearly identify its specific attributes is vital to understanding past research and planning for future possibilities. One of our fundamental roles as a publisher for a non-profit society is to properly lay this metadata foundation so that we can provide services and new venues for our members, authors, and readers that match their needs and track with the trends in research. Without good and robust metadata, it is impossible to truly understand the direction in which our community is pointing us.

Metadata for your own research outputs in the last year has grown rapidly. Why such focus on metadata in 2022?

DP: This is something that ASM has been chipping away at over time. Years ago we found that it wasn’t always easy to take advantage of deposits that included new kinds of metadata. That was either because we needed to work out how and where to capture it in the process or because platform providers weren’t always ready — coming up with ways to process the XML that publishers supply in many different ways takes time. These back-end processes that feed the infrastructure aren’t usually of great interest to stakeholders, and so it allowed us to play around, flounder, fail, refine, and try again.

We looked at having 3rd parties deposit metadata for us, and while that helped expand the kind of metadata we were delivering, it created workflow challenges of its own. What turned out to be most effective was budgeting for content cleanup projects and depositing updated and more robust metadata to Crossref.

We also benefited from a platform migration, which allowed us to take advantage of additional resources during that process.

DH: Coming from a production background, I have always been fascinated with the when and how of capturing key metadata during the publishing process. When are those data good and valuable, and when should they be tossed or cleaned up for downstream deliveries? Because Deborah and ASM directors saw a more complete Crossref metadata set for our corpus as a truly valuable target, we were able to really think hard about what kind of data we were capturing and when, how those requirements may have influenced our various policies and copyediting requirements over the years, and how best to re-engineer our processes with the goal of good metadata capture throughout our publishing workflows. From our perspective, Crossref gave us a target, a “this-is-cool-bit-of-info" that Crossref can collect in a deposit; therefore, how can we capture that during our processes while driving further efficiencies? ASM journals had been so driven by legacy print workflows that such a change in perspective (toward metadata as a publishing object) really allowed us to re-imagine almost everything we do as a publisher.

Has the OSTP memo influenced your effort?

DP: I think that the Nelson memo hasn’t changed our focus; instead, I think it’s been another data point supporting our efforts and work in this area.

DH: Deborah is exactly right. The release of this memo only re-affirmed our commitment to creating complete and rich metadata. The Nelson memo points to many possible paths forward, in terms of both Open Access and Open Science, but we feel our work on improving our metadata outputs positions us well to pick a path that best suits our goals as a non-profit society publisher.

How big was this effort? Could you draw us a picture of how many colleagues or parts of the organisation were involved? Did you involve any external stakeholders, such as authors, editors, or others?

DH: It was simple. Took five minutes… In all seriousness, the key is having the support of the organisation as a whole. To do this properly, it is vitally important to know the end from the beginning, so to speak. It is one thing to say let’s start capturing ORCID IDs and deliver them to Crossref, but it is completely another to create a cohesive process in which those IDs are authenticated and validated throughout the workflow. So something as simple as a statement “ORCID IDs seem cool, let’s try to capture them” could affect how researchers submit files, how reviewers log into various systems (i.e., ORCID as SSO), how data are passed to production vendors, what copyeditors and XML QC people need to be focused on, and what integrations authors may expect at the time of publication. Being part of an organisation that embraced such change allowed us to proceed with care with each improvement to the metadata we made.

But that is more about incremental improvement. The beginning of this process started when we were making upgrades to our online publishing platform, and we were trying to figure out how best to get DOIs registered for our older content. When we started looking at this, we soon realized that, sure, we could do the bare minimum and just assign DOIs to this older content outside the source XML/SGML, but did that make sense? Wouldn’t it make more sense, especially since we were updating the corpus to a new DTD, to populate the source content with these newly assigned DOIs? Once we decided that we were going to revise the older content with DOIs, it made sense for us to create a custom XSL transform routine to generate Crossref deposits that would capture as much metadata as possible. So, working with a vendor to clean and update our content for one project (an online platform update) allowed us also to make massive improvements to our Crossref metadata as a side benefit.

Of course, I do have to apologize to the STM community for the Crossref outages in late 2019. That was just me depositing thousands of records in batches one sleepless night.

What were the key challenges you encountered in this project, and how did you overcome them?

DH: Resources and time are always an issue. Much of the work was done in-house in spare moments captured here and there. But there are great resources in github and at Crossref to help focus on defining what is important and what is possible in such a project. And, honestly, defining what was important and weighing that against the effort to find said important bit in the corpus of articles we have was the most challenging part of this process. In other words, limiting the focus. Once one decides to start looking at the inconsistencies in older content, it is hard not to say: “Oh, look. That semi-important footnote was treated as a generic author note rather than a conflict-of-interest statement; let’s fix that.” Once you start down that path, you can spend years fiddling with stuff. For me, a key mantra was: “We now have access to the content. We can always do another Crossref metadata update if things change or shift over time.”

Have there been any important milestones along the way you were able to celebrate? Or any set-backs you had to resolve in the process?

DP: For as long as I can remember, the importance of good metadata has been among the loudest messages of best practice in the industry. I don’t think that I have been able to really quantify/ demonstrate the value of that work. Looking at the consistent increases in the Crossref monthly resolution reports that we saw between 2015 and 2022 and looking at our participation reports has helped provide some measure of progress. For example, the number of average monthly successful resolutions in that Crossref report in 2015 was ~390,000. The last time I checked, the 2022 numbers were ~ 3.7 million. In 2023, I hope that we will be able to leverage Event Data for this as well.

The setbacks have fallen into two categories: timing and process. Our internal resourcing to get this done within our preferred time frame, to have the content loaded and delivered, and triage problems—it’s a battle between the calendar and competing priorities.

DH: When Deborah first shared those stats with me, I was floored. I don’t think either of us suspected such an increase was possible. For me, the biggest setback was mistakenly sending about ~50,000 DOI records to queue and watching them all fail because I grabbed the wrong batch. Ooops. I never made that mistake again, though.

Was any specific type of metadata or any part of the schema particularly easy or particularly difficult to get right in ASM’s production process?

DH: For us, the most difficult piece of metadata revolves around data availability and how we capture linked data resources (outside of data citation resources). Because of our current editorial style (which had been print-centric for years), we did not do a good job of identifying whether there are data associated with published content in a consistent machine-readable way. We did some experiments with one of our journals to capture this outside of our normal Crossref deposit routine, but that was not as accurate or sustainable as we would have liked. But, in that experiment, we learned a few things about how we treat these data throughout our publishing process and we have plans to create a sustainable integrated workflow for this to capture resource/data linkages in our Crossref deposits.

What were your thoughts on last year’s move to open references metadata? Has that impacted on your project in any way?

DP: We were really excited about this; based on the rather limited approach to sorting out impact at the moment, the more metadata we push out into the ecosystem, the more it appears to be used. In my view, that is at the core of what society publishers want to do—ensure that research is accessible and discoverable wherever our users expect to find it.

DH: 100% agree.

How did you keep motivated and on-course throughout?

DP: These kinds of things are never done; for example, we have placeholders for CRediT roles, and getting ready for that work as part of a DTD migration will be the next big thing. The motivation for that is really meeting our commitment to the community, seeing the impact of the author metadata versus article metadata, and seeing what we can learn.

DH: Metadata at its core is one of the pillars of our service as a publisher. To provide the best service, we need to provide the best metadata possible. Just remembering that this can be incremental, allows us to celebrate the large moments and the small. And whether one is partying with a massive 7 layer cake or a smaller cake pop, both are sweet and motivating.

Now that the project is completed, are you seeing the benefits you were hoping to achieve?

DP: This is a hard one to answer as we are using limited measurements at this time. At a high level, I am pleased. While I am eager to leverage event data in the coming year, it would be really helpful to get feedback from the community on how we can improve as well as other ways to evaluate impact.

DH: I want to take up this idea of metadata as a service once more. I don’t mean in terms of discoverability or searchability, either. Let’s take ORCID deposited into Crossref as an example. When done properly (with the proper authentication and validation occurring in the background), we are able to integrate citation data directly to an author’s ORCID profile. We have found that this small service is really appreciated.

Is there any metadata that you’d like to be able to include with your publishing records in the future that isn’t possible currently? What would it be and why?

DP: CRediT roles would be great because it could give greater insight into collaboration within and across disciplines, it could allow for some automation and integration opportunities in the peer review process, and maybe it would visualize aspects of authors’ careers.

DH: I second capturing CRediT roles. What would be really interesting is also creating a standard that quantifies the accessibility conformance/rating of content and passing that into Crossref.

What was the key lesson you learned from this project?

DP: Incremental change can be just as challenging as a massive overhaul, and so it’s important to reevaluate your goals along the way—things always change. There have been cases where we were able to do things that we hadn’t initially thought were feasible.

DH: Always keep the larger goal in mind and remember that any project can birth a new project. Everything does not happen at once.

What’s your next big challenge for 2023?

DP: There is a lot to contend with in the industry right now, and in addition to that we are going through some serious infrastructure changes in our program. With all that madness comes many opportunities. For that reason, when I take a step back from the tactical implications of all that and what we are interested in doing, I think our biggest challenge in 2023 will be identifying what has made an impact and why.

DH: In the short-term, it is making sure that none of our production process changes has negatively affected the past metadata work we spent so much time honing. Once that settles down, it will be determining the best way forward from a publishing perspective in handling true versioning and capturing accurate event data.

Based on your experience, what would be your advice for colleagues from other scholarly publishing organisations?

DP: It can seem daunting, but the small wins can create momentum and do not have to be expensive. Remembering that your publishing program benefits as much as everyone else’s when you deposit more metadata can help refine your short-term and long-term priorities.

DH: Don’t be afraid of making a mess of things. Messes are okay. They aren’t risky. They just reveal the clutter. And clutter gives one reason to clean things up.

THANK YOU for the interview!

About the American Society for Microbiology

The American Society for Microbiology is one of the largest professional societies dedicated to the life sciences and is composed of 30,000 scientists and health practitioners. ASM’s mission is to promote and advance the microbial sciences.

ASM advances the microbial sciences through conferences, publications, certifications and educational opportunities. It enhances laboratory capacity around the globe through training and resources. It provides a network for scientists in academia, industry and clinical settings. Additionally, ASM promotes a deeper understanding of the microbial sciences to diverse audiences. For more information about ASM visit asm.org.

In the know on workflows: The metadata user working group

Jennifer Kemp — Tue, 28 Feb 2023 00:00:00 +0000

What’s in the metadata matters because it is So.Heavily.Used.

You might be tired of hearing me say it but that doesn’t make it any less true. Our open APIs now see over 1 billion queries per month. The metadata is ingested, displayed and redistributed by a vast, global array of systems and services that in whole or in part are often designed to point users to relevant content. It’s also heavily used by researchers, who author the content that is described in the metadata they analyze. It’s an interconnected supply chain of users large and small, occasional and entirely reliant on regular querying.

Tl;dr

Crossref recently wrapped up our first Working Group for users of the metadata, a group that plays a key role in discoverability and the metadata supply chain. You can jump directly to the stakeholder-specific recommendations or take a moment to share your use case or feedback.

Why a metadata user group? Why now?

A majority of Crossref metadata users rely on our free, open APIs and many are anonymous. A small but growing group of users pay for a guaranteed service level option and while their individual needs and feedback have long been integrated into Crossref’s work, as a group they provide a window into the workflows and use cases for the metadata of the scholarly record. As this use grows in strategic importance, to both Crossref and the wider community, it was clear that we might be overdue for a deeper dive into user workflows.

In 2021, we surveyed these subscribers for their feedback and brought together a few volunteers over a series of 5 calls to dig into a number of topics specific to regular users of metadata. This group, the first primarily non-member working group at Crossref, wrapped up in December 2022, and we are grateful for their time:

Achraf Azhar, Centre pour la Communication Scientifique Directe (CCSD)
Satam Choudhury, HighWire Press
Nees Jan van Eck, CWTS-Leiden University
Bethany Harris, Jisc
Ajay Kumar, Nova Techset
David Levy, Pubmill
Bruno Ohana, biologit
Michael Parkin, European Bioinformatics Institute (EMBL-EBI)
Axton Pitt, Litmaps
Dave Schott, Copyright Clearance Center (CCC)
Stephan Stahlschmidt, German Centre for Higher Education Research and Science Studies (DZHW)

This post is intended to summarize the work we did, to highlight the role of metadata users in research communications, to provide a few ideas for future efforts and, crucially, to get your feedback on the findings and recommendations. Though this particular group set out to meet for a limited time, we hope this report helps facilitate ongoing conversations with the user community.

Survey Highlights

If you’re looking for an easy overview of users and use cases, here’s a great starting point.

If you interpret this graphic to mean that there is a lot of variety centered on a few high level use cases, the survey and our experiences with users certainly supports that. A few key takeaways from the 2021 survey may be useful context:

Frequency of use: At least 60% of respondents query metadata on a daily basis
Use cases
- Finding and enhancing metadata as well as using it for general discovery are all common use cases
- For most users, matching DOIs and citations is a common need but for a significant group, it is their primary use case
- Analyzing the corpus for research was a consistent use case for 13% of respondents
Metadata of particular interest
- Abstracts are the most desirable non-bibliographic metadata, followed by affiliation information, including RORs
  - Some other elements (beyond citation information) that respondents find useful are:
    - Corrections and retractions
    - Relationship metadata
    - Book chapters
    - Grant information

NB: The survey did not ask about references but we are frequently asked why they’re not included more often.

It’s also worth noting that about a third of respondents said that correct metadata is more important to them than any particular element.

There is more to this survey that isn’t covered here but it was kept fairly short to help with the response rate. Knowing we would have some focused time to discuss issues too numerous or nuanced to reasonably address in a survey, we compiled a long list of questions and topics for the Working Group then followed up with a second, more detailed survey to kick off the meeting series.

What we set out to address

We had three primary goals for this Working Group:

Highlight the efforts of metadata users in enabling discovery and discoverability
Determine direction(s) for improved engagement
Inform the Crossref product development roadmap for metadata retrieval services

Of course, everyone involved had some questions and topics of interest to cover, including (but not limited to):

Understanding publisher workflows
How best to introduce changes, e.g. for a high volume of updated records
Understanding the Crossref schema
Query efficiencies, i.e. ‘tips and tricks’ (here for the REST API)
Which scripts, tools and/or programs are used in workflows
What other metadata sources are used
What kind of normalization or processing is done on ingest
How metadata errors are handled

What did we learn?

Workflows
I started with the admittedly ambitious goal of collecting a library of workflows. After a few years of working with users, I learned never to assume what a user was doing with the metadata, why or how. For example, some subscribers use Plus snapshots (a monthly set of all records), regularly or occasionally and some don’t use them at all. Understanding why users make the choices they do is always helpful.

In my experience, workflows are frequently characterized as “set it and forget it.” It’s hard to know how often and how easily they might be adapted when, for example, a new record type like peer review reports becomes available. So, it’s worth exploring when and how to highlight to users changes that might be of interest.

As it turned out, half the group had their workflows mostly or fully documented. The rest are partially documented, not documented at all or the availability of documentation was unknown. Helping users document their workflows, to the extent possible, should be a mutually beneficial effort to explore going forward. We’re doing similar work with the aim of making ours more transparent and replicable.

Feedback on subscriber services
User feedback might be the most obvious and directly consequential work of this group, at least for Crossref - understanding how well the services used meet their needs and what might be improved.

One frequent suggestion for improvement is faster response time on queries. This is an area we’ve focused on for some time, because refining queries to be more efficient is often the most straightforward way to improve response times and one reason for the emphasis on workflows.

We also discussed the possibility of whether or how to notify users of changes of interest. Just defining “change” is complex since they are so frequent and may often be considered very minor. We’ve been experimenting a bit over the past few years with notifying these users in cases where we’re aware of upcoming large volumes of changes, which is sometimes the case when landing page URLs are updated due to a platform change, for example. It was incredibly useful to discuss with the group what volume of records would be a useful threshold to trigger a notification (100K if you’re curious).

But perhaps the most common feedback we get from all users is on the metadata itself and the myriad quality issues involved. The group spent a fair amount of time discussing how this affects their work and shared a few examples of notable concerns:

Author name issues, e.g. ‘Anonymous’ is an option for authors but that or things like ‘n/a’ are sometimes used in surname fields
Invalid DOIs are sometimes found in reference lists
Garbled characters from text not rendering properly
Affiliation information is often not included or incomplete (e.g. doesn’t include RORs)
Inconsistencies in commonly included information, e.g. ISSNs

It’s worth noting that a common misunderstanding - not just among users - is what is required in the metadata. Users nearly always expect more metadata and more consistency than is actually available. The introduction of Participation Reports a few years ago was a very useful start to what is an ongoing discussion about the variable nature of metadata quality and completeness.

Users in the metadata supply chain
A few years ago, our colleague Joe Wass used Event Data to put together this chart of referrals from non-publisher sources in 2015.

The role of metadata users in discoverability of content is key in my view and one that often doesn’t get enough attention, especially given that the systems and services that use this information often use it to point their own users to relevant resources. And because they work so closely with the metadata, users frequently report errors and so serve as a sort of de facto quality control. So, unfortunately, the effects of incomplete or incorrect metadata on these users might be the most powerful way to highlight the need for more and better metadata.

What are the recommendations?

In discussions with the Working Group, a few themes emerged, largely around best practices, which, by their nature, tend to be aspirational.

If you’re not already familiar with the personas and Best Practices and Principles of Metadata 2020, that is a useful starting point (I am admittedly biased here!) and many are echoed in the following recommendations:

For users:

Document and periodically review workflows
Report errors to members or to Crossref support and reflect corrections when they’re made (metadata and content)
Understand what is and isn’t in the metadata
Follow best practices for using APIs

For Crossref:

Define a set of metadata changes, e.g. to affiliations, to further the discussion around thresholds for notifying users of ‘high volumes’ of changes
Provide an output schema.
Continue refining the input schema to include information like preprint server name, journal article sub types (research article, review article, letter, editorial, etc.), corresponding author flags, raw funding statement texts, provenance information, etc.
Collaborate on improving processes for reporting metadata errors and making corrections and enhancements

For metadata providers (publishers, funders and their service providers):

Follow Metadata 2020 Metadata Principles and Practices
Consistency is important, e.g. using the same, correct relationship for preprint to VoR links for all records
- Workarounds such as putting information into a field that is ‘close’ but not meant for it can be considered a kind of error
Understand the roles and needs of users in amplifying your outputs
Respond promptly to reports of metadata errors
Whenever possible, provide PIDs (ORCID IDs, ROR IDs, etc.) in addition to (not as a substitute for) textual metadata

What is still unclear or unfinished?

Honestly, a lot. We knew from the outset that the group would conclude with much more work to be done, in part because there is so much variety under the umbrella of metadata users and many answers lead to more questions and in part because the metadata and the user community will continue to evolve. Even without a standing group that meets regularly, it’s very much an ongoing conversation and we invite you to join it.

Now it’s your turn–can you help fill in the blanks?

Does any or all of this resonate with you? Do you take exception to any of it? Do you have suggestions for continuing the conversation?

Specifically, can you help fill in any of the literal blanks? We’ve prepared a short survey that we hope can serve as a template for collecting (anonymous) workflows. Please take just a few minutes to answer a few short questions such as how often you query for metadata.

If you are willing to share examples of your queries or have questions or further comments, please get in touch.

Don't take it from us: Funder metadata matters

Jennifer Kemp — Thu, 16 Feb 2023 00:00:00 +0000

Why the focus on funding information?

We are often asked who uses Crossref metadata and for what. One common use case is researchers in bibliometrics and scientometrics (among other fields) doing meta analyses on the entire corpus of records. As we pass the 10 year mark for the Funder Registry and 5 years of funders joining Crossref as members to register their grants, it’s worth a look at some recent research that focuses specifically on funding information. After all, there is funding behind so much scholarly work it seems obvious that it would be routinely documented in the scholarly record. But it often isn’t and that’s a problem. These sources make clear the need for accurate funding information and the problems that the lack of it creates.

First, a few notes for context on these sources and the issues they discuss :

The percent of records with funding information reached about 25% as of 2021. Not all items registered are the result of funding but surely it is much higher than 25% so there is considerable room for improvement. The authors cite publishers that omit funding information as well as those that include it routinely. Overall, society publishers are at the top of the list of those that do it well.
Three of the four sources found problems in some cases confirming funding information from the metadata in the original sources. This initially surprised me though less so once I thought about the strange nature of metadata workflows.
The complexity of fully and correctly acknowledging multiple sources of funding in any given publication is a recurring theme.
All of the sources mention the need for manual work in analyzing funding and publication information.

The first two papers are from the same 2022 issue of Quantitative Science Studies and are complementary.

Alexis-Michel Mugabushaka, Nees Jan van Eck, Ludo Waltman; Funding COVID-19 research: Insights from an exploratory analysis using open data infrastructures. Quantitative Science Studies 2022; 3 (3): 560–582. doi: https://doi.org/10.1162/qss_a_00212

This first paper tackles the timely question of determining which funders have supported publications of COVID-19 research and compares coverage of funding data in Crossref to that in Scopus and Web of Science. Even with so much urgent attention focused on the pandemic, the authors found that only 17% of publications in the COVID-focused CORD-19 database have funding identified in their Crossref records. We’re often asked about differences in the metadata (and citation counts) between Crossref and other sources such as Scopus. In this case, both proprietary sources studied have more funder coverage. If you are disappointed in these results or want to learn more, I encourage you to read the authors’ recommendations for improving funding data in Crossref or get in touch with us.

Bianca Kramer, Hans de Jonge; The availability and completeness of open funder metadata: Case study for publications funded by the Dutch Research Council. Quantitative Science Studies 2022; 3 (3): 583–599. doi: https://doi.org/10.1162/qss_a_00210

This next paper focuses on a set of outputs funded by the NWO (the Dutch Research Council). Since the funder is already known, the authors could look at multiple sources (Crossref and others) to see whether or where the NWO is correctly identified as the funder. This study also found better coverage than Crossref in proprietary sources like Web of Science. Knowing that not all outputs are the result of funded research, this paper provides a new and useful baseline for comparing percentages of coverage. Discussions of research funding so often focus on the physical and life sciences so it’s very good to see that 37% of works in this study are in the humanities and social sciences.

Borst, T., Mielck, J., Nannt, M., Riese, W. (2022). Extracting Funder Information from Scientific Papers - Experiences with Question Answering. In: , et al. Linking Theory and Practice of Digital Libraries. TPDL 2022. Lecture Notes in Computer Science, vol 13541. Springer, Cham. https://doi.org/10.1007/978-3-031-16802-4_24

Given the considerable effort required to conduct these analyses, it’s only logical to consider automating as much of the work as possible. This next paper focuses on automatic recognition of funders in economics papers in digital libraries. An interesting complication described here is the inclusion of funding for open access fees in acknowledgments and while the authors conclude that automated text mining of funder information performs better than manual curation, they also state that manual indexing is still necessary “for a gold standard of reliable metadata.”

Habermann, T. (2022). Funder Metadata: Identifiers and Award Numbers. https://metadatagamechangers.com/blog/2022/2/2/funder-metadata-identifiers-and-award-numbers

Finally, this concise blog post looks at RORs as well as funder names and acronyms. The author shows how acronyms contribute to the need for manual analysis. He also spends some time on award numbers, which is one of the three funding elements publishers can (and, as we’ve seen, should) include in their metadata. Award numbers are also a focus of this work and, unfortunately, another frequent reason for additional manual work.

A common theme: More metadata needed

Though collectively, this research paints a fairly dim picture of the current availability, completeness and accuracy of existing funding information in publication metadata, all is not lost. This is a good opportunity to point out the value and availability of grant records since unique, persistent identifiers for grants (yes, DOIs for grants) paired with more and better funding metadata from publishers go a very long way to realizing the vision of the Research Nexus. And it certainly would make things a whole lot easier for the researchers who use this open metadata to analyze the scholarly record for the rest of us.

Measuring Metadata Impacts: Books Discoverability in Google Scholar

Lettie Conrad — Wed, 25 Jan 2023 00:00:00 +0000

This blog post is from Lettie Conrad and Michelle Urberg, cross-posted from the The Scholarly Kitchen.
As sponsors of this project, we at Crossref are excited to see this work shared out.

The scholarly publishing community talks a LOT about metadata and the need for high-quality, interoperable, and machine-readable descriptors of the content we disseminate. However, as we’ve reflected on previously in the Kitchen, despite well-established information standards (e.g., persistent identifiers), our industry lacks a shared framework to measure the value and impact of the metadata we produce.

In 2021, we embarked on a Crossref-sponsored study designed to measure how metadata impacts end-user experiences and contributes to the successful discovery of academic and research literature via the mainstream web. Specifically, we set out to learn if scholarly books with DOIs (and associated metadata) were more easily found in Google Scholar than those without DOIs.

Initial results indicated that DOIs have an indirect influence on the discoverability of scholarly books in Google Scholar – however, we found no direct linkage between book DOIs and the quality of Google Scholar indexing or users’ ability to access the full text via search-result links. Although Google Scholar claims to not use DOI metadata in its search index, the results of our mixed-methods study of 100+ books (from 20 publishers) demonstrate that books with DOIs are generally more discoverable than those without DOIs.

As we finalize our analysis, we are sharing some early results and inviting input from our community. What relevant lessons can we glean from this exercise? What changes might book publishers consider based on the outcomes of this study?

Background on the study

This study was designed to evaluate metadata impacts & benefits to users. Given its popularity with a range of stakeholders in our industry, we set out to measure metadata impacts on discoverability in the mainstream web – namely, Google Scholar.

Our test method and analysis rubric was developed based on our own information-user research, in particular how readers search and retrieve scholarly ebooks, as well as published studies about academic information experiences and research practices. We rated the search performance of more than 100 scholarly books using preset test queries (two for each title). The books tested in this study came from publishers of all sorts and sizes, and represent both monographs and edited volumes from a range of fields; some were open access and others were published under traditional licensing models.

We developed and executed known-item test searches that were designed to simulate common researcher practices. Heuristic analysis of the search results was used to rate the search performance on a 5-point scoring rubric, which was designed to measure the degree of friction in locating the book in question. This method allowed us to assess specific book and metadata attributes by their search performance scores to assess the impact of book metadata on content discoverability in Google Scholar.

Results and findings

In this study, we learned that high-value fields include the primary title paired with subtitles, author/editor surnames and/or field of study. Queries using full book titles performed the best across the board. Those using publication dates and/or author/editor surnames and/or publisher names, but without the book title, were the lowest performers.

Surprisingly, our discoverability scores show no significant variation in performance by the type of book, whether edited or authored. Open-access titles performed somewhat better than traditional ones. Books covering humanities and social science fields performed a bit better than STM books, but only by a slim difference (that is not statistically significant).

We primarily tested the discoverability of book titles, from equal numbers of books with and without chapter-level DOIs. We ran similar tests for chapter-title discoverability but found the majority of test queries for chapters lead users to the full book itself. While books without title-level DOIs were found to be less discoverable, we did not find a measurable difference between books with or without chapter-level DOIs. (Note: All books in this study with chapter-level DOIs assigned also carried a title-level DOI, which was found to be fairly common.)

Based on these results, we are developing a theory that books with DOIs perform better in Google Scholar because they benefit from the structured, open metadata associated with those DOIs – which are used by hundreds of platforms and services, and therefore are “seeded” throughout the mainstream web, which Scholar may draw on for indexing, linking, etc. That said, however, these results also suggest that publishers are best served by a metadata strategy that is well attuned to the protocols expected of each channel for book search and discovery. In a recent conversation about our findings, Anurag Acharya himself noted that these results underscore the need for publishers to invest in the robust construction and broad distribution of book metadata.

In this study, we have observed that the metadata protocols surrounding Google Scholar are not fully integrated into our industry’s established scholarly information standards bodies, like NISO, or infrastructure organisations, like Crossref. While some mainstream data standards prevail in the Scholar index, like the use of schema.org and HTTP, some key metadata attributes seem to be lacking. For example, an indicator of the type of scholarly book (monograph, handbook, etc.) would improve Google Scholar’s search index and could be used to filter search results, thereby improving users’ experiences discovering scholarly books. One clear challenge for book publishers today is the fact that Google Scholar operates outside of our community-governed scholarly information infrastructure.

What comes next

While this study focused on Google Scholar, the results and lessons learned are applicable to other mainstream channels of information seeking/discovery. Our report, due out spring 2023, will contribute to the literature intended to support user-centric information systems design and content architecture by scholarly publishers and service providers.

As we write up our findings, we intend to develop a framework that can help publishers and others measure the impact of their work to enrich and distribute scholarly metadata. We hope this first systematic review of the impacts of metadata on the discoverability of books in Google Scholar will provide valuable insights for this community. In the meantime, please share your thoughts and questions in the comments below – or reach out to us directly (see Lettie’s profile here and Michelle’s profile here).

Acknowledgments: The authors would like to thank Jennifer Kemp at Crossref for the inspiration to take this dive into the metadata literature and reflect on its impact on research information experiences. Special thanks to Anurag Acharya at Google Scholar for his consultation during this study.

How funding agencies can meet OSTP (and Open Science) guidance using existing open infrastructure

Ed Pentz — Thu, 17 Nov 2022 00:00:00 +0000

In August 2022, the United States Office of Science and Technology Policy (OSTP) issued a memo (PDF) on ensuring free, immediate, and equitable access to federally funded research (a.k.a. the “Nelson memo”). Crossref is particularly interested in and relevant for the areas of this guidance that cover metadata and persistent identifiers—and the infrastructure and services that make them useful.

Funding bodies worldwide are increasingly involved in research infrastructure for dissemination and discovery. While this post does respond to the OSTP guidelines point-by-point, the information here applies to all funding bodies in all countries. It will be equally useful for publishers and other systems that operate in the scholarly research ecosystem.

In response to calls from our community for more specifics, this post:

Provides an overview of the specific ways that Crossref (along with organisations and initiatives like DataCite, ORCID, and ROR) helps U.S. federal agencies—and indeed any other funder—meet critical aspects of the recommendations.
Restates our intent to collaborate with all stakeholders in the scholarly research ecosystem, including the OSTP, the US federal agencies, our existing funder, publisher, and university members, to support the recommendation as plans develop.
References the work and adoption of Crossref Grant DOIs, including analyses of existing metadata matching funding to outputs.
Highlights that what’s outlined in the memo aligns with our longstanding mission to capture and maintain the scholarly record and our vision of the Research Nexus, as we describe in our current blog series, regarding our role in preserving the integrity of the scholarly record (ISR).

Infrastructure already exists to support funder goals; it just needs more adoption

Ensuring free, immediate, and equitable access to metadata that captures the scholarly record is an essential part of meeting the aims of the memo but also supporting Open Science globally.

In September, Crossref ORCID, DataCite, and ROR participated in the 2022 Forum on Global Grants Management run by Altum and the summary provides a good example of the importance of open infrastructure and open metadata to the goals of Open Science:

Open Science begins with open infrastructure: Attendees agreed that Open Science relies on many other ‘opens’ – most notably, open metadata, open infrastructure, and open governance. Metadata and DOIs (digital object identifiers) for publications, grants, and research outputs, are essential to illuminate the connections that exist between funding and outcomes. That metadata runs on infrastructure powered by organisations such as Crossref, ORCID, ROR, and DataCite.

As a foundational scholarly infrastructure committed to meeting the Principles of Open Scholarly Infrastructure (POSI) of governance, insurance, and sustainability, Crossref plays an essential role in implementing and supporting key aspects of the guidance. For many years, we have been focused on the integrity of the scholarly record (ISR), and the shared vision to collectively achieve what we call the Research Nexus, which is described as

A rich and reusable open network of relationships connecting research organisations, people, things, and actions; a scholarly record that the global community can build on forever, for the benefit of society.

Metadata—including persistent identifiers and relationships between different research objects—is the foundation of the Research Nexus and is critical to openly and sustainably fulfilling the OSTP memo’s recommendations.

This topic of open metadata and identifiers isn’t just an issue for research resulting from US federal funding. We are working to implement open scholarly infrastructure globally, bringing significant benefits to the whole scholarly research ecosystem.

The current situation brings to mind the William Gibson quote, “The future is already here - it’s just not evenly distributed yet”. Much of the open infrastructure to support the identifier, metadata and reporting requirements of the OSTP memo already exists, but it is unevenly implemented. Increased collaboration and effort will be needed to bring this all to fruition.

We set out below some steps that all stakeholders can take to meet not just the OSTP guidelines, but Open Science goals more broadly, and globally.

What does ‘adoption’ look like? How exactly do funders and other stakeholders work with this infrastructure?

The OSTP memo calls for specific actions concerning metadata and identifiers where, fortunately, open and global solutions already exist.

For example, item 4 a) says, “Collect and make publicly available appropriate metadata associated with scholarly publications and data resulting from federally funded research.” Crossref and DataCite make metadata, including persistent identifiers (DOIs to be specific), openly available for a broad range of research objects from publications to data. Item 4 b) reads, “Assign unique digital persistent identifiers to all scientific research and development awards and intramural research protocols”. Again, federal agencies and other funders are already joining to register awards and grants and distribute these records openly through Crossref. However, this is an example of uneven adoption as registering awards and grants with DOIs is only being done by a few funders so far, which needs to increase.

Here is an ideal workflow that funders and publishers can already follow

Funders join Crossref to register grants and awards (or indeed any other object such as reports). They apply on our website, accept our terms, and provide key information such as contact details. An annual membership fee ranges from $200-$1200 USD.
Funders and publishers collect ROR IDs and authenticated ORCID iDs for all authors/awardees and their affiliations.
Funders register a Crossref DOI for the award/grant, including awardees’ ORCID iDs and ROR IDs. They send us XML information about the grant (note that we will imminently release an online form to make it easier for the less technical funders). Many funder members register the metadata through a third party, such as Altum (if they use ProposalCentral) or Europe PMC.
At the same time, funders update the awardees’ ORCID record directly with the Crossref Grant DOI and metadata.
Grantees produce research objects and outputs such as data, protocols, code, preprints, articles, conference papers, book chapters, etc.
These objects are registered with Crossref or DataCite, and DOIs are created by the publisher or repository members who include ORCID iDs, Crossref Grant DOIs (gathered from the author), ROR IDs for affiliations for all contributors, and other key metadata such as licensing information, and in the case of publications - references and abstracts. Note that the publisher works its magic (actually, publishers do a lot of editorial and production work, such as including data citations in the references using DataCite DOIs for the data in data repositories).
On the Crossref side, we do a bunch of processing and matching and are planning to refine this and do more. Sometimes relationships are notified and added, such as data citation, preprints related to articles or funding acknowledgements converted from free text to Open Funder Registry IDs and names.
Grant records with Crossref DOIs are now part of the scholarly record. All stakeholders may retrieve the open metadata and relationships through our public APIs. Crossref and DataCite will always provide open metadata, as safeguarded by our respective commitments to POSI.

Anyone can use the open metadata registered with Crossref, DataCite and ORCID as connections have been established between (ideally all) research objects and entities through open metadata and identifiers. This means that:

Funding agencies can monitor compliance with their policies
Publishers can identify the funder and meet their requirements
Funding agencies can assess and report on the reach and return of their funding programs
The provenance and integrity of the scholarly record is preserved and discoverable, benefitting all stakeholders.

Suggestions for meeting OSTP and Open Science guidance, point by point

OSTP Recommendation	Publishers should…	Funding agencies should…
4 a) Collect and make publicly available appropriate metadata associated with scholarly publications and data resulting from federally funded research	For scholarly publications: register comprehensive metadata & DOIs with Crossref. For scholarly data: register comprehensive metadata and DOIs with DataCite.	Use Crossref’s API to retrieve publication and other metadata. Use DataCite’s API to retrieve data/repository metadata.
i) all author and co-author names, affiliations, and sources of funding, referencing digital persistent identifiers, as appropriate;	Collect and validate the following from authors at manuscript submission: ROR & ORCiD IDs, Crossref Grant DOIs. Include data citations in reference lists, preferably with DataCite DOIs.	Register awards and grants with Crossref and create DOI records for them. Use ORCID’s API to retrieve validated contributor metadata. Update contributors’ ORCID records with Crossref Grant DOIs and metadata. Use ROR API to retrieve and verify affiliation metadata. Recommend data citations be included in published outputs.
ii) the date of publication; and,	Include acceptance and publication dates in Crossref metadata.	Use Crossref’s API to retrieve publication dates.
iii) a unique digital persistent identifier for the research output;	For scholarly publications and research outputs: register full metadata & DOIs with Crossref. For scholarly data: register full metadata and DOIs with DataCite.	Use Crossref and DataCite APIs to retrieve DOIs for research outputs.
4 b) Instruct federally funded researchers to obtain a digital persistent identifier that meets the common/core standards of a digital persistent identifier service defined in the NSPM-33 Implementation Guidance, include it in published research outputs when available, and provide federal agencies with the metadata associated with all published research outputs they produce, consistent with the law, privacy, and security considerations.	Collect ORCID iDs on manuscript submission for all authors. Register Crossref and DataCite DOIs and metadata for research outputs, including data.	Recommend that researchers applying for funding obtain an ORCID iD and collect them upon grant application for all applicants. Prepopulate grant applications with CV and publication information from applicants’ ORCID records. ORCID iDs should be included in the grants registered by the agencies with Crossref. Agencies can use our open APIs to retrieve the metadata on publications and data rather than ask researchers to do it, saving time and effort.
4 c) Assign unique digital persistent identifiers to all scientific research and development awards and intramural research protocols that have appropriate metadata linking the funding agency and their awardees through their digital persistent identifiers.		Join Crossref to register Crossref Grant DOIs, including ROR IDs and ORCID iDs Ensure grant proposal and assessment systems integrate with Crossref, ROR for affiliations and with ORCID for applicants/awardees.
5 a) coordinate between federal science agencies to enhance efficiency and reduce redundancy in public access plans and policies, including as it relates to digital repository access;	Work with agencies to ensure a smooth, automated workflow.	Using and supporting existing open scholarly infrastructure and using open identifiers will avoid duplication of effort and make the overall ecosystem more efficient .
5 b) improve awareness of federally funded research results by all potential users and communities;	Collect Crossref Grant DOIs from authors and use them to link from publications to grant information.	Communicate your Crossref Grant DOIs and open grant metadata widely via human and machine interfaces. Inclusion in the Crossref API will enhance dissemination and discoverability Update contributors’ ORCID records with Crossref Grant DOIs and metadata
5 c) consider measures to reduce inequities in the publishing of, and access to, federally funded research and data, especially among individuals from underserved backgrounds and those who are early in their careers;		Registering grants and sharing metadata through Crossref means it’s part of the world’s largest open community-governed metadata exchange and makes it available to the entire world without restriction.
5 d) develop procedures and practices to reduce the burden on federally funded researchers in complying with public access requirements;	Ensure your systems and those you work with make it as easy as possible for authors to provide the necessary metadata and persistent identifiers - work towards as much automation as possible and pulling from other systems rather than asking for data to be re-keyed.	Ensure the platforms you work with, such as grant proposal or assessment systems, retrieve and prepopulate ROR IDs, ORCID iDs, and Crossref and DataCite DOIs and associated metadata whenever possible so that the researchers don’t have to manually rekey or reformat data.
5 e) recommend standard consistent benchmarks and metrics to monitor and assess implementation and iterative improvement of public access policies over time;		Ensure that platforms and systems integrate with ROR, ORCID, Crossref, and DataCite so that this open metadata can lead to the creation of benchmarks and metrics.
5 f) improve monitoring and encourage compliance with public access policies and plans;	Use open infrastructure to help authors easily comply with public access and funder/institution policies. Automate systems as much as possible.	Using the open infrastructure, metadata, and identifiers outlined in this post will make monitoring more straightforward and compliance easier for all stakeholders. The community can build services on open infrastructure and metadata.
5 g) coordinate engagement with stakeholders, including but not limited to publishers, libraries, museums, professional societies, researchers, and other interested non-governmental parties on federal agency public access efforts;	Work with the global open infrastructure organisations (Crossref, DataCite and ORCID) whose members include funding agencies, societies, publishers, universities, libraries, repositories, museums, NGOs, and many other stakeholders - all looking to improve the efficiency of the research ecosystem.	Work with the global open infrastructure organisations (Crossref, DataCite and ORCID) whose members include funding agencies, societies, publishers, universities, libraries, repositories, museums, NGOs, and many other stakeholders - all looking to improve the efficiency of the research ecosystem.
5 h) develop guidance on desirable characteristics of—and best practices for sharing in—online digital publication repositories;	Support automated systems that use metadata and identifiers to populate repositories automatically.	Collaborate with publishers, Crossref and others to develop automated systems to populate repositories.
5 j) develop strategies to make federally funded publications, data, and other such research outputs and their metadata are findable, accessible, interoperable, and re-useable, to the American public and the scientific community in an equitable and secure manner.	Provide and support a range of discovery services based on open infrastructure.	Encourage discovery services - and develop services - that use the open infrastructure, metadata and persistent identifiers to enable.

Everybody needs to play their part

A lot of the work on making the above happen is already underway, and there is widespread adoption of open identifiers and metadata, but as noted above, funders are still early in the adoption journey, and implementation among all stakeholders is patchy.

Critical parts of the infrastructure rely on third-party platforms that supply tools and systems to authors, funders, and publishers - so coordinating the support for the appropriate metadata and identifiers in these systems and tools is very important.

We are emphasising how our existing open scholarly infrastructure systems are helping. But we also know that it’s not all perfect yet. Infrastructure is always evolving, metadata is never complete, refactoring workflows and systems can be costly, and integration can always be smoother. But our existing open infrastructure has already delivered significant benefits, and broader adoption will bring additional benefits to the whole scholarly research and communications ecosystem and help achieve the promise of Open Science in advancing human knowledge.

While working on this coordination and integration, we all try to remember that it should minimise work for researchers, and processes should be as automated as possible.

Collaboration is key to making this all work.

We already work with many funders through our Advisory Group, our 30 funder members, 25 of whom have so far collectively registered around 40,000 Crossref Grant DOIs, retrievable from our open API. Some grants are even matched to resulting outputs already, and some funders have recently dug into Crossref metadata to analyse outcomes from their investments, such as the Dutch Research Council (NWO) which presents findings and makes a case for greater emphasis on Crossref funding metadata.

We also work closely with partners Europe PMC and Altum, and we engage in community research and discussion, for example, through the Open Research Funders Group.

Alongside our fellow infrastructures and open identifier registries ORCID, DataCite, and ROR, we integrate with and support each other operationally and out in the community.

We will continue focusing our resources and efforts on engaging with funders, including US federal agencies responding by the OSTP guidelines, and all stakeholders to support the entire global scholarly research ecosystem.

Everyone has a part to play, and we must all pull together to prioritize this work.

Who’s in?

Please get in touch with Ed, Ginny, or Jennifer (or indeed DataCite or ORCID or ROR) if you’d like to have a discussion about the workflows described here, or just to make sure you’re up to date on the latest developments and opportunities we describe. We look forward to working with all funding agencies to support them as they develop their plans.

Better preprint metadata through community participation

Martyn Rittman — Wed, 09 Nov 2022 00:00:00 +0000

Preprints have become an important tool for rapidly communicating and iterating on research outputs. There is now a range of preprint servers, some subject-specific, some based on a particular geographical area, and others linked to publishers or individual journals in addition to generalist platforms. In 2016 the Crossref schema started to support preprints and since then the number of metadata records has grown to around 16,000 new preprint DOIs per month.

Preprints aren’t the same as journal articles, books, or conference papers. They have unique features, and how they are viewed and integrated into the publishing process has evolved over the past six years. For this reason, we have been revisiting the preprint metadata schema and decided that the best approach would be to form an advisory group (AG) of preprint practitioners and experts to help us.

The AG has identified a number of areas in which preprint metadata could be improved. Four of these were considered to have the highest priority:

Withdrawal and removal of preprints.
Preprints as an article type (not a subtype of posted content) in the schema.
Relationships between preprints and other outputs.
Versioning of preprints.

The members of the AG set to work with great enthusiasm, sharing perspectives and expertise. This led to a first tranche of recommendations shared for feedback earlier this year, and we’re grateful for engagement and feedback from the community over the last few months.

What did the community say?

Some of the points raised in the feedback were:

Could the origin of a withdrawal be included in the metadata, in particular whether it was requested by an author or another party?
Can the metadata represent when a preprint has been submitted to a journal and what stage it is in the editorial process?
Crossref is not alone in looking at preprint metadata, and several NISO groups are also engaged in related work.
Interoperability and the ability to create relationships with identifiers beyond DOIs is important to maintain an accurate and comprehensive record of research outputs.

These will form the basis for ongoing discussions.

What happens next?

There are three next steps that we will be taking.

The recommendations outline only the outcomes of discussions in a relatively brief format. We have been working on a more detailed paper to communicate more about what was discussed and provide some extra justification and alternatives.
The AG will continue to meet and discuss the points raised during consultation on the recommendations, along with topics that were considered a lower priority at an earlier stage.
We will draw up a set of proposals for specific changes to the metadata schema that will reflect the outcomes of the recommendations and discussions.

Although the initial period for feedback on preprint metadata has ended, we welcome feedback at any time. If you would like to get in touch, please contact me or any member of the advisory group.

The Research Nexus: a vision for a more connected scholarly community

Jennifer Kemp — Tue, 01 Nov 2022 00:00:00 +0000

The Research Nexus: A vision for a more connected scholarly community

Published in Information Services and Use (2022), this paper sets out Crossref’s vision for a Research Nexus — a comprehensive, interconnected graph linking scholarly entities through persistent identifiers and open metadata. Based on a presentation at NISO Plus in February 2022.

Strategists

Understand why connections between scholarly entities matter as much as the entities themselves. How a richer graph of relationships — between works, people, organisations, and outputs — can transform discovery, assessment, and trust in the scholarly record.

Decision-makers

See how the Research Nexus vision maps to your organisation’s metadata strategy. Why investing in persistent identifiers and open metadata is foundational to a more connected, more trustworthy research ecosystem.

Practitioners

Learn how Crossref’s metadata infrastructure supports the Research Nexus. The role of DOIs, ORCIDs, ROR IDs, funder IDs, and relationships between records in building a comprehensive scholarly graph.

What this paper covers

The Research Nexus concept — a vision for a rich, machine-readable graph connecting all entities in the scholarly ecosystem: works, people, organisations, funders, datasets, and more
Why connections matter — how relationships between entities enable discovery, research assessment, integrity checking, and open science workflows that individual records cannot support alone
The role of persistent identifiers — DOIs, ORCIDs, ROR IDs, and funder IDs as the building blocks of a connected scholarly record
Crossref’s contribution — how Crossref metadata links works to people, institutions, funders, and related outputs, and how members can enrich those connections
Gaps and opportunities — where the scholarly graph is incomplete, and what it would take to fill those gaps through community collaboration
A call to action — how publishers, institutions, funders, and infrastructure providers can work together to realise the Research Nexus vision

Read the full paper

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Flies in your metadata (ointment)

Isaac Farley — Mon, 25 Jul 2022 00:00:00 +0000

Quality metadata is foundational to the research nexus and all Crossref services. When inaccuracies creep in, these create problems that get compounded down the line. No wonder that reports of metadata errors from authors, members, and other metadata users are some of the most common messages we receive into the technical support team (we encourage you to continue to report these metadata errors).

We make members’ metadata openly available via our APIs, which means people and machines can incorporate it into their research tools and services - thus, we all want it to be accurate. Manuscript tracking services, search services, bibliographic management software, library systems, author profiling tools, specialist subject databases, scholarly sharing networks - all of these (and more) incorporate scholarly metadata into their software and services. They use our APIs to help them get the most complete, up-to-date set of metadata from all of our publisher members. And of course, members themselves are able to use our free APIs too (and often do; our members account for the vast majority of overall metadata usage).

We know many organisations use Crossref metadata. We highlighted several different examples in our API case study blog series and user stories. Now, consider how errors could be (and often are) amplified throughout the whole research ecosystem.

While many inaccuracies in the metadata have clear consequences (e.g., if an author’s name is misspelled or their ORCID iD is registered with a typo, the ability to credit the author with their work can be compromised), there are others, like this example of typos in the publication date, that may seem subtle, but also have repercussions. When we receive reports of metadata quality inaccuracies, we review the claims and work to connect metadata users with our members to investigate and then correct those inaccuracies.

Thus, while Crossref does not update, edit, or correct publisher-provided metadata directly, we do work to enrich and improve the scholarly record, a goal we’re always striving for. Let’s look at a few common examples and how to avoid them.

Pagination faux pas

First page marked as 1

In the XML registered

<pages>
<first_page>1</first_page>
<last_page>1</last_page>
</pages>

https://api.crossref.org/works?filter=type:journal-article&select=DOI,title,issue,page&sample=100

Other pagination errors

In the XML registered

<item_number item_number_type="article-number">1</item_number>

In the XML registered

<pages>
<first_page>121-123</first_page>
<last_page>129</last_page>
</pages>

Author naming lapses

Examples: Titles (Dr., Prof. etc.) in the given_name field; Suffixes (Jr., III, etc.) in the surname field; superscript number, asterisk, or dagger after author names (usually carried over from website formatting that references affiliations); full name in surname field

In the XML registered

<contributors>
<person_name sequence="first" contributor_role="author">
<given_name>DOCTOR KATHRYN</given_name>
<surname>RAILLY</surname>
</person_name>
<person_name sequence="additional" contributor_role="author">
<given_name>DOCTOR JOSIAH S.</given_name>
<surname>CARBERRY</surname>
</person_name>
</contributors>

<contributors>
<person_name contributor_role="author" sequence="first">
<surname>Mahmoud Rizk</surname>
</person_name>
<person_name contributor_role="author" sequence="additional">
<surname>Asta L Andersen(</surname>
</person_name>
</contributors>

organisations as authors slip-ups

Examples: The contributor role for person names is for persons, not organisational contributors, but we see this violated from time to time. Unfortunately, no persons are being credited with contributing to content that have these errors present in the metadata record.

In the XML registered

<contributors>
<person_name sequence="first" contributor_role="author">
<surname>Society</surname>
</person_name>
</contributors>

<person_name contributor_role="author" sequence="first">
<given_name>University of Melbourne</given_name>
<surname>University of Melbourne</surname>
</person_name>
</contributors>

Null no-nos

Examples: Too many times we see “N/A”, “null”, “none” in various fields (pages, authors, volume/issue numbers, titles, etc.). If you don’t have or know the metadata, it’s better to omit it for optional metadata elements than to include inaccuracies in the metadata record.

In the XML registered

<journal_volume>
<volume>null</volume>

<pages>
<first_page>null</first_page>
<last_page>null</last_page>
</pages>

<person_name sequence="first" contributor_role="author">
<given_name>Not Available</given_name>
<surname>Not Available</surname>
</person_name>
<person_name sequence="additional" contributor_role="author">
<given_name>Not Available</given_name>
<surname>Not Available</surname>
</person_name>

Where to go from here?

One thing we’ve said throughout this blog that we’ll reiterate here is: accurate metadata is important. It’s important in itself, and the metadata registered with us is heavily used by many systems and services, so think Crossref and beyond. In addition to that expanding perspective, there are practical steps members and metadata users can take to help us:

As a member registering metadata with us:

make sure we have a current metadata quality contact for your account and update us if there’s a change
if you receive an email request from us to investigate a potential metadata error, help us
if you do not know what to enter into a metadata element or helper tool field, please leave it blank; perhaps some of the examples of errors within this blog were placeholders that the responsible members intended to come back to - to correct in time; that’s also a practice to avoid
if you find a record in need of an update, update it - updates to existing records are always free (we do this to encourage updates and the resulting accurate, rich metadata, so take advantage of it).

As a metadata user:

if you spot a metadata record that doesn’t seem right, let us know with an email to support@crossref.org and/or report it to the member responsible for maintaining the metadata record (if you have a good contact there)
if you’re eager to confirm the last update of a metadata record, our REST API is a great resource; here’s a handy query to use as a starting point: this one returns records on our Crossref prefix 10.5555 that have been updated in 2022: https://api.crossref.org/prefixes/10.5555/works?rows=500&filter=from-update-date:2022-01-01,until-pub-date:2022-12-31&mailto=support@crossref.org

Making connections between research objects is critical, and inaccurate metadata complicates that process. We’re continually working to better understand this, too. That’s why we’re currently researching the reach and effects of metadata. Our technical support team is always eager to assist in correcting errors. We’re also keen on avoiding those mistakes altogether, so if you are uncertain about a metadata element or have questions about anything included in this blog post, please do contact us at support@crossref.org. Or, better yet, post your question in the community forum so all members and users can benefit from the exchange. If you have a question, chances are others do as well.

2022 public data file of more than 134 million metadata records now available

Patrick Polischuk — Fri, 13 May 2022 00:00:00 +0000

In 2020 we released our first public data file, something we’ve turned into an annual affair supporting our commitment to the Principles of Open Scholarly Infrastructure (POSI). We’ve just posted the 2022 file, which can now be downloaded via torrent like in years past.

We aim to publish these in the first quarter of each year, though as you may notice, we’re a little behind our intended schedule. The reason for this delay was that we wanted to make critical new metadata fields available, including resource URLs and titles with markup.

Crossref metadata is always openly available via our API. We recommend you use this method to incrementally add new and updated records once you’re up and running with an annual public data file. If you’re interested in more frequent and regular “full-file” downloads, consider subscribing to our Metadata Plus program. Plus subscribers have access to monthly snapshots in JSON and XML formats.

Every year our metadata corpus grows. The 2020 file was 65GB and held 112 million records; 2021 came in at 102GB and 120 million records. This year the file weighs in at 160 GB and contains metadata for 134 million records, or all Crossref records registered up to and including April 30, 2022.

Tips for using the torrent and retrieving incremental updates

Use the torrent if you want all of these records. Everyone is welcome to the metadata, but it will be much faster for you and much easier on our APIs to get so many records in one file. Here are some tips on how to work with the file.
Use the REST API to incrementally add new and updated records once you’ve got the initial file. Here is how to get started (and avoid getting blocked in your enthusiasm to use all this great metadata!).
‘Limited’ and ‘closed’ references are not included in the file or our open APIs. And while bibliographic metadata is generally required, lots of metadata is optional, so that records will vary in quality and completeness.

Questions, comments, and feedback are welcome at support@crossref.org.

Amendments to membership terms to open reference distribution and include UK jurisdiction

Ginny Hendricks — Mon, 04 Apr 2022 00:00:00 +0000

Tl;dr

Forthcoming amendments to Crossref’s membership terms will include:

Removal of ‘reference distribution preference’ policy: all references in Crossref will be treated as open metadata from 3rd June 2022.
An addition to sanctions jurisdictions: the United Kingdom will be added to sanctions jurisdictions that Crossref needs to comply with.

Sponsors and members have been emailed today with the 60-day notice needed for changes in terms.

Reference distribution preferences

In 2017, when we consolidated our metadata services under Metadata Plus, we made it possible for members to set a preference for the distribution of references to Open, Limited, or Closed. Prior to the 2017 change, we acted as a broker of 1:1 feeds of parts of metadata for parts of our community - clearly a role that was not scalable.

We are well underway to pay back technical debt on our 20-year-old metadata system and effectively rearchitect it. We therefore recently needed to decide whether to rewrite code for a capability that hardly any member was using. Just one member has chosen Closed, and Limited was the default for a while, but the vast majority of our members now prefer Open distribution. Additionally, bringing references in line with other metadata significantly simplifies this work and will speed up the technical development.

The Crossref Board discussed the issue in our meeting on 10th March 2022, and voted to remove the reference distribution policy set in 2017. All board motions go on our website, and the wording of this particular motion is:

Resolve that, based on a technical assessment, we will change the reference distribution policy so that all references registered with Crossref are treated the same as other metadata, following a planned transition.

This motion means that 60 days from today—3rd June 2022—all references in Crossref will be open and after that available through our API. As with all other metadata, if members cannot make references available, or do not want them openly distributed, they can choose not to deposit them. However, depositing references is necessary in order to retrieve citation links from our members-only Cited-by API.

Check the documentation for information on how to deposit references and use Cited-by. Also look up your participation dashboard to see if you are already registering references and your current distribution setting.

Sanctions jurisdictions

Following the UK departing from the European Union, we needed to add the United Kingdom as a separate jurisdiction that we must comply with, alongside the United Nations, the United States of America, and the European Union.

Where there are either relevant financial or governance-based sanctions against individuals, organisations, geographic regions, or whole countries, Crossref is legally bound to comply with these four different jurisdictions. These laws supersede our own governing bylaws.

We have launched a new operations and sustainability section of our website, which includes a sanctions page which we will keep updated with any changes and actions we’re taking.

The specific terms that will change

The complete membership terms are online here. In the text below, any text to be removed is shown in ‘strike-through’ text and any additions are in bold. These new terms will be in effect from 3rd June 2022.

5. Distribution of Metadata by Crossref. Without limiting the provisions of Section 4 above, the Member acknowledges and agrees that~~, subject to the Member’s reference distribution preference,~~all Metadata and Identifiers registered with Crossref are made available for reuse without restriction through (but not limited to) public APIs and search interfaces, which enhances discoverability of Content. Metadata and Identifiers may also be licensed to third party subscribers along with an agreement for Crossref to provide third parties with certain higher levels of support and service. For the avoidance of doubt, the scope of Crossref’s distribution (if any) of a Member’s references is based on such Member’s reference distribution preference, as established by the Member in accordance with the “Reference Distribution” page on the Website.

20. Compliance. Each of the Member and Crossref shall perform under this Agreement in compliance with all laws, rules, and regulations of any jurisdiction which is or may be applicable to its business and activities, including anti-corruption, copyright, privacy, and data protection laws, rules, and regulations.

The Member warrants that neither it nor any of its affiliates, officers, directors, employees, or members is (i) a person whose name appears on the list of Specially Designated Nationals and Blocked Persons published by the Office of Foreign Assets Control, U.S. Department of Treasury (“OFAC”), (ii) a department, agency or instrumentality of, or is otherwise controlled by or acting on behalf of, directly or indirectly, any such person; (iii) a department, agency, or instrumentality of the government of a country subject to comprehensive U.S. economic sanctions administered by OFAC; or (iv) is subject to sanctions by the United Nations, the United Kingdom, or the European Union.

As always, please get in touch with us via member@crossref.org with any questions.

With a little help from your Crossref friends: Better metadata

Jennifer Kemp — Thu, 31 Mar 2022 00:00:00 +0000

We talk so much about more and better metadata that a reasonable question might be: what is Crossref doing to help?

Members and their service partners do the heavy lifting to provide Crossref with metadata and we don’t change what is supplied to us. One reason we don’t is because members can and often do change their records (important note: updated records do not incur fees!). However, we do a fair amount of behind the scenes work to check and report on the metadata as well as to add context and relationships. As a result, some of what you see in the metadata (and some of what you don’t) is facilitated, added or updated by Crossref.

Much of the work is automated but some of it still requires manual intervention (sound familiar?). Here’s an overview:

Before registration

Our open APIs allow for Crossref metadata to be used throughout research and scholarly communications systems and services, before and after records are registered with us. Those who have used a search function in something like a manuscript submission system, rather than having to hand key or copy and paste the information, will appreciate how these integrations reduce time, effort and the likelihood of errors in collecting metadata well before it gets to Crossref.

For one example, it’s very common for members to use the metadata to add DOIs to reference lists when preparing deposits. Of course, new members first need a prefix (and a memberID and name, but more on that later) in order to register content. We also provide a suffix generator for help in constructing DOIs. If you’re not sure how best to make use of existing metadata in deposits, we’ve got a few options for you. Questions are welcome.

We don’t often put it this way but we should: Crossref members rely on the metadata as much, if not more, than the rest of the community. More and better metadata directly benefits our members.

Upon registration

There are a number of ways we work with the metadata when deposits are received.

Checking for uniqueness In order to avoid duplicate records, we check to make sure that a title or work hasn’t been registered before. Depending on what we find, a conflict report or failed registration may result.
Adding DOIs to references When references come to us without DOIs, we’ll try to match and add them.
ORCID auto-update We automatically update authors’ ORCID records (with their permission of course) whenever deposits include their ORCID iDs.
Preprint to VoR reports We compare title information and provide notifications of matching records to members depositing preprints, to help them fulfill their obligation to link to Versions of Record (VoRs), where they exist.
Relationships Like preprint to VoR links, components are another kind of relationship. These might be supplementary material such as figures we can link to the ‘parent’ record.
Funding data When members register only a funder name as part of the information on who funded the work, we’ll try to match it to its identifier from the Funder Registry, to support better linking between funders and works.
Timestamps We add date-times for first created and last updated to member-supplied timestamps.
Count of references That’s right, we count all the references for each record that includes them and add the total to the metadata.

After registration

Once registered, we check, report on and update metadata in a few ways.

Link checking We email each member a monthly Resolution Report with details of the number of failed and successful resolutions for their DOIs. If someone in the community reports a DOI that isn’t registered, we email the member a DOI Error Report.
Citation counts and matches Citation counts for records of members participating in our Cited-by service are openly available in our REST API. The matching citations themselves are available to members, for their own records only.
Title transfers Title, prefix and DOI transfers are common and require assistance from our team.
MemberID It’s not uncommon for members to have more than one prefix. The memberID means users of the REST API can query for records associated with all of a member’s prefixes.
Digital preservation We handle the infrequent but critical update of URLs that are necessary when titles are triggered for digital preservation. We also preserve the metadata itself, with both CLOCKSS and Portico.

Of course, since records are often redeposited with updates (note, deposit fees are only charged once per record), some of these processes on our side are repeated as necessary.

This list isn’t exhaustive and other needs and opportunities will emerge. For example, we are looking at matching to add ROR IDs, as we do for funderIDs, and doing some research into how we might determine and assert subject classifications at the work-level. If you’re interested in more about this kind of work, you’ll want to read this recent post by my Labs colleague Dominika on matching grants to outputs.

Get in touch if you have questions or for more information.

A Registry of Editorial Boards - a new trust signal for scholarly communications?

Fabienne Michaud — Wed, 09 Mar 2022 00:00:00 +0000

Background

Perhaps, like us, you’ve noticed that it is not always easy to find information on who is on a journal’s editorial board and, when you do, it is often unclear when it was last updated. The editorial board details might be displayed in multiple places (such as the publisher’s website and the platform where the content is hosted) which may or may not be in sync and retrieving this information for any kind of analysis always requires manually checking and exporting the data from a website (as illustrated by the Open Editors research and its dataset).

For well-established as well as early career researchers, membership of an editorial board demonstrates their contribution to their community, brings prestige, improves (or maintains) their professional profile and often increases their chances of being published.

Whilst most journal websites only give the names of the editors, others possibly add a country, some include affiliations, very few link to a professional profile, an ORCID ID. Even when it’s clear when the editorial board details were updated, it’s hardly ever possible to find past editorial boards information and almost none lists declarations of competing interest.

We hear of instances where a researcher’s name has been listed on the board of a journal without their knowledge or agreement, potentially to deceive other researchers into submitting their manuscripts. Regular reports of impersonation, nepotism, collusion and conflicts of interest have become a cause for concern.

Similarly, recent studies on gender representation and gender and geographical disparity on editorial boards have highlighted the need to do better in this area and provide trusted, reliable and coherent information on editorial board members in order to add transparency, prevent unethical behaviour, maintain trust, promote and support research integrity.

Registry of Editorial Boards

We are proposing the creation of some form of Registry of Editorial Boards to encourage best practice around editorial boards’ information and governance that can easily be accessed and used by the community.

What we have in mind

A Registry of Editorial Boards could be a new trust-signal for Crossref members and details would be included on a member’s Participation Report.

Crossref members would register and maintain this information for their journal titles in a similar way as they currently manage their metadata. Only the owner of the title, or their trusted service provider, would be able to update it. Editors would be linked by ORCID iD and ROR and Crossref would use ‘autoupdate’ to push editorship information to ORCID profiles, saving researchers time. The information would be made available via Crossref’s API.

This new service would introduce more transparency and automation to the editorial process and connect content platforms (i.e. peer review management systems, publishers’ websites, ORCID and other author register systems, ROR, bibliographic databases, etc.) and make available current and historical information on editorial boards including metadata on the editorial boards’ full affiliations.

The benefits for the community

The benefits would be wide-ranging for the different stakeholders in the scholarly communications community, from publishers, researchers, institutions, funders, bibliometricians to librarians including:

providing those involved in the peer review process and research ethics a single, authoritative and up-to-date resource on editorial boards
reducing fraudulent claims to be or to have been on an editorial board of a publication in order to be published or publish others
connecting and automating editorship role updates with e.g. ORCID, ROR, etc.
generating a detailed analysis of the publication practices of editorial board members and their close contacts
assessing any relationships between authors, reviewers and editorial board members for conflict of interest, etc.
supporting researchers responding to a request to join an editorial board, making proactive approaches to a journal or wanting to ensure that an editorial board is representative of its community and assess its levels of diversity and inclusivity
providing increased visibility to researchers, particularly to early career researchers

Your feedback

Before we progress further, we would like to fully understand what the needs of the community are and whether members would be willing and have the capacity to participate and contribute regularly in registering and maintaining details of their editorial boards.

✏️ Please let us know what your thoughts and experience are with editorial boards by completing this brief survey by 31 March 2022.

A ROR-some update to our API

Rachael Lammey — Wed, 19 Jan 2022 00:00:00 +0000

Earlier this year, Ginny posted an exciting update on Crossref’s progress with adopting ROR, the Research Organization Registry for affiliations, announcing that we’d started the collection of ROR identifiers in our metadata input schema. 🦁

The capacity to accept ROR IDs to help reliably identify institutions is really important but the real value comes from their open availability alongside the other metadata registered with us, such as for publications like journal articles, book chapters, preprints, and for other objects such as grants. So today’s news is that ROR IDs are now connected in Crossref metadata and openly available via our APIs. 🎉

This means ROR can be used by and within all the tools services that integrate with Crossref APIs to analyse, search, recommend, or evaluate research. It’s an important element of the Research Nexus, our vision of a fully connected open research ecosystem, and helps identify, share, and link the affiliations of those producing and publishing different types of research or receiving grants.

Now that this metadata is available, it helps confer the downstream benefits of ROR for different (and interconnected) groups:

It makes it easier for institutions to find and measure their research output by the articles their researchers have published, or perhaps make it easier to track the grants they’ve received.
Funders need to be able to discover and track the research and researchers they have supported.
Academic librarians need to easily find all of the publications associated with their campus.
Journals need to know where authors are affiliated so they can determine eligibility for institutionally sponsored publishing agreements.
Editors can use more accurate information on author and reviewer institutions during the peer review process, which can help avoid potential conflicts of interest.

Those are just a handful of use cases, which is why disseminating ROR affiliation identifiers via our APIs is so important; it lets others choose to do what they need to with the information, without restriction.

The story so far

A growing number of our members have started to include ROR in the metadata they register with us, so we’re excited to be able to see this via simple API queries.

At the time of writing we can see nearly 4,000 RORs being registered by these 21 members (we’ve removed test accounts). Note that many of these are being baked into metadata being registered for grant records, also recently released and now findable through the REST API:

"Wellcome": 2821,
"Natural Resources Canada/CMSS/Information Management": 277,
"University of Szeged": 139,
"RTI Press": 104,
"American Cancer Society": 103,
"University of Missouri Libraries": 77,
"Keldysh Institute of Applied Mathematics": 52,
"Boise State University, Albertsons Library": 52,
"Australian Research Data Commons (ARDC)": 52,
"The Neurofibromatosis Therapeutic Acceleration Program": 49,
"Boise State University": 12,
"The ALS Association": 11,
"Children's Tumor Foundation": 9,
"Episteme Health Inc": 3,
"The University of the Witwatersrand": 2,
"Office of Scientific and Technical Information": 2,
"AGH University of Science and Technology Press": 2,
"York University Libraries": 1,
"SZTEPress": 1,
"Masaryk University Press": 1,
"Institut für Germanistik der Universität Szeged": 1,

Our grants schema accommodated ROR first, so it’s the funder members and grant records that dominate the adoption of ROR… so far! But there are a few articles and reports there too already. These record types include ROR in their records:

"Grant": 3047,
"Report": 382,
"Dissertation": 164,
"Journal Article": 140,
"Conference Paper": 22,
"Posted Content": 12,
"Dataset": 7,
"Monograph": 6,
"Book": 3,
"Chapter": 2,
"Proceedings Series": 1,
"Peer Review": 1,
"Journal Issue": 1,
"Book Set": 1,
"Book Series": 1

We can currently see 205 different ROR IDs in Crossref metadata, with the most frequently provided ROR ID being: https://ror.org/02jx3x895, or University College London as it’s also known as.

If you’re a Crossref member keen to assert affiliation identification in your content, our recent webinar, Working with ROR as a Crossref member: what you need to know, covers all the detail.

Interested in using the information? Dig into our REST API documentation and into the API itself, use the polite pool if you can (i.e. identify yourself). There’s also a wealth of information on the ROR support site or being shared among integrators in the growing ROR community.

Join us in doing more with ROR!

Come and get your grant metadata!

Rachael Lammey — Mon, 08 Nov 2021 00:00:00 +0000

Tl;dr: Metadata for the (currently 26,000) grants that have been registered by our funder members is now available via the REST API. This is quite a milestone in our program to include funding in Crossref infrastructure and a step forward in our mission to connect all.the.things. This post gives you all the queries you might need to satisfy your curiosity and start to see what’s possible with deeper analysis. So have the look and see what useful things you can discover.

How it started

Back in 2017 we posted the outcomes of some discussions with a newly-reformed Funder Advisory Group, plotting Crossref’s path. In 2018, Wellcome described their rationale for supporting the grants effort with the help of Europe PMC, and in 2019 the sub-groups of the Advisory Board put out a call for feedback on the metadata plan as the fee model they created was also approved by our board.

Since late 2019, research funders have been registering metadata and identifiers for their grants with us. We currently have a healthy 26k grants registered with us, via 13 funding organisations. I’d specifically highlight Wellcome for volume (registering via Europe PMC), and the Australian Research Data Commons (ARDC) who was the first funder that included ROR IDs in their grant metadata, really getting the value of connecting all related entities and contributors.

The reasons for registering grants with Crossref? Let’s recap:

Support of open data and information about grants
Streamlined discovery of funded content
Improved analytics and data quality
More complete picture of outputs and impact
Better value from investments in reporting services
Improved timeliness, completeness and accuracy of reporting: save time for researchers
More complete information to support analysis and evaluation without relying on manual data entry

How it’s going

For grant information to be used, it’s key that it is is openly available and disseminated as widely as possible. That work starts with funders registering their grants, and continues with us. Now that we’ve completed the REST API’s Elasticsearch migration, we’re happy to announce that all our grant information is now available via our REST API.

Here’s a snippet of the kind of metadata you can see related to the grants registered with us. This is information related to grant record https://doi.org/10.35802/218300, found using this request (https://api.crossref.org/works/10.35802/218300) which you can use to see the full metadata record:

"publisher": "Wellcome",
"award": "107769",
"DOI": "10.35802/107769",
"type": "grant",
"created": {
"date-parts": [
[
2019,
9,
25
]
],
"date-time": "2019-09-25T07:17:20Z",
"timestamp": 1569395840000
},
"source": "Crossref",
"prefix": "10.35802",
"member": "13928",
"project": [
{
"project-title": [
{
"title": "Initiative to Develop African Research Leaders (IDeAL)"
}
],
"project-description": [
{
"description": "Research is key in tackling the heath challenges that Africa faces. In KWTRP we have been committed to building sustainable capacity alongside an active and diverse research programme covering social science, health services research, epidemiology, laboratory science including molecular biology and bioinformatics. Our strategy has been successful in delivering high quality PhD training, leveraging individual funding and programme funding in order to place students in productive groups and provide high quality supervision and mentorship. Here we plan to consolidate and build on these outputs to address long-term sustainability. We will emphasise the full career path needed to generate research leaders. KWTRP aims to address capacity building for research through an initiative that employs a progressive and long term outlook in the development of local research leadership. The overall aim of the \"Initiative to Develop African Research Leaders\" (IDeAL) is to build a critical mass of African researchers who are technically proficient as scientists and well-equipped to independently lead science at international level, able to engage with funders, policy makers and governments, and to act as supervisors and mentors for the next generation of researchers.",
"language": "en"
},

If you dig in, you can see information about the project, investigators (including their ORCID iDs), the funder, award type, amount, description of the grant, and a link to the public page showing information about the grant. More information on the required and optional fields is available in our grants markup guide.

Here are some examples of the kind of things you can now ask:

Show me who is registering grants:

https://api.crossref.org/types/grant/works?rows=0&facet=funder-name:*

Show me all of the grants registered by Wellcome:

https://api.crossref.org/works?query.funder-name=Wellcome&filter=type:grant

Show me all of the grants associated with the investigator name Caldas:

https://api.crossref.org/works?query.contributor=Caldas&filter=type:grant

And bibliographic queries finding entries in…

Award number:

https://api.crossref.org/works?query.bibliographic=7196&filter=type:grant

Project title:

https://api.crossref.org/works?query.bibliographic=RIZ1&filter=type:grant

More to do

This is a milestone but it’s not the end of the story. We have more to add relationships, encourage the use of this metadata amongst publishers and their platforms, and to add grant records to our tools such as Participation Reports and Metadata Search. But in the meantime, feel free to get in touch if you have queries about registering grants with us or about using the related metadata in your tools and services.

This information will grow over time as more funders join Crossref and add their grant metadata and as more analyses is possible. We’re looking forward to the next steps!

Now is the time to work together toward open infrastructures for scholarly metadata

Ginny Hendricks — Wed, 27 Oct 2021 00:00:00 +0000

Now is the time to work together toward open infrastructures for scholarly metadata

The closure of Microsoft Academic — and its records not covered by Crossref — was a wake-up call for the scholarly community. Published on the LSE Impact Blog in October 2021, this piece draws lessons from that moment and makes the case for open, collectively governed, and sustainable metadata infrastructure.

Strategists

Understand why open scholarly infrastructure is fragile — and what makes it resilient. How the loss of Microsoft Academic revealed gaps in coverage, governance, and sustainability, and why POSI offers a framework for building something more durable.

Decision-makers

Know what your organisation should commit to. A direct call to action for publishers, funders, institutions, and infrastructure providers — and why mandating open, FAIR metadata is essential to the health of the scholarly record.

Practitioners

See the gaps and how to fill them. What the Microsoft Academic coverage data revealed about grey literature and Global South scholarship, and how open metadata workflows and full-text access can address those gaps.

What this piece covers

The Microsoft Academic closure — what was lost, and what the coverage gap revealed about equity and representation in open scholarly infrastructure
Four lessons learned — why metadata infrastructure must be POSI-compliant, collaborative, supported by systematic policy, and paired with open full-text access
A call to action for each stakeholder group:
- Publishers — deposit complete metadata (references, abstracts) in open infrastructures; support the Initiatives for Open Citations and Open Abstracts
- Researchers — choose journals that offer open access to both full text and complete, validated metadata
- Funding agencies — mandate that metadata from funded research be made openly available
- Institutions and libraries — require complete, open metadata availability in contracts with publishers
- Infrastructure and service providers — simplify metadata deposition for smaller publishers with limited technical capacity
- Metadata disseminators — ensure enriched metadata is openly available with full provenance using common standards and open licences

Read the article

Read on LSE Impact Blog

Lesson learned, the hard way: Let’s not do that again!

Isaac Farley — Wed, 08 Sep 2021 00:00:00 +0000

TL;DR

We missed an error that led to resource resolution URLs of some 500,000+ records to be incorrectly updated. We have reverted the incorrect resolution URLs affected by this problem. And, we’re putting in place checks and changes in our processes to ensure this does not happen again.

How we got here

Our technical support team was contacted in late June by Wiley about updating resolution URLs for their content. It’s a common request of our technical support team, one meant to make the URL update process more efficient, but this was a particularly large request. Shortly thereafter, we were provided with nearly 1,200 separate files by Atypon on behalf of Wiley in order to update the resolution URLs of ~9 million records. We manually spot checked over 50 of these files, because, prior to this issue, our technical support team did not have a mechanism to automatically check for errors. That labor intensive review did not turn up any problems. That is, those 50 samples had no errors with the headers, like were found later.

Among the files we didn’t check, there were headers included in the files with different owning fromPrefix and acquiring toPrefix members’ DOI prefixes. In a URL update request, the prefixes should always be the same.

And still other files included requests to update records with DOIs that had never even been registered. Here are some examples:

_{H:email=support@crossref.org;fromPrefix=10.5555;toPrefix=10.5555

10.5555/doi1 http://www.newurl.com/whatever

10.5555/doi2 http://www.newurl.com/whatever2}

In the example above, these fictional DOIs are both under prefix 10.5555. Thus, the result of this request will ONLY be that the resolution URLs of DOI 10.5555/doi1 and 10.5555/doi2 are updated in the metadata.

_{H:email=support@crossref.org;fromPrefix=10.5555;toPrefix=10.9876

10.5555/doi1 http://www.newurl.com/whatever

10.5555/doi2 http://www.newurl.com/whatever2}

In this second example, these fictional DOIs are both under prefix 10.5555, but because the toPrefix in the header differs from the fromPrefix, the result of this request will be that the resolution URLs of 10.5555/doi1 and 10.5555/doi2 are updated in the metadata AND the owning prefix of both records will be transferred from prefix 10.5555 to prefix 10.9876.

We kicked off the URL update request on 30 June and all legitimate DOIs whose files were free of errors were updated by 7 July (yes, it takes about a week to update the resolution URLs for ~9 million records).

On 9 July, Peter Strickland of the International Union of Crystallography, one of 22 members affected by this mistake, contacted us to enquire how/why much of their content was resolving to incorrect URLs and why ownership of their content appeared within our search interface to be Wiley. Peter was rightly concerned. We were, too. Our technical support team quickly elevated this issue, because, frankly, this is not the first time our finicky URL update process has caused unwanted metadata updates, albeit not quite at this volume.

How we investigated the problem

We rallied our internal team. We investigated and discovered that we believed that some ~600,000 DOIs were erroneously included and updated in the requested 1,200 files. We later extended that estimate to include other conditions, in order to be as cautious as we could, to over 1 million DOIs. In the end, we determined that the incorrect files attempted updates of 1,228,041 DOIs. Due to the errors in the files (i.e., erroneous headers and non-registered DOIs), we only actually updated and then reverted 520,512 DOIs. The other 700,000+ DOIs were never updated (because of errors in the original files provided to us) or simply had never been registered with us.

Prior to this mistake, Crossref had never reverted a member’s metadata update before. To be clear, and as I said above, we have had other URL update mistakes over the years, like this one; they were just smaller in scale. We knew there were holes in our process that needed to be plugged. And we knew we needed a better solution for members to manage these updates themselves without our manual intervention. So, while there were mistakes made in the files supplied to us, this was our error and we’re fixing it; more on that below.

For this situation, we quickly realized that reversion of the metadata update was the best option for us, albeit we did not have an existing process in place to execute that reversion. That’s because we only keep the current version of each metadata record. We couldn’t back out of the change; we couldn’t simply restore these records to the metadata registered with us as of late June, because we no longer had an easily accessible, central record of those previous resolution URLs. What we did have was a record of all the previous submissions made against each DOI, so our technical team, focused their efforts there.

How we fixed all those records

We had two errors to correct: the ownership transfers (those records that had inadvertent and mismatched from/to prefixes) and the incorrect resolution URLs. We reverted all of the ownership transfers on 9 July and then double and triple checked that ownership during the week of 12 July to ensure we didn’t miss anything.

The resolution reversion was more complicated. We invested in creating a patch to identify the records that had been updated by our team, and then extract the last legitimate resolution URL registered with us by the owning member in order to revert the metadata for each record. In order to provide confidence that this mistake was contained, we also built a check into the patch to ensure that those DOIs that did have their ownership temporarily transferred were not updated during the few days that ownership was incorrect. That check helped us determine that none of the 520,512 DOIs were incorrectly updated beyond this mistaken URL update request.

The technical team built and tested this patch. The tests turned up gaps in the patch, so we refined it during the week of 2021 July 12. We kicked off the reversion of these records on Monday, 19 July at 20:05 UTC and the patch completed all reversions at 20:14 UTC, Thursday, 22 July.

In the end, we successfully reverted all of the resolution URLs for those 520,512 DOIs we identified; provided daily updates and apologies to the 22 affected members; together we worked some longer hours; and persevered.

Ed updates everyone internally on the situation and thanks all the people who worked together to resolve the issue

Next up

We don’t want this to ever happen again. Like, never. We clearly need to make changes to our internal processes to prevent this in the future.

Here’s what’s ahead:

We are building a checker that we can run URL update files through to automate and our checks. This means we will be able to check every single file in a large batch, rather than relying on manual and labor intensive spot-checking;
As said above, one compounding issue in this mistake was the mismatched from/to prefixes in the file headers. Our technical support team uses the same file headers to transfer ownership/stewardship of a record or set of records between members AND to update resolution URLs. These two tasks are almost never legitimately completed in the same file. That is, there is usually a lag between ownership transfers and resolution URL updates (most members will request an ownership transfer and then a month or two later update their URLs). Because of this, simply decoupling these two tasks (feel free to follow our work at this link) would help eliminate a glaring risk, so we’re working on that too;
Lastly, we’re researching ways we can streamline resource resolution URL updates. You can also monitor our progress on this one. No promises or specifics yet, but we’re eager to reduce toil on our technical support team, avoid problems like this one, and provide members safe and straightforward ways to better update your metadata.

Thanks for the support of the whole Crossref team and our community - and for reading this far! Never a dull moment…

Some rip-RORing news for affiliation metadata

Ginny Hendricks — Mon, 26 Jul 2021 00:00:00 +0000

We’ve just added to our input schema the ability to include affiliation information using ROR identifiers. Members who register content using XML can now include ROR IDs, and we’ll add the capability to our manual content registration form, participation reports, and metadata retrieval APIs in the near future. And we are inviting members to a Crossref/ROR webinar on 29th September at 3pm UTC.

The background

We’ve been working on the Research Organization Registry (ROR) as a community initiative for the last few years. Along with the California Digital Library and DataCite, our staff has been involved in setting the strategy, planning governance and sustainability, developing technical infrastructure, hiring/loaning staff, and engaging with people in person and online. In our view, it’s the best current model of a collaborative initiative between like-minded open scholarly infrastructure (OSI) organisations.

Last year, Project Manager Maria Gould described the case for publishers adopting ROR and ROR was ranked the number one priority at our last in-person annual meeting. Now it’s time that Crossref’s services themselves took up the baton to meet the growing demand.

The inclusion of ROR in the Crossref metadata will help everyone in the scholarly ecosystem make critical connections more easily. For example, research institutions need to monitor and measure their output by the articles and other resources their researchers have produced. Journals need to know with which institutions authors are affiliated to determine eligibility for institutionally sponsored publishing agreements. Funders need to be able to discover and track the research and researchers they have supported. Academic librarians need to easily find all of the publications associated with their campus.

Earlier this month, GRID and ROR announced that after working together to seed the community-run Research Organization Registry, GRID would be retiring from public service and handing the proverbial torch over to ROR as the scholarly community’s reliable universal open identifier for affiliations. That means that our members who have been using GRID now need to consider their move to ROR and think about how they can add ROR IDs into the metadata that they manage and share through Crossref.

The plan

We’ve been able to include ROR IDs for our grant metadata schema as affiliation information for two years, since July 2019. And the Australia Research Data Commons (ARDC) was the first member to add ROR IDs to the Crossref system in 2020. In early July, we completed the work to accept ROR IDs for affiliation assertions for all other types of records with an affiliation or institution element, such as journal articles, book chapters, preprints, datasets, dissertations, and many more.

Next, we will commence the plans to support ROR in our other tools and services, such as Participation Reports. We’ll work on alignment with the Open Funder Registry and share our plans to collect the information via the new user interface we’re developing for registering and managing metadata. Open Journal Systems (OJS) already has a ROR Plugin, developed by the German National Library of Science and Technology (TIB). This supports the collection of ROR IDs and future releases of this plugin and the OJS DOI plugin will allow including ROR IDs in the metadata sent to Crossref, to support thousands of our members to share ROR IDs via their Crossref metadata. We also aim to add ROR to our metadata retrieval options, including the REST API, which recently saw the start of an unblocking with our move to a more robust technical foundation.

The call for participation

Many Crossref publishers, funders, and service providers are already planning to integrate ROR with their systems, map their affiliation data to ROR, and include ROR in Crossref metadata. In addition to publishers and funders, libraries, repositories, and other stakeholders are developing support for ROR. For example, the Plan S Journal Checker tool uses ROR IDs to let people check whether a particular journal is compliant with an author’s funder and institutional open access policies. In addition, the ROR website shows a growing list of active and in-progress ROR integrations.

Crossref members registering research grants via Altum’s ProposalCentral system can already add ROR IDs. Now those registering articles, books, preprints, datasets, dissertations, and other research objects, can start including much clearer and all-important affiliation metadata as part of their content registration going forward. As with all newly-introduced metadata elements, we recommend adding ROR IDs from now and ongoing, but planning a distinct project to backfill older records. We know that more than 80% of records have been updated and enriched at least once with additional and cleaner metadata, so as members do this routinely, they can include ROR IDs alongside updating URLs, license or funding information, and other metadata.

For information on how ROR will be supported in the Crossref metadata, take a look at our latest schema release (version 5.3.0) or in this journal article example XML.

Join the discussion in our forum below and register for the Crossref/ROR webinar on September 29th at 3pm UTC to learn all you need to know about incorporating ROR into your Crossref metadata.

RFP: Help evaluate the reach and effects of metadata

Jennifer Kemp — Wed, 21 Jul 2021 00:00:00 +0000

UPDATE, 14 October 2021:

We received several excellent proposals in response to this RFP and we’d like to thank everyone involved for their time and enthusiasm.

We are excited to announce the two projects that have been selected, to run through early 2023. Stay tuned!

With or Without: Measuring Impacts of Books Metadata
This project will test the premise that academic books metadata improves discoverability and usage by assessing the impact of book chapter records with DOIs (unique from metadata associated with the entire book) with associated chapter and book attributes. The study aims to prove or disprove its hypothesis and rank metadata attributes by their association with successful content discovery and access. The findings will be considered alongside similar metadata research in order to develop a metadata efficacy framework, which can be used to determine the return on metadata investments by publishers and service providers.

Lettie Y. Conrad and Michelle Urberg, Independent consultants

Metadata For Everyone
This project will explore the metadata quality, consistency and completeness from various individual journals and communities. The project will pay special attention to elements that are most likely to vary across cultures, such as names and those that are potentially multi-lingual, with the understanding that metadata issues do not affect nor impact all communities in the same way.

Juan Pablo Alperin, Associate Director of Research, Public Knowledge Project & Co-Director, Scholarly Communications Lab
Mike Nason, Scholarly Communications & Publishing Librarian, University of New Bruinswick Libraries
Marco Tullney, Head of Publishing Services & Coordination Open Access at TIB – Leibniz Information Centre for Science and Technology

We’re excited (and a little nervous) to launch a new research project designed to assess the effects of metadata on research communications. We’re expecting this effort to be a significant contribution to the existing research on the topic and we’re really looking forward to getting started. We’re also a little nervous because of course we don’t know what the conclusions will be (after all, if we did, we wouldn’t be starting this project).

Assume nothing

It seems logical and very widely accepted that more and better metadata leads to good things. Does it? If so, how and how do we know that? What does the ‘before and after’ look like when metadata is corrected or enhanced? There are so many questions, so many stakeholders and enough variation around record types (books come to mind) and disciplines (hello citation styles) that the topic warrants all the attention it gets and more. This project is designed to be very broad in scope, sampling from various criteria, and is expected to last about a year.

Interested in getting involved?

If you’re a researcher involved in scientometrics or bibliometrics or if you’re a consultant with experience in original research, please have a read of the RFP and get in touch with a statement of interest by 1st September or with questions in the meantime. We’re looking for an individual, research group or organisation that will work with us over the course of the project to define terms, finalize the approach, analyze the data and communicate the results, whatever they may be.

RFP responses are requested by 1st September so don’t hesitate to get in touch with questions.

If you’re interested in the project but not in responding to the RFP, you may still be able to help. We would appreciate wide circulation of this announcement to help us find qualified respondents to the RFP so please do share this with your network. And, of course, we hope you stay tuned for the outcome of the work. Check back with us on that in about a year…

An Advisory Group for Preprints

Martyn Rittman — Wed, 09 Jun 2021 00:00:00 +0000

We are delighted to announce the formation of a new Advisory Group to support us in improving preprint metadata. Preprints have grown in popularity over the last few years, with increasing focus brought by the need to rapidly disseminate knowledge in the midst of a global pandemic. We have supported metadata deposits for preprints under the record type ‘posted content’ since 2016, and members currently register a total of around 17,000 new preprints metadata records each month.

As preprints develop and different practices arise, we are keen to re-examine the metadata schema: to do this properly we need community input. We want to ensure that the schema is fit for purpose and supports the diversity of ways in which preprints are posted, linked with other objects, and used. Metadata schema need regular review, and this is just one example of a number of areas we are looking to update. Several topics we see as a high priority for preprints are better notification for when a preprint has been withdrawn or removed, accurate recording of versioning, and better indication of preprint server names.

We have invited a number of organisations we know to be active in this area, and are looking forward to some very positive discussions. Participants span five continents and include members who post preprints, indexing services, and others with significant experience in the area of preprints. The first meeting took place earlier this week and brought up a diverse range of themes that will be tackled in future meetings.

Service Provider perspectives: A few minutes with our publisher hosting platforms

Jennifer Kemp — Mon, 24 May 2021 00:00:00 +0000

Service Providers work on behalf of our members by creating, registering, querying and/or displaying metadata. We rely on this group to support our schema as it evolves, to roll out new and updated services to members and to work closely with us on a variety of matters of mutual interest. Many of our Service Providers have been with us since the early days of Crossref. Others have joined as scholarly communications has grown and services have evolved. Though fewer than 20 in number, their impact far outweighs the size of the group.

They, like us, work with a great variety of members and have a broad view into publishing trends. In this post, we focus on views from some of the publishing hosting platform Service Providers, who’ve taken the time to share their thoughts on a few questions:

What is the biggest change you’ve experienced working with publisher metadata over the last few years and how have you adapted to it?

It has become more and more important that not only the DOIs are registered with the minimum of necessary metadata to get the DOIs registered, but that a most complete set of metadata is being sent along – including author identifiers, funding information, abstracts, licenses, to support other Crossref services and improve discoverability.

– de Gruyter

Our clients are increasingly aware of the key role metadata plays in the effective dissemination of research. With an increasing number of published articles and a clear domination of “search engines” and aggregation of content, metadata is the primary means of making sure that publications reach the right audience. Publishers’ value-add includes not just copy editing, formatting, and packaging, but also now creating journal articles for the digital age that are discoverable and well linked to the research corpus. Furthermore, we sense a clear move toward standardization, which goes beyond the structure to introduce standardized semantics: adopting common taxonomies for classifying content in different dimensions. Our response is to introduce effective, automated and consistent services that capture, and surface metadata throughout the value chain from authoring to publication and search.

– Atypon

Highwire’s publishers are always looking to use the latest DTD (Document Type Definition) for the content to stay up to current standards. Currently this would be JATS 1.2. They are choosing to remain current so that they can stay on top of all or new metadata that can enrich their deposits. We have handled this well and offer support for the latest version of DTD when they are released, but some publishers are not always familiar with what can/should be deposited with their content and this can be a learning process for them.

– MPS Limited

How do you explain to clients (and others!) why correct, quality metadata is important?

In the digital age, metadata is the key to enabling effective content consumption. Publications that cannot be effectively discovered are of little value. We can only increase the impact of research with “discoverable” and “machine readable” publications. So ensuring correct and quality metadata is the key to optimizing not only the processing (finding the right journal, editor, reviewers) but also to positioning each publication properly. As the volume of published scientific research increases, article metadata is the way forward — it brings “order” and enables our community to manage this volume.

– Atypon

Highwire always positions itself as “good content in” means “good content out”. This is true for our own content stores. Strong and valid metadata will result in valid and strong deposits. We explain this to all new clients on-boarded with Highwire and the use of current standards and for current client projects where content should/can be enriched through re-load.

– MPS Limited

Getting our journals to care about metadata is a two step process: First, make sure they understand how metadata will help their journal succeed (i.e. why it matters to them). Second, make it easy for them to produce metadata while minimizing the cost, time, or complexity of their workflow. The first step – making a case for why metadata matters – is often easier than you’d think. At the very least, most journal editors understand that metadata, e.g., JATS or DOI registration, is an important signifier of professionalism / prestige. In other words, they see that top journals publish metadata and want the same for their journal. From a more technical standpoint, metadata is important because that’s the format computers understand and, like it or not, the publishing ecosystem relies on computers to deliver all sorts of critical services – such as indexing, archiving, and discoverability. So, if you’re not publishing metadata, you’re likely missing the benefit of these services. The second step – making it easy to produce metadata – is more difficult. Journal editors generally understand metadata matters but often lack the technical skills or resources necessary to create metadata. This is where a platform, such as Scholastica, can be very helpful. Because platforms work with many journals, they can invest in tools to automate the creation of metadata, reducing costs for all their clients. For example, most platforms offer integrations to support automatic DOI registration. At Scholastica, we’re pushing this idea even further with automatic integration to more complicated services such as PubMed Central. By reducing cost and complexity, we can help new or small-budget journals have the same quality metadata normally reserved for large, established journals.

– Scholastica

We are sending other publishers’ metadata to academic libraries and distribution channels. Erroneous metadata will have a direct impact on how discoverable a title may be. The more uniform and correct the metadata, the better it will be indexed in other places.

– de Gruyter

What is the one industry development or trend you’re most excited about for the near future and why?

Open Science and the ability to deliver research with the tools for reproducing it is the most exciting and game changing trend. Technology has enabled the output of science to transition from two-dimensional printed text delivery into globally accessible and responsive web-based delivery. We are now taking the next steps to further leverage web technology to enhance research output with rich assets ranging from audio and video, datasets, executable code, high-resolution imagery, interactive applications and more. As more assets accompany research publications, viewing these assets as modular, individually citable, and reusable becomes a requirement. We are reviewing the whole research output flow from authoring to publishing, and most importantly to its dissemination through the myriad of discovery tools now available.

– Atypon

The move of everything to the cloud – this is changing and improving our infrastructure, our possibility to scale and to stay on top of technological development.

– de Gruyter

Thanks very much to the interviewees for their time and thoughts. We look forward to working with our entire Service Provider group on questions like these and many more. If you’d like more details, you can read about our Service Provider program or contact me for more information.

Doing more with relationships - via Event Data

Martyn Rittman — Fri, 14 May 2021 00:00:00 +0000

Crossref aims to link research together, making related items more findable, increasing transparency, and showing how ideas spread and develop. There are a number of moving parts in this effort: some related to capturing and storing linking information, others to making it available.

By including relationship metadata in Event Data, we are taking a big step to improve the visibility of a large number of links between metadata. We know this is long-promised and we’re pleased that making this valuable metadata available supports a number of important initiatives. We will also be backfilling, so all previously deposited relationships will eventually become available as events. The first step will be to add relationships between items that have DOIs, such as between a research article and a related review report or dataset.

What are relationships?

When members register metadata with us, they have the possibility to identify other works, items, and websites that they know are related. This might be supplementary material or previous versions of a work (especially for preprints and working papers). Equally, identifiers for a protein, gene, or organism used in the research can be included. These are recorded as ‘relationships’ and can be accessed in the same way as the rest of the metadata we hold about registered content.

Some examples

Relationships in the metadata show links to the published article from this bioRxiv preprint. In the Crossref Rest API:

"relation": {
 "is-preprint-of": [
 {
 "id-type": "doi",
 "id": "10.1038/s41467-020-17892-0",
 "asserted-by": "subject"
 }
 ],
 "cites": []
},

And now in Event Data:

"subj": {
 "pid": "https://doi.org/10.1101/2020.05.21.109546",
 "url": "https://doi.org/10.1101/2020.05.21.109546",
 "work_type_id": "posted-content"
},
"obj": {
 "pid": "https://doi.org/10.1038/s41467-020-17892-0",
 "url": "https://doi.org/10.1038/s41467-020-17892-0",
 "method": "doi-literal",
 "verification": "literal",
 "work-type-id": "journal-article"
},

Linking to a dataset in the Dryad Digital Repository by a recent eLife article. In the Crossref metadata:

"relation": {
 "is-supplemented-by": [
 {
 "id-type": "doi",
 "id": "10.5061/dryad.s58qh",
 "asserted-by": "subject"
 }
 ],
 "references": [
 {
 "id-type": "doi",
 "id": "10.5061/dryad.s58qh",
 "asserted-by": "subject"
 }
 ],
 "cites": []
},

And now in Event Data:

"subj": {
 "pid": "https://doi.org/10.7554/elife.19920",
 "url": "https://doi.org/10.7554/elife.19920",
 "work_type_id": "journal-article"
},
"obj": {
 "pid": "https://doi.org/10.5061/dryad.s58qh",
 "url": "https://doi.org/10.5061/dryad.s58qh",
 "method": "doi-literal",
 "verification": "literal",
 "work-type-id": "Dataset"
},

If you are interested in relationships for a single DOI, we still recommend checking the metadata of that record, however Event Data is a great option for looking across multiple records. For example, to check for relationships across a prefix, in a given time period, or for a specific type of relationship.

Data citation

Data citations can be included in data deposits in relationship metadata, usually using the ‘is-supplemented-by’ relationship. By creating an event from each relationship, the links between journal articles and books, and the data they rely on are more visible. This makes the data much easier to locate.

Many datasets have DOIs which are usually recorded with DataCite, meaning you are unlikely to find them via searches of Crossref metadata. Making data citation relationship metadata available in Event Data means it will be available in the same format as citations from datasets to articles (which DataCite sends to Event Data) and citations from articles to datasets from Crossref reference metadata (more to come on this later this year). It also means we will convert this information into Scholix format so that it can be harvested and combined with other sets of Scholix-compliant article/data links. Data citations will therefore be available for the community to identify, share, link and recognise research data. We’re working with initiatives like Make Data Count and STM’s research data program to support the growing uptake of good data citation practices. This is a big step forward in making data citation happen for the community; we have more to do, but Crossref is committed to completing this work as a strategic priority.

What’s next?

In this first stage we are adding relationships that link two objects with a DOI, and later this year we will bring in relationships using other identifiers such as accession numbers and URIs. That will make it more straightforward to ask questions of Event Data such as which organisms have relationships to which works with a DOI.

More info and staying in touch

Find out more about Event Data in our support documentation or check out tickets in the GitLab repo.
Keep informed and ask us anything via our community forum for Event Data discussion

Event Data: A Plan of Action

Martyn Rittman — Mon, 01 Feb 2021 00:00:00 +0000

Event Data uncovers links between Crossref-registered DOIs and diverse places where they are mentioned across the internet. Whereas a citation links one research article to another, events are a way to create links to locations such as news articles, data sets, Wikipedia entries, and social media mentions. We’ve collected events for several years and make them openly available via an API for anyone to access, as well as creating open logs of how we found each event. Some organisations are already using Event Data and we are keen for more to come on board.

Last year we gave an update on Event Data with apologies for being so quiet and a promise of more information at a later date. It’s been some time, so here goes…

I joined Crossref in the middle of last year as a Product Manager and was tasked with looking into Event Data. The first thing I found was a large amount of enthusiasm for Event Data, both within Crossref and further afield. The idea of gathering information beyond the metadata deposited by our members is popular, and creates valuable connections between DOIs and a range of other sources. Interest spans the spectrum of academic research, publishing, bibliometrics, and beyond.

At the same time, I found a project with a very solid, well-built code base but unstable performance. After being put into production in 2018, we didn’t provide sufficient support. Coupled with staff changes and other competing priorities, Event Data hasn’t had the opportunity to live up to early expectations.

To address these issues, we have embarked on a plan to make the server infrastructure more robust, improve monitoring, and make sure that the future of Event Data makes the best use of the resources we have without over-stretching. It means working with the community to determine the most essential aspects of Event Data, and providing support where it’s needed.

The steps below are not necessarily sequential and some depend on the completion of work in other parts of Crossref, but they outline the priorities we have for Event Data in 2021.

The Plan

Stability

Since we put in place our original Event Data infrastructure, the amount of incoming data has grown, and at an ever-increasing rate. In 2017 we were creating 2 million new events per month, that number is now over 20 million. We have known for some time that we need to refresh the infrastructure, but didn’t have the resources to move forward: now we do.

In the first part of the plan we will renew the server infrastructure that underpins Event Data. Maybe not a headline-grabbing move, but the aim is to reduce downtime and pull in missing data. Through improving our monitoring and shortening the response time when things go wrong, we will be able to ensure that events are added on a regular basis and the API can reliably handle requests.

We’ve made the first steps in this direction by upgrading our API infrastructure and making some other tweaks to improve performance. There is still work to do, but we’ve already seen a significant improvement in performance with nearly >99.99% uptime in December.

Consolidation

The second component of the plan is to review performance and data quality. We will evaluate the event sources, update artefacts (such as the lists of publisher landing pages and news websites, and review performance reporting. This will help us to have a better understanding of Event Data in its current form: if the stability component is about improving what comes in and goes and out, this part will give us increased confidence in what Event Data already contains.

Future roadmap

While the two steps above are being carried out, we will revisit the applications of Event Data and talk to organisations that currently use it or have expressed an interest. These conversations will feed into future development in which we will evaluate new sources and other ways to optimize the service.

Central to the roadmap will be continued support of the data citation endpoint in Scholix format, which we run in close collaboration with DataCite. Additionally, we will add new data from relationships between Crossref works, for example a preprint is matched to a journal article, or where there are corrections, retractions, or translations of works.

We expect to continue supporting the current sources of events and where there are organisations with either a strong interest in a particular source or a database of events that they can send directly, we are keen to build collaborations. Event Data, like everything that Crossref does, is a community-based effort.

Staying in touch

To join the conversation about Event Data and keep informed, head over to our Community pages. You can also check out our Gitlab pages. At the end of last year we updated the Education pages where you can learn more about Event Data.

New public data file: 120+ million metadata records

Jennifer Kemp — Tue, 19 Jan 2021 00:00:00 +0000

2020 wasn’t all bad. In April of last year, we released our first public data file. Though Crossref metadata is always openly available––and our board recently cemented this by voting to adopt the Principles of Open Scholarly Infrastructure (POSI)</agic––we’ve decided to release an updated file. This will provide a more efficient way to get such a large volume of records. The file (JSON records, 102.6GB) is now available, with thanks once again to Academic Torrents.

Use of our open APIs continues to grow, as does the metadata. Last year’s file was 112 million records and 65GB. Just nine months later (though it feels longer than that!), the new file is over 120 million records and over 102GB. That’s all of the Crossref records ever registered up to and including January, 7, 2021. We continue to see around 10% growth in records each year––and while journal articles account for most of the volume, preprints and book chapters are two of our fast-growing record types. In addition to the growth in the number of records, many of the records are getting bigger and better as members look at their participation report and understand the value of enriching metadata records for distribution throughout the scholarly ecosystem. Elsevier recently opened its references, enriching over 12 million records. A number of members, including Royal Society, Sage, Emerald, OUP, World Scientific and more have started adding <a href="/blog/open-abstracts-where-are-we/" target="_blank"gicabstracts which now number over 9 million.

Help us help you––using the torrent and other important notes

We decided to release these public data files largely to help support COVID-19 research efforts but of course use cases for Crossref metadata vary widely and a few pointers should help all users:

Use the torrent if you want all of these records. Everyone is welcome to the metadata but it will be much faster for you and much easier on our APIs to get so many records in one file.
Use the REST API to incrementally add new and updated records once you’ve got the initial file. Here is how to get started (and avoid getting blocked in your enthusiasm to use all this great metadata!).
‘Limited’ and ‘closed’ <a href="/education/content-registration/descriptive-metadata/references/#00564/" target="_blank"gicreferences are not included in the file or our open APIs. And, while bibliographic metadata is generally required, lots of metadata is optional, so records will vary in quality and completeness.

Questions, comments and feedback are welcome at support@crossref.org.

Here’s hoping 2021 is a better year for us all! Stay well.

EASE Council Post: Rachael Lammey on the Research Nexus

Rachael Lammey — Mon, 12 Oct 2020 00:00:00 +0000

This blog was initially posted on the European Association of Science Editors (EASE) blog: “EASE Council Post: Rachael Lammey on the Research Nexus”. EASE President Duncan Nicholas accurately introduces it as a whole lot of information and insights about metadata and communication standards into one post…

I was given a wide brief to decide on the topic of my EASE blog, so I thought I’d write one that tries to encompass everything - I’ll explain what I mean by that.

In the past, Crossref has had the opportunity to talk to EASE members about the importance of registering content whose metadata contains important information related to the article. Richer metadata helps to connect the content to other key information such as who wrote it, who it was funded by, the relevant license, the research it cites, any updates to the work such as corrections and retractions, and the data that underpin the research. The use of open persistent identifiers like DOIs, funder IDs, ORCID iDs and ROR IDs are always recommended.

Such rich and connected metadata also helps discoverability of the published research in a different way than just direct access; if you can find something based on looking at the publications related to a particular funder, author, or institution, then there are more ways to come across what you’re looking for. Making links between objects underpinning the research also helps put the research in context and can help further research by making connections to other valuable information that may have been more difficult to make otherwise.

I’ve mentioned the Research Nexus in the title of this post. It’s achieved by declaring relationships between publications and other associated research objects, and from those objects to related publications. The metadata that reveals relationships between research objects can be as informative as the objects themselves. These relationships can assert certain facts that may not be otherwise obvious: this is our goal with the Research Nexus. These relationships and assertions need to exist not just on the web pages of the outputs, but also reflected in a standard way in the metadata so that the information is computer-readable and can be used at scale. As Jennifer Lin, who coined the term, explains:

“Researchers are adopting new tools that create consistency and shareability in their experimental methods. Increasingly, these are viewed as key components in driving reproducibility and replicability. They provide transparency in reporting key methodological and analytical information. They are also used for sharing the artefacts which make up a processing trail for the results: data, material, analytical code, and related software on which the conclusions of the paper rely. Where expert feedback was also shared, such reviews further enrich this record.”

In her Crossref blog, Jennifer goes on to give some examples, including:

Linking to an entire collection of methods and video protocols via Protocols.io
Linking to software and peer reviews in JOSS
Linking to preprint, data, code, source code, peer reviews in Gigascience

I’d include an additional example of linking research to the grant using the grant identifier and associated metadata from the funding section of this PLOS paper (read more about the example from EuroPMC who register grants with Crossref for Wellcome).

These links can be established by adding them into the Crossref relationship metadata schema. The information is then made available to anyone via our open APIs, so that they can easily see and use the information.

In all of these, publishers and other parties are linking to associated research outputs to support the reproducibility and discoverability of content.

The reproducibility point is worth reiterating; EASE has always supported projects to maintain high standards around the review of research, publication standards and ethics, and the reduction of research waste. And connecting articles to data, preprints, protocols, and peer reviews, and making the relationships open for analysis will help achieve this.

We also know that there are work and cost involved in establishing these links, and we’re working on ways to lower the barriers in doing so by:

Revisiting what we charge to encourage best practice. Starting in 2020, we have removed fees for registering vital information on corrections, retractions and other Crossmark metadata. This is timely in light of the updates to the EASE Standardised Retraction form.
We’re also working to remove fees for translations and versions that are linked together by the appropriate relationship metadata so that publishers posting translations or different versions of an article don’t have to pay multiple times for these. Our Membership & Fees Committee is currently reviewing other ways we can support publishers keen to make these connections.
Finding ways to make it easier for publishers to collect this information from authors e.g. submission systems integrations with data repositories to collect robust information on article/data links.
Allowing the registration of peer review metadata for content other than journal articles e.g. books, preprints (coming soon).
Making it easier for publishers to register this information with us at Crossref via the provision of simple to use tools, interfaces and reporting.

The outputs of the research process, such as journal articles, don’t exist in isolation - you only have to look at the interest in the corpus of COVID-19 publications, preprints and associated data to see this. This thinking is also supported by campaigns like Metadata 2020 advocating for “richer, connected, and reusable, open metadata will advance scholarly pursuits for the benefit of society.” The relationships revealed by the Research Nexus may one day help progress research to realise benefits that help us all, providing we all make efforts to effectively support them. More to come…

Open Abstracts: Where are we?

Ludo Waltman — Fri, 25 Sep 2020 00:00:00 +0000

The Initiative for Open Abstracts (I4OA) launched this week. The initiative calls on scholarly publishers to make the abstracts of their publications openly available. More specifically, publishers that work with Crossref to register DOIs for their publications are requested to include abstracts in the metadata they deposit in Crossref. These abstracts will then be made openly available by Crossref. 39 publishers have already agreed to join I4OA and to open their abstracts.

Where are we at the moment in terms of openness of abstracts? For an individual publisher working with Crossref, the percentage of the publisher’s content for which an abstract is available in Crossref can be found in Crossref’s Participation Reports. The chart presented below gives the overall picture (as of September 1, 2020) for medium-sized and large publishers working with Crossref. The vertical axis shows the number of journal articles of a publisher in the period 2018-2020. Because of the large differences between publishers in the number of articles they publish, this axis has a logarithmic scale. The horizontal axis shows the percentage of the articles of a publisher for which an abstract is available in Crossref. The orange dots represent publishers that have agreed to join I4OA. The publishers colored in blue have not yet agreed to join the initiative.

A similar chart was published a few months ago in this blog post on the importance of open abstracts. Comparing the above chart with the one published a few months ago, the first effects of I4OA are already visible. While for most publishers the percentage of abstracts available in Crossref has hardly changed, it has increased from 11% to 95% for the Royal Society, one of the founding publishers of I4OA. This reflects the efforts the Royal Society has made over the past months to improve the availability of abstracts in Crossref for its content, not only for new content but also for existing content. For SAGE, another founding publisher of I4OA, the percentage of abstracts available in Crossref has increased from 38% to 50%. A further increase can be expected to take place in the coming months. The third founding publisher of I4OA, Hindawi, has remained at a stable level, with abstracts being available for 97% of its content.

The above chart shows that many publishers supporting I4OA are already making abstracts available in Crossref. Other publishers do not yet make abstracts available in Crossref but have nevertheless decided to join I4OA. This is the case for Frontiers, PLOS, and Karger, and also for several smaller publishers not visible in the above chart, such as EMBO and Ubiquity Press. These publishers are currently adjusting their workflows and will start submitting abstracts to Crossref soon.

Of the publishers that have not yet joined I4OA, some may not yet be aware of I4OA, while others may need more time to decide whether they will join the initiative. As can be seen in the above chart, most publishers that have not yet joined I4OA do not make abstracts available in Crossref at the moment. However, some publishers have not yet joined I4OA even though they do make abstracts available in Crossref. We hope these publishers will join I4OA soon. By joining the initiative, these publishers would formalize their commitment to openness of abstracts.

None of the publishers in the above chart makes abstracts available in Crossref for 100% of its journal content. Some publishers, such as Copernicus and Hindawi, are close to 100%, but even these publishers have some content for which no abstract is available. Importantly, this does not necessarily mean that publishers have failed to submit abstracts to Crossref for some of their content. Instead, it may simply mean that some of their journal content does not have an abstract. Research articles usually have an abstract, but many other types of content published in journals, such as book reviews, letters, editorials, and corrections, often do not have an abstract. For most publishers, it is therefore impossible to make abstracts available for 100% of their content. Moreover, since Crossref does not distinguish between different types of content published in journals, we cannot provide separate statistics on the availability of abstracts for different types of journal content.

As an example, let’s consider Brill, a publisher that has joined I4OA and that mainly focuses on the humanities and social sciences. Abstracts are available in Crossref for 57% of Brill’s content in the period 2018-2020. This may suggest that Brill has failed to submit abstracts to Crossref for a significant share of its content. However, when we look up journal publications of Brill in 2018 and 2019 in the Web of Science database, abstracts turn out to be available for only 68% of these publications. Assuming that Web of Science has more or less complete coverage of abstracts, this seems to indicate that Brill has already submitted most of its abstracts to Crossref. In fact, Web of Science shows that about a quarter of the publications of Brill are book reviews and that hardly any of these book reviews has an abstract. This illustrates why some publishers, for instance those that publish many book reviews, cannot be expected to get close to 100% availability of abstracts.

Despite the above caveats, it is clear that there is still a long way to go in improving the availability of abstracts in Crossref. As of September 1, 2020, abstracts were available for 21% of all journal articles in Crossref in the period 2018-2020. In Web of Science (Science Citation Index Expanded, Social Sciences Citation Index, and Arts & Humanities Citation Index), 86% of all journal publications in 2018 and 2019 that have a DOI also have an abstract.

Publishers who wish to distribute their abstracts openly through Crossref can include them in the normal content registration process. They can send XML to Crossref (using Crossref’s metadata deposit schema), either directly via HTTPS POST or via the Crossref admin system. For back-content, a resubmission of the full XML is required. In addition, various tools can be used to deposit abstracts. Open Journal Systems (OJS) has a plugin that supports the depositing of abstracts. Metadata Manager also facilitates this, but only for journal articles. Crossref’s web deposit form does not yet support abstracts, but Crossref is working on this.

To keep track of the progress publishers are making in depositing abstracts in Crossref, we plan to publish regular updates of the chart presented above on the I4OA website. We look forward to witnessing the impact of I4OA in the coming months!

Thank you to guest authors Bianca Kramer and Ludo Waltman, as well as the other founding members of I4OA.

Come for a swim in our new pool of Education materials

Laura J Wilkinson — Wed, 29 Apr 2020 00:00:00 +0000

After 20 years in operation, and as our system matures from experimental to foundational infrastructure, it’s time to review our documentation.

Having a solid core of education materials about the why and the how of Crossref is essential in making participation possible, easy, and equitable.

As our system has evolved, our membership has grown and diversified, and so have our tools - both for depositing metadata with Crossref, and for retrieving and making use of it.

Our new documentation gives the full picture, with each chapter explaining an aspect of Crossref and why it matters, followed by instructions on how to participate. As far as possible, these instructions are given for each of our deposit and retrieval methods.

The revised documentation has been edited for use of simple English, and consistent terminology. Specialist vocabulary is explained as it is introduced. Understanding what’s involved across the full range of Crossref services can often seem complicated. This makes the documentation easier for readers, and provides a good basis for human and machine translations.

The chapters and sections are modular, so you can approach and combine them in different ways according to your existing knowledge and what you wish to learn. This Choose Your Own Adventure style means that sections don’t overlap, avoiding problems of repetition and versioning, and helping us to keep the information current.

The revised documentation includes several new topics, including:

The importance of metadata, explaining why you might register metadata for different purposes (discoverability, research integrity, reproducibility, and reporting and assessment)
Persistent identifiers (PIDs), explaining the structure of a DOI, and how you might use DOIs at different levels
Choosing which way to register your content, including suggested DOI registration workflow and suffix generator to make life easier
Introduction to types of metadata, including descriptive (bibliographic), administrative, and structural
Version control, corrections, and retractions, including publication stages and DOIs
Metadata stewardship, including maintaining your metadata, reports, understanding your member obligations, and maintaining your Crossref membership.

This new documentation is part of our efforts to make Crossref participation possible, easy, and rewarding for our members large and small, all over the world. It provides a concrete basis on which to build further education and outreach projects in the future. New members will start to see our paced member onboarding program, introducing them to parts of the documentation as and when it’s useful to them. And like the rest of the Crossref website, it’s all licensed for reuse under CC-BY.

I would like to say a big thank you to the members of the Education Task Force, who helped guide the development of the new documentation, representing a diverse range of Crossref members large and small from around the world:

Anjum Sherasiya - India, Editor-in-Chief of Veterinary World, Crossref Ambassador
Budi Setiawan - Indonesia, Poltekkes Kemenkes Yogyakarta
Caroline Breul - USA, BioOne
Isabel Recavarren - Peru, Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica (CONCYTEC), Crossref Ambassador
Mike Nason - Canada, Public Knowledge Project (PKP) and University of New Brunswick
Nadine van der Merwe - South Africa, Academy of Science of South Africa (ASSAf)
Roberto Camargo - Brazil, Associação Brasileira de Editores Científicos (ABEC)
Sioux Cumming - UK, INASP
Taeil Kim - South Korea, Korean Association of Medical Journal Editors (KAMJE)
and from Crossref: Amanda, Esha, Geoffrey, Ginny, Isaac, Kirsty, Patricia, and Susan.

Please explore the new documentation, give us your feedback using the yellow “Docs feedback” button at the bottom of each page, and share this update to spread the word!

Crossing the Rubicon - The case for making chapters visible

Jennifer Kemp — Wed, 29 Apr 2020 00:00:00 +0000

To help better support the discovery, sale and analysis of books, Jennifer Kemp from Crossref and Mike Taylor from Digital Science, present seven reasons why publishers should collect chapter-level metadata.

Book publishers should have been in the best possible position to take advantage of the movement of scholarly publishing to the internet. After all, they have behind them an extraordinary legacy of creating and distributing data about books: the metadata that supports discovery, sales and analysis.

Librarianship, and the management of book catalogs at scale took off in the nineteenth century. The Dewey Decimal Classification, the various initiatives of the Library of Congress and the British Library followed. Innovations from the 1960s gave us MARC records and ISBNs. The late 90s produced ONIX, which gave the book industry a tremendous start in migrating online.

However, progress in the decades after appears to have been less dramatic. Some might even argue that this tremendous legacy and wealth of metadata experience has acted as a weight, and has slowed progress. Nowhere is this lack of progress clearer than in the discovery and analysis of book chapters: approximately one-quarter of books published per year has chapter-level metadata, and about two-thirds of books don’t have a persistent and open identifier, ratios that have not significantly changed over the last ten years.

Only one-quarter of scholarly books make chapter level metadata available

The proportion of edited books and monographs with chapter-level data is approximately one-quarter of all books published in the last ten years. Calculating this figure is necessarily approximate, using numbers published in Grimme et al (2019), and based on data and observed trends in both Dimensions and Crossref.

So why the lack of progress?

For many publishers and their vendor partners, with systems geared up to the efficient delivery of title-level information, the case for moving towards chapter-level metadata can seem daunting (and potentially expensive!).

Metadata is necessarily detailed and it’s not the kind of thing most people will dabble in. Practitioners, as in other technical fields, have expertise that others may find difficult to leverage if they don’t know what questions to ask. organisations often find themselves entrenched in outdated approaches to metadata.

Crossref and Metadata 2020 are collaborating to produce arguments why publishers should move from book-level metadata to chapters. They’ve been working with representatives from the scholarly community, including both small and large presses, not-for-profits and university presses.

Here we present 7 reasons why publishers should collect chapter-level metadata:

1. Increased discoverability
Increasingly, we’re seeing students and researchers move away from traditional book catalogs and onto more general purpose tools, that are often optimized for journal content, and which may - inadvertently - exclude books and chapters from search results. Making chapter level data and DOIs available places book content into these new channels at no additional cost, and starts to reduce the dependency on specialist vendors. Discovery is simplified, requiring less familiarity or expertise to find relevant book content.

2. Increased usage
Exposing the contents of books at a more granular level drives more users towards the book content, and increasing usage numbers and (depending on platform and business model) revenue.

3. Matching author expectations
New generations of authors expect their content to be easily discoverable in the platforms they use. Without chapter level data, this content won’t easily be found in Google Scholar, Mendeley or ResearchGate. For younger researchers, for those in certain disciplines or using resources well-suited to it, if the chapter metadata - which in many cases requires either an introductory paragraph or an abstract - is missing, the book may as well not exist.

4. Author exposure
About half of scholarly book publishing is thought to be in the form of collected works: books where two or three editors get credit at the top level, but dozens of authors contribute to the chapters. Without chapter level metadata, these authors – the book authors of tomorrow – get no credit for their efforts.

5. Usage and citations reporting
Having chapters readily available in the modern platforms means that they start to accumulate evidence of sharing and citations from the moment of being published. Where chapter content is available on its own, the lack of associated metadata inhibits this evidence. After all, the DOI is a citation identifier. Evidence of impact is now critical for research evaluation, funding, tenure and promotion, and without this data, an author’s chapter may as well remain unread.

6. Supporting your authors with funding compliance and reporting
Authors are increasingly being mandated by their funders to report back on the status of their books and chapters. And, in the case of Open Books and Open Chapters, the funders and authors are frequently the ultimate clients, who are looking to record and report evidence of both academic or social impact. Making chapter level information and identifiers available will facilitate this evidence gathering, especially for open chapters within otherwise non-open books, and increasingly common phenomena.

7. Understanding the hot topics in your books
Whether you use Altmetric, or one of the other data sources that capture book activity, being able to access the social and media metrics of the chapters in your book gives you an immediate insight into the topics that capture interest at a broader level. Vital information when it comes to planning more books in the space, especially if you’re on the look out for books with trade crossover potential.

With chapter-level data, publishers can summarize their programs and compare how many authors they work with, how many book titles they have and where there might be gaps in subject and authors omitted from the metadata. Does the scholarly record fully reflect each book? If not, there may be a good deal of information that is simply unavailable to the machines that read the metadata and use it in systems throughout scholarly communications.

Fortunately, it’s becoming easier to manage this data. Although traditional book metadata systems don’t always support chapter-level data, they do often permit publishers to register title-level DOIs, and with Crossref encouraging ISBN information alongside the generation of chapter level DOIs, some of the significant challenges have been reduced.

Both Crossref and Metadata 2020 offer best practices that make clear the need for richer metadata. It’s also important to acknowledge the very real barriers to providing robust metadata, whether for book chapters or anything else, which is why having the conversations and being aware of available resources is important. Because, though it may be difficult, the hurdles are often up-front making the decision to invest in better metadata, factoring in associated costs, setting up workflows, etc.

But as we have seen from the previous decades, book publishers and their suppliers are experts in managing substantial amounts of metadata. Just as no-one would argue to roll-back all those advantages, we believe that - once deployed - industry-wide creation and distribution of chapter data would be an advance from which there is no retreat.

REFERENCES

https://riojournal.com/article/38698/

The State of Open Monographs Report

https://longleafservices.org/blog/the-sustainable-history-monograph-pilot/

https://scholarlykitchen.sspnet.org/2017/12/07/enriching-metadata-is-marketing/

https://www.ingenta.com/blog-article/five-reasons-chapter-level-metadata-increases-value-academic-books/

Memoirs of a DOI detective...it’s error-mentary dear members

Paul Davis — Mon, 27 Apr 2020 00:00:00 +0000

Hello, I’m Paul Davis and I’ve been part of the Crossref support team since May 2017. In that time I’ve become more adept as a DOI detective, helping our members work out whodunnit when it comes to submission errors.

If you have ever received one of our error messages after you have submitted metadata to us, you may know that some are helpful and others are, well, difficult to decode. I’m here to help you to become your own DOI detective.

Motive: ridding the world of bad metadata

When depositing xml files to us, there can be a plethora of error messages returned to you in the submission logs. Wait, what are submission logs? If that is the first thing that came to mind, then you’re in the right place; do keep reading.

Means: XML deposits

After each content registration or update is received into our deposit admin system, it is initially placed in the submission queue and later, once its time comes, is processed. Whether that deposit comes from the web deposit form, Metadata Manager, or a good old fashioned XML deposit, a submission log is created in our system. This log contains important information about the deposit and its success or failures.

I will go through how you will find and receive this log later on. At the bottom of the submission log you will see a status message that looks like this:

 <batch_data>
<record_count>***</record_count>
<success_count>***</success_count>
<warning_count>***</warning_count>
<failure_count>***</failure_count>
</batch_data>

To some, this might look a bit like a crime scene. If the status report displays the same number in the <record_count> and the <success_count>, then no crime (against deposits) has been committed. Everything you have tried to register or update has been successful and we are all free as DOI detectives to knock off early.

At some point you will probably come across an error or failure in the submission logs, where the failure count is 1.

 <batch_data>
<record_count>1</record_count>
<success_count>0</success_count>
<warning_count>0</warning_count>
<failure_count>1</failure_count>
</batch_data>

For the purposes of this blog, this type of message means a “crime” has been committed. The worst kind of crime - a metadata crime. In the real world, outside of this blog, it just means that your deposit has failed and you need to take some action to fix it. You will also receive accompanying error messages (an evidence log) with details about what went wrong with your submission. We’ll deliver these submission details to you as well in the following ways:

For those submitting via the web deposit form, to the email address used to register your submission
On screen and within the admin tool using the submission ID for those submitting via Metadata Manager
For those submitting XML, to the email included in the <email_address> element of your deposit XML
You can also find the submission log in the admin system at any point

More information on viewing past deposits in the admin system can be found on our support site.

The usual suspects

Those serial offenders, when it comes to failed deposits, are:

Timestamps

Misdemeanor - Every deposit has a <timestamp> value, and that value needs to be incremented each time the DOI is updated. This is done automatically for you in Metadata Manager, the Web Deposit Form and the OJS plugin. But if you’re updating an existing DOI by sending us the whole XML file again, you need to make sure that you update the timestamp as well as the field you’re trying to update.

Error: <msg>Record not processed because submitted version: 201907242206 is less or equal to previously submitted version 201907242206</msg>

Rehabilitation - simply resubmit your XML file, but make sure that you increment the timestamp value to be larger than the current timestamp value.

Titles

Misdemeanor - These need to match exactly between what we have on the system against the ISSN/ISBN and what is in the deposit file.

Error: <msg>Deposit contains title error: the deposited publication title is different than the already assigned title</msg>

Error: <msg>ISSN "123454678" has already been assigned, issn (123454678) is assigned to another title (Journal of Metadata)</msg>

Rehabilitation - you can check the title we have on the system against the ISSN/ISBN on the title list and make the necessary changes, or contact support for us to check the title in our system and make changes to match the title in the deposit to the one in the system, if known.

Title level DOIs

Misdemeanor - These also need to match up exactly in both system and deposit

Error: <msg>Deposit contains title error: The journal has a different DOI assigned; If you want to change the journal's DOI please contact Crossref support: title=Journal of Metadata; current-doi=10.14393/JoM; deposited-doi=10.14393/JoM.1.1</msg>

Rehabilitation - contact us to change the journal level DOI in the system or change the DOI in the deposit yourself to match the one already registered for the title.

Errors in the xml

Misdemeanor - Poor formatting, self closing tags, invalid values.

Error: <msg>Deposited XML is not well-formed or does not validate: Error on line 538</msg>

Rehabilitation - update the xml file that was deposited as it was not well formed against our schema or as an xml file in general. Check you have saved the file correctly (as an .xml file), edited it in an xml editor and not a word processor and if that fails, then contact support and we will try to assist. We also have a collection of new xml examples you may use as a template.

Forensics

There are a few tools we offer to help with the deciphering of the error messages –– we think of these as our magnifying glass(es).

The Title list: A list of all of the titles in our database, you can check against the ISSN/ISBN to see what the title on our system is and whether it matches the title you have in your deposit.
The Depositor Report: Shows all journals, books, and conference proceedings against each member. The report includes all DOIs for each journal, book, conference; the most recently used timestamps; and citation counts for each DOI.
The Reports tab in the admin system: You can find out the history behind a DOI by searching against this in the admin console.
Our common error messages are documented within our support documentation. You can always find out more about most of the error messages are system displays at the link above.
You can find the current xml metadata against a DOI by adding the DOI to the end of this link http://doi.crossref.org/search/doi?pid=support@crossref.org&format=unixsd&doi= (you might need an xml viewer browser extension to view the xml in a more readable format).

Calling for backup

We’ll also soon be adding more leads to our submission logs and error messages for the best of our detectives. These improvements will point our DOI detectives to better documentation about interpreting error messages and taking the appropriate action to resolve those errors.

But there are a lot more error messages out there. If you have trouble deciphering any error message you encounter, then please do send the case number (submission ID) over to CSI (Crossref Support Investigations) at support@crossref.org.

You can also find lots of great information in the pages of our new documentation.

Helping researchers identify content they can text mine

Geoffrey Bilder — Thu, 16 Apr 2020 00:00:00 +0000

TL;DR

Many organisations are doing what they can to aid in the response to the COVID-19 pandemic. Crossref members can make it easier for researchers to identify, locate, and access content for text mining. In order to do this, members must include elements in their metadata that:

Point to the full text of the content.
Indicate that the content is available under an open access license or that it is being made available for free (gratis).

How to do it.

If your content is open access

Make sure the Crossref metadata for all of your open access content includes:

The URL of the open access license the content is under.
A URL that points to the full text of the content on your site (PDF, XML or HTML).

Instructions for including license and full text URLs in your metadata.

If you are making subscription content available for text mining (temporarily or otherwise).

Make sure the Crossref metadata for the content you are making freely available for text mining includes:

The URL of the publisher license the content is under.
A URL that points to the full text of the content where it is being made freely available (PDF, XML or HTML). This might not be on your site.

Instructions for including license and full text URLs in your metadata.

In addition, you need to flag the content that you are making freely available.

A “free to read” element in the access indicators section of your metadata indicating that the content is being made available free-of-charge (gratis).
An assertion element indicating that the content being made available is available free-of-charge.

Instructions for flagging your content as “free”

Note that step #4 is required in order for users to be able to find content marked as “gratis” in Crossref’s REST API.

And if you decide to revoke the free access in the future, you will need to update the data to reflect that restrictions have been reimposed.

Sounds great. Has anybody else actually done this?

Yes.

Over 43 million metadata records already have a license and a full text link. https://api.crossref.org/works?filter=has-license:true,has-full-text:true&rows=0

Millions of the above items have one of the Creative Commons licenses or a dedicated text and data mining license provided by the publisher.

And in the past three weeks (as of the writing of this blog post) over 23,000 articles have been flagged as “free” so they are available for text mining.

https://api.crossref.org/v1/works?filter=assertion:free,has-full-text:true

Free public data file of 112+ million Crossref records

Jennifer Kemp — Thu, 09 Apr 2020 00:00:00 +0000

A lot of people have been using our public, open APIs to collect data that might be related to COVID-19. This is great and we encourage it. We also want to make it easier. To that end we have made a free data file of the public elements from Crossref’s 112.5 million metadata records.

The file (65GB, in JSON format) is available via Academic Torrents here: https://doi.org/10.13003/83B2GP

It is important to note that Crossref metadata is always openly available. The difference here is that we’ve done the time-saving work of putting all of the records registered through March 2020 into one file for download.

The sheer number of records means that, though anyone can use these records anytime, downloading them all via our APIs can be quite time-consuming. We hope this saves the research community valuable time during this crisis.

A few important notes

All records are included. In other words, the data file has every DOI ever registered with Crossref through March 31st, 2020. This means it’s a large file, 65GB.
- Metadata is supplied by our members and, as such, not all records have the same completeness (or quality) of metadata. Bibliographic metadata is generally required. All other metadata, e.g. license and funding information, ORCIDs, etc. is optional (though very much encouraged).
- References (i.e. authors’ cited sources) are also optional metadata. Nearly 50 million records include references and, of those, nearly 30 million have open references that are included in the data file. “Limited” and “Closed” references are not included in the data file. [EDIT 6th June 2022 - all references are now open by default with the March 2022 board vote to remove any restrictions on reference distribution].
- If an error in the metadata is found, please report it directly to the publisher to correct.
The records are in JSON.
New and updated records can be added incrementally using our REST API, which includes a number of date filter options, e.g. index-date.
No registration is required to use our REST API but we do strongly encourage being a ‘polite’ (i.e. identified) user. It makes troubleshooting much easier and reduces the chance of negatively impacting other users.

Questions, comments and feedback are welcome at support@crossref.org.

We thank AcademicTorrents.com for helping us make this data available. And we are grateful for the incredible efforts of everyone working to support research everywhere–stay safe and well.

You’ve had your say, now what? Next steps for schema changes

Patricia Feeney — Thu, 02 Apr 2020 00:00:00 +0000

It seems like ages ago, particularly given recent events, but we had our first public request for feedback on proposed schema updates in December and January. The feedback we received indicated two big things: we’re on the right track, and you want us to go further. This update has some significant but important changes to contributors, but is otherwise a fairly moderate update. The feedback was mostly supportive, with a fair number of helpful suggestions about details.

Feedback and changes

Many of you are excited about CRediT, and a number of members have indicated that they are ready and waiting to send us CRediT roles. To support this, as in my initial proposal, we’re adding a new role element and role_type attribute that supports existing Crossref-defined roles and CRediT roles, as well as a required vocab attribute to specify which vocabulary is being supplied.

<role role_type="author" vocab="crossref">author</role> <role role_type="writing-original_draft" vocab="credit"/>

CRediT as it exists now is an informal standard coordinated by CASRAI, but a formal standard is in the works via NISO. CRediT is currently a list of well considered and defined roles that are not particularly machine-readable. I’ve created a list for implementation that eliminates spaces and ampersands. CRediT also lacks reliable PIDs or persistent URLs for the role definitions, so that has been omitted from our implementation. We’ll adopt any changes resulting from the NISO standard, but have decided to go forward with it as-is, as many of our members are eager to implement.

Beyond CRediT, we’ll also be expanding and refining our contributor support in a number of ways:

We’ll be expanding our affiliation metadata beyond a simple string to include organisation identifiers like ROR, and allow markup of organisation names and locations.
We’re expanding the contributor identifiers as well - in addition to ORCID iDs, members can send us Wikidata, ISNI, and other identifiers.
We’re adding support for multiple names to support contributors whose names can be expressed in multiple alphabets, or who have aliases or nicknames.
We’re changing surname to family_name and will be relaxing the requirement that all person names have a “surname” - a given name may be supplied on its own to support contributors who do not have family names.
The current element for corporate/group authors, organisation, will be replaced by collab as the term “organisation” was widely confusing (we have a lot of affiliation info registered as group authors!), and the collab section will also allow organisation identifiers.

Many of these updates align with how JATS supports contributors - I hope these changes will allow our members to supply robust contributor metadata without the burden of complicated conversions.

I’m also including the proposed changes to support data citation and typing of citations. Additionally, we’ll be adding support for members who want to:

supply Grant IDs in their metadata records
register identifiers for conferences.

A draft 5.0 xsd file is available in a branch of our GitLab schema repository with the details of the planned updates, and more robust documentation and examples are forthcoming.

Implementation plans

My house was built in 1890 and there are always surprises whenever we need to fix or renovate anything. Our system is just as old in technology years - it’s been chugging along since the aughts. This means while we don’t think it’s powered by knob-and-tube wiring, we can’t be sure until we open up the walls. We want to implement our plans (in fact we want to do more!) but if we run into any big blockers or crucial issues, we may roll out the changes over several iterations. These updates are fairly conservative and I remain optimistic we’ll be able to implement them as-is. Our update will help us build a foundation for future updates, allowing us to continuously evolve our schema as we move forward.

Some of you are understandably worried about our implementation schedule and backwards incompatibility. We’re aware that changes are expensive and inconvenient, and making them on our schedule doesn’t always work for your schedule. That’s why we’ve sustained 12+ versions of our schema over the past 12 years. We won’t be mandating a change any time soon, and definitely won’t do so without sufficient warning and community involvement. In the future we’ll need to make a sustained effort to retire older schema, but now isn’t the time for that.

We intend to commence work in Q2 but won’t have a firm timeline for a few more weeks. I will be providing regular updates as we progress, and will be asking for volunteers to test the updates when we’re ready. I’ll also be sharing more documentation and information about how the changes will be represented in our metadata outputs.

Have more to say?

Our feedback period has finished and we do plan to implement the changes as described, but if you have opinions, please share them.

Encouraging even greater reporting of corrections and retractions

Kirsty Meddings — Mon, 30 Mar 2020 00:00:00 +0000

TL;DR: We no longer charge fees for members to participate in Crossmark, and we encourage all our members to register metadata about corrections and retractions - even if you can’t yet add the Crossmark button and pop-up box to your landing pages or PDFs.

–

Research doesn’t stand still; even after publication, articles can be updated with supplementary data or corrections. When research outputs are is changed in this way the publisher should report and link it, so that those accessing and citing the content know if it’s been updated, corrected or even retracted. This also emphasizes the member’s commitment to the ongoing stewardship of research outputs.

Many people find and store articles to read later, either as PDFs on their laptop or on one of any number of reference management systems - when they come back to read and cite these articles, possibly many months later, they want to know if the version they have is current or not.

Removing Crossmark fees

To encourage even wider adoption of Crossmark, and to promote best practice around better reporting of corrections and retractions, we will no longer be charging additional fees for our Crossmark service. This change applies to all Crossmark metadata registered from 1 January 2020. All members are now encouraged to add Crossmark metadata and add the Crossmark button and pop-up box to their publications - and you can do so as part of your regular content registration.

Richer metadata gives important context

We know that there are many more corrections and retractions that are not yet being registered, and to address this, we are now asking all of our members to start registering metadata for significant updates to your publications, even if you don’t implement the Crossmark button and pop-up box on your content. Remember, anyone can access the Crossmark metadata through our public REST API, and start using it straight away - even if you’re not ready to implement the Crossmark button.

Check out how to get started; if you only want to deposit metadata, follow steps one through four. If you also want to add the Crossmark button and pop-up box to your web pages/PDFs so that readers can easily see when content has changed, then also follow the rest of the steps.

Crossmark

We launched Crossmark in 2012 to raise awareness of these critical changes, by asking Crossref members to:

record such updates in your metadata, either as part of your regular Crossref metadata deposit, or deposited as stand-alone data for back-year records
help readers find out about the changes by placing a Crossmark button and pop-up box (which is consistent across all members making it recognizable to readers) on your landing pages and in PDFs

Members can also use Crossmark to register additional metadata about content, giving further context and background for the reader. These metadata appear in the “More Information” section of the Crossmark box. 7 million DOIs have some additional metadata, the most common being copyright statements, publication history, and peer review methods.

Anyone can access the Crossmark metadata through our public REST API, providing a myriad of opportunities for integration with other systems, and analysis of changes to the scholarly record.

Who has implemented Crossmark?

440 Crossref members have implemented Crossmark to date. 11.4 million DOIs have some Crossmark metadata.

	Total DOIs	DOIs with Crossmark metadata	%
Journal articles	80,862,460	10,155,340	12.56%
Book chapters	14,040,646	792,953	5.65%
Conference Papers	6,175,733	457,237	7.40%
Datasets	1,862,852	19,206	1.03%
Books	753,298	239	0.03%
Monographs	469,333	23	0.00%

Of those, about 130,000 contain an update:

You can see which members or journals have implemented Crossmark by viewing the relevant Crossref Participation Report.

Events got the better of us

Bryan Vickery — Fri, 27 Mar 2020 00:00:00 +0000

Publisher metadata is one side of the story surrounding research outputs, but conversations, connections and activities that build further around scholarly research, takes place all over the web. We built Event Data to capture, record and make available these ‘Events’ –– providing open, transparent, and traceable information about the provenance and context of every Event. Events are comments, links, shares, bookmarks, references, etc.

In September 2018 we said Event Data was ‘production ready.’ What we meant was development of the service had reached a point where we expected no further major changes to the code, and we encouraged you to use it. What normally would have followed was a detailed handover to our operations team, for monitoring and performance management, and for Product Management to expand Event Data by adding new Crossref member domains and evaluating additional event sources.

Why so quiet?

But many things changed on the staff front, meaning 2019 was a year of reinvention for the Technical and Product teams and of critical knowledge sharing and learning –– Event Data had to take a back seat as we focused resources on other key projects (more on that later). From a technical perspective, we’ve found the Elasticsearch index is not performing well and the approach taken to specifically support data citations through Scholix has not really scaled.

When things go wrong, whether in ways you can or can’t anticipate, the most important thing is communication –– in dealing with the challenges we forgot to do that. We understand how frustrating that can be and we’re extremely sorry to have gone so quiet.

So, where are we today?

Event Data is important to us and clearly important to you too as you’ve contacted us about your use-cases and the reliability of the service. Event Data remains available and you’re welcome to use it, but you should expect instability to continue and be aware that it does not find events for DOIs/domains of our newer members (who joined Crossref since 2019) –– so we’re conscious it might be hard to say whether it’s a good fit for your project at this point.

What are we doing?

We have brought in additional expert Elasticsearch resources to assist with a separate project to migrate our REST API from SOLR to Elasticsearch. We’re making fantastic progress on this. As soon as we’re confident we can make this switch, we will move those same Elasticsearch resources to shoring up Event Data. The REST API takes priority over Event Data because we need to add support for important new record types (like research grants) that aren’t yet available via the API.

We’re also concluding the process of hiring two new Product Managers which means we’ll be in a position to assign someone to head up the product management of Event Data. When we do return to Event Data in the coming months, our initial priority will be increased support for data citation and Scholix. If that means radical changes to the rest of the service, we’ll let you know.

Opening up the discussion

We will have more news on Event Data in mid-2020. We’d love you to join the Crossref Community Forum; we’ve created a new Category for Event Data where you can post details of how you are using, or plan to use Event Data; post questions to the group; suggestions for future development and provide general feedback on the Event Data service.

Metadata Manager Update

Bryan Vickery — Tue, 24 Mar 2020 00:00:00 +0000

At Crossref, we’re committed to providing a simple, usable, efficient and scalable web-based tool for registering content by manually making deposits of, and updates to, metadata records. Last year we launched Metadata Manager in beta for journal deposits to help us explore this further. Since then, many members have used the tool and helped us better understand their needs.

What we’ve learned has made us realize how useful such a tool can be to both large and small publishers, but also that the approach we took with Metadata Manager needs to be changed - it’s not flexible enough to easily add other record types, like books/book chapters, or to include any changes we may make to our input schema.

With that in mind, we’re pausing development on Metadata Manager to allow us to properly evaluate what we’ve learned. If you’re currently using Metadata Manager for journal deposits without any problems, please do continue - you’re helping us learn a lot! But if you haven’t used Metadata Manager before, or are having problems, please:

use our existing Web Deposit Form instead, or
upload XML directly through the deposit system admin interface

We won’t be fixing bugs in Metadata Manager, except for providing any essential security updates. Of course, if you still need help please read our Content Registration help pages, or contact the Support team.

Metadata Manager’s features will be reimagined as part of our planned Member Center (working title, subject to change) project, where we will start to bring together all business and technical information for our members, service providers and metadata users. The Member Center will be the heart of our strategy to make it easier for you to work with Crossref to:

register and update metadata
view, update and transfer titles
visualize your activity/participation and act on problems with metadata
understand your bills and invoices
manage your users and service providers and their access and entitlements
and more

We’re in the early stages of planning for the Member Center and will be seeking feedback from members, service providers and metadata users in the coming months.

Double trouble with DOIs

Dominika Tkaczyk — Tue, 10 Mar 2020 00:00:00 +0000

Detective Matcher stopped abruptly behind the corner of a short building, praying that his loud heartbeat doesn’t give up his presence. This missing DOI case was unlike any other before, keeping him awake for many seconds already. It took a great effort and a good amount of help from his clever assistant Fuzzy Comparison to make sense of the sparse clues provided by Miss Unstructured Reference, an elegant young lady with a shy smile, who begged him to take up this case at any cost.

The final confrontation was about to happen, the detective could feel it, and his intuition rarely misled him in the past. He was observing DOI 10.2307/257306, which matched Miss Reference’s description very well. So far, there was no indication that DOI had any idea he was being observed. He was leaning on a wall across the street in a seemingly nonchalant way, just about to put out his cigarette. Empty dark streets and slowly falling snow together created an excellent opportunity to capture the fugitive.

Suddenly, Matcher heard a faint rustling sound. Out of nowhere, another shady figure, looking very much like 10.5465/amr.1982.4285592, appeared in front of the detective, crossed the street and started running away. Matcher couldn’t believe his eyes. These two DOIs had identical authors, year and title. They were even wearing identical volume and issue! He quickly noticed minor differences: slight alteration in the journal title and lack of the second page number in one of the DOIs, but this was likely just a random mutation. How could have he missed the other DOI? And more importantly, which of them was the one worried Miss Reference simply couldn’t live without?

TL;DR

Crossref metadata contains duplicates, i.e. items with different DOIs and identical (or almost identical) bibliographic metadata. This often happens when there is more than one DOI pointing to the same object. In some cases, but not all of them, one of the DOIs is explicitly marked as an alias of the other DOI.
In this blog post, I analyze those duplicates, that are not marked with an alias relation. The analysis shows that the problem exists, but is not big.
Among 524,496 DOIs tested in the analysis, 4,240 (0.8%) were flagged as having non-aliased duplicates. I divided those duplicates into two categories:
- Self-duplicate is a duplicate deposited by the same member as the other DOI, there were 3,603 (85%) of them.
- Other-duplicate is a duplicate deposited by a different member than the other DOI’s depositor, there were only 637 (15%) of them.
I used three member-level metrics to estimate the volume of duplicates deposited by a given member:
- Self-duplicate index is the fraction of self-duplicates in member’s DOIs: on average 0.67%.
- Other-duplicate index is the fraction of other-duplicates in a member’s DOIs: on average 0.13%.
- Global other-duplicate index is the fraction of globally detected other-duplicates involving a given member: on average 0.34%.

Introduction

In an ideal world, the relationship between research outputs and DOIs is one-to-one: every research output has exactly one DOI assigned and each DOI points to exactly one research output.

As we all know too well, we do not live in a perfect world, and this one-to-one relationship is also sometimes violated. One way to violate it is to assign more than one DOI to the same object. This can cause problems.

First of all, if there are two DOIs referring to the same object, eventually they both might end up in different systems and datasets. As a result, merging data between data sources becomes an issue, because we no longer can rely on comparing the DOI strings only.

Reference matching algorithms will also be confused when they encounter more than one DOI matching the input reference. They might end up assigning one DOI from the matching ones at random, or not assigning any DOI at all.

And finally, more than one DOI assigned to one object is hugely problematic for document-level metrics such as citation counts, and eventually affects h-indexes and impact factors. In practice, metrics are typically calculated per DOI, so when there are two DOIs pointing to one document, the citation count might be split between them, effectively lowering the count, and making every academic author’s biggest nightmare come true.

It seems we shouldn’t simply cover our eyes and pretend this problem does not exist. So what are we doing at Crossref to make the situation better?

It is possible for our members to explicitly mark a DOI as an alias of another DOI, if it was deposited by mistake. This does not remove the problem, but at least allows metadata consumers to access and use this information.
Whenever a DOI is registered or updated in Crossref, we automatically compare its metadata to the metadata of existing DOIs. If the metadata is too similar to the metadata of another DOI, this information is sent to the member and they have a chance to modify the metadata as they see fit.

Despite these efforts, we still see duplicates that are not explained by anything in the metadata. In this blog post, I will try to understand this problem better and assess how big it is. I also define three member-level metrics that can show how much a given member contributes to duplicates in the system and can flag members with unusually high fractions of duplicates.

Gathering the data

The data for this analysis was collected in the following way:
Only journal articles were considered in the analysis.
Only members with at least 5,000 journal article DOIs were considered in the analysis.
For each member, a random sample of 1,000 journal article DOIs was selected.
DOIs with no title, title shorter than 20 characters or shorter than 3 words were removed from each sample. This was done because items with short titles typically result in incorrectly flagged duplicates (false positives).
For each remaining DOI in the sample, a simple string representation was generated. This representation is a concatenation of the following fields: authors, title, container-title, volume, issue, page, published date.
This string representation was used as query.bibliographic in Crossref’s REST API and the resulting item list was examined.
If the original DOI came back as the first or the second hit, the relevance score difference between the first two hits is less than 1, they are both journal articles, and there is no relation (alias or otherwise) between them, the other one of the two is considered a duplicate of the original DOI. The score difference threshold was chosen through a manual examination of a number of cases. Most detected duplicates came back scored identically.

Overall results

In total, I tested 590 members and 524,496 DOIs. Among them, 4,240 DOIs (0.8%) were flagged as duplicates of other DOIs. This shows the problem exists, but is not huge.

I also analyzed separately two categories of duplicates:

self-duplicates are two DOIs with (almost) identical metadata, deposited by the same member,
other-duplicates are two DOIs with (almost) identical metadata, deposited by two different members.

Self-duplicates are more common: 3,603 (85%) of all detected duplicates are self-duplicates, and only 637 (15%) are other-duplicates. This is also good news: self-duplicates involve one member only, so they are easier to handle.

Self-duplicates

To explore the levels of self-duplicates among members, I used a custom member-level metric called self-duplicate index. Self-duplicate index is the fraction of self-duplicates among the member’s DOIs, in this case calculated over a sample.

On average, members have a very small self-duplicate index of 0.67%. In addition, in the samples of 44% of analyzed members no self-duplicates were found. The histogram shows the skewness of the distribution:

As we can see in the distribution, there are only a few members with high self-duplicate index. The table shows all members with the self-duplicate higher than 10%:

Name	Total DOIs	Sample size	Self-duplicate index
University of California Press	129,741	798	36%
Inderscience Publishers	127,729	998	29%
American Society of Hematology	137,124	990	24%
Pro Reitoria de Pesquisa, Pos Graduacao e Inovacao - UFF	7,756	919	19%
American Diabetes Association	49,536	946	18%

Other-duplicates

Other-duplicate index is the fraction of other duplicates among the member’s DOIs, in this case calculated from a sample.

On average, members have a very low other-duplicate index of only 0.13%. What is more, 89% members have no other-duplicates in the sample, and the distribution is even more skewed than in the case of self-duplicates:

Here is the list of all members with more than 2% of other-duplicates in the sample:

Name	Total DOIs	Sample size	Other-duplicate index
American Bryological and Lichenological Society	5,593	844	41%
Maney Publishing	15,342	832	6%
JSTOR	1,612,174	864	4%
American Mathematical Society (AMS)	83,015	844	4%

American Bryological and Lichenological Society is a clear outlier with 41% of their sample flagged as duplicates. Interestingly, all those duplicates come from one other member only (JSTOR) and JSTOR was the first to deposit them.

Similarly, all other-duplicates detected in the American Mathematical Society’s sample are shared with JSTOR, and JSTOR was the first to deposit them.

Maney Publishing’s 51 other-duplicates are all shared with a member not listed in this table: Informa UK Limited.

JSTOR is the only member in this table, whose 36 other-duplicates are shared with multiple (8) members.

Another interesting observation is that the members in this table (apart from JSTOR) are rather small or medium, in terms of total DOIs registered by them. It is also worrying that Informa UK Limited, a member that shares 51 other-duplicates flagged in Maney Publishing’s sample, was not flagged by this index. The reason might be differences in the overall number of registered DOIs: two members that deposited the same number of other-duplicates, but have different overall numbers of registered DOIs, will have different other-duplicate indexes.

To address this issue, I looked at a third index called global other-duplicate index. Global other-duplicate index is the fraction of globally detected other-duplicates involving a given member.

Global other-duplicate index has a useful interpretation: it tells us how much the overall number of other-duplicates would drop, if the given member resolved all its other-duplicates (for example by setting appropriate relations or correcting the metadata so that it is no longer so similar).

Here is the list of members with global-duplicate index higher than 2%:

Name	Total DOIs	Global other-duplicate index
JSTOR	1,612,174	69%
American Bryological and Lichenological Society	5,593	54%
Informa UK Limited	4,275,507	15%
Maney Publishing	15,342	8%
American Mathematical Society (AMS)	83,015	6%
Project Muse	326,300	5%
Wiley	8,003,815	3%
Elsevier BV	16,268,943	3%
Liverpool University Press	31,870	3%
Cambridge University Press (CUP)	1,621,713	2%
Ovid Technologies (Wolters Kluwer Health)	2,152,723	2%
University of Toronto Press Inc. (UTPress)	46,778	2%

Note that the values add up to more than 100%. This is because in every other-duplicate there are two members involved, so the involvement adds up to 200%.

As we can see, all the members from the previous table are in this one as well. Apart from them, however, this index flagged several large members. Among them, Informa UK Limited, that was missing from the previous table.

All the indexes defined here are useful in identifying members that contribute a lot of duplicates to the Crossref metadata. They can be used to help to clean up the metadata, and also to monitor the situation in the future.

Limitations

It is important to remember that index values presented here were calculated on a single sample of DOIs drawn for a given member. The values would be different if a different sample was used, and so they shouldn’t be treated as exact numbers.

The tables include members with the index exceeding a certain threshold, chosen arbitrarily, for illustrative purposes. Different runs with different samples could result in different members being included in the tables, especially in their lower parts.

To obtain more stable values of indexes, multiple samples could be used. Alternatively, in the case of smaller members, exact values could be calculated from all their DOIs.

Crossref metadata for bibliometrics

Ginny Hendricks — Fri, 21 Feb 2020 00:00:00 +0000

Our paper, Crossref: the sustainable source of community-owned scholarly metadata, was recently published in Quantitative Science Studies (MIT Press). The paper describes the scholarly metadata collected and made available by Crossref, as well as its importance in the scholarly research ecosystem.

Containing over 106 million records and expanding at an average rate of 11% a year, Crossref’s metadata has become one of the major sources of scholarly data for publishers, authors, librarians, funders, and researchers. The metadata set consists of 13 record types, including not only traditional types, such as journals and conference papers, but also data sets, reports, preprints, peer reviews, and grants. The metadata is not limited to basic publication metadata, but can also include abstracts and links to full text, funding and license information, citation links, and the information about corrections, updates, retractions, etc. This scale and breadth make Crossref a valuable source for research in scientometrics, including measuring the growth and impact of science and understanding new trends in scholarly communications. The metadata is available through a number of APIs, including REST API and OAI-PMH.

In the paper, we describe the kind of metadata that Crossref provides and how it is collected and curated. We also look at Crossref’s role in the research ecosystem and trends in metadata curation over the years, including the evolution of its citation data provision. We summarize the research that used Crossref’s metadata and describe plans that will improve metadata quality and retrieval in the future.

Using the Crossref REST API (with Open Ukrainian Citation Index)

Rachael Lammey — Wed, 05 Feb 2020 00:00:00 +0000

Over the past few years, I’ve been really interested in seeing the breadth of uses that the research community is finding for the Crossref REST API. When we ran Crossref LIVE Kyiv in March 2019, Serhii Nazarovets joined us to present his plans for the Open Ukrainian Citation Index, an initiative he explains below.

But first an introduction to Serhii and his colleague Tetiana Borysova.

Serhii Nazarovets is a Deputy Director for Research at the State Scientific and Technical Library of Ukraine. Serhii has a Ph.D. in Social Communication Science. His research interests lie in the area of scientometrics and library science. Serhii is the Associate Editor for DOAJ (www.doaj.org) and the Regional Editor for E-LIS (Eprints in Library and Information Science). Serhii has worked in different scientific libraries of Ukraine for more than 10 years. Tetiana Borysova is a Senior Researcher at the State Scientific and Technical Library of Ukraine. Her research interests are focused on topics such as research data management, journal management and scientometrics.

Introducing OUCI

OUCI (Open Ukrainian Citation Index) is a new search engine and a citation database based on publication metadata from Crossref members.

OUCI is intended to simplify the search of scientific publications, to attract the editors’ attention to the problem of completeness and quality of the metadata of Ukrainian scholarly publications, and will allow bibliometricians to freely study the relations between authors and documents from various disciplines, in particular in the field of social sciences and humanities. OUCI is open for every user in the world without any restrictions.

OUCI launched in November 2019. The project is being implemented by the State Scientific and Technical Library of Ukraine with the support of the Ministry of Education and Science of Ukraine.

In Ukraine, we do not have a national citation database, and this significantly impedes the search and analysis of information about Ukrainian publications. According to preliminary estimates, more than 3,000 titles of scientific journals are currently published in Ukraine. At the same time, only around 100 Ukrainian journal titles are indexed in authoritative citation databases, such as Scopus and Web of Science Core Collection. Thus, researchers and managers lack this citation data to understand the impact of Ukrainian journals and their demand in the scientific communication system. Our approach is that OUCI database contains metadata from all publishers that use the Crossref’s Cited-by service and who support the Initiative for Open Citations by making the reference metadata they publish with Crossref openly available.

How is Crossref metadata used in OUCI?

A publication can only be indexed in OUCI if there is a DOI. At first glance, the idea of creating an index of national publications based on this condition may seem too optimistic. However, in January 2018, a new requirement was adopted by the List of scientific publications of Ukraine (a list of Ukrainian journals recognized by experts as qualitative for publishing their research results for a scientific degree), which listed a DOI as one of the requirements for inclusion. After that, the number of publishers who received the DOI prefix from Crossref has tripled, to 352 in November 2019.

Another important feature of OUCI is that publishers have to use Crossref’s Cited-by service and support the Initiative for Open Citations. We are working to build a new fair infrastructure where everyone who is interested in the dissemination of scientific knowledge can present their publications to the community, develop expert judgment skills and access citations to explore the links between documents. The philosophy of the index is to use only open resources to fill it.

In addition to standard filters from Crossref metadata (such as publisher, publication, type, year), OUCI offers to refine search results by:

indexation in Web of Science and/or Scopus,
journal category (A or B according to the List of scientific publications of Ukraine),
the field of knowledge and scientific specialties (according to the Ukrainian legislation) and other aspects important to Ukrainian users characteristics.

Figure 1: OUCI search and filter options

Beyond the ability to search articles, OUCI displays profiles for Ukrainian journals (the titles of these journals will include hyperlinks in the search results). Administrators can manage them, add and edit information about their journals: web-site, aims and scope, scientific fields of the journal according to the Ukrainian classification. Also, you can see some quantitative characteristics of journals: number of publications, number of citations, h-index, i10-index etc.

Figure 2: Display of journal information in OUCI

In addition, we have implemented an analytics module. Using the data about the number of articles and citations from Crossref, it allows users to analyze Ukrainian journals by field.

Figure 3: Publication and citation information

What are the future plans for OUCI?

In the near future, we plan to add:

the ability to export search results for further analysis;
integration with Unpaywall;
alternative metrics from Crossref Event Data.

In the ideal future for our index, every Ukrainian article will be registered with Crossref and have open references. We plan to promote the importance of reach and quality metadata in Crossref among Ukrainian publishers. We also encourage all publishers to support the Initiative for Open Citations.

What else would OUCI like to see in Crossref metadata?

One of the main problems we encountered when creating OUCI was the metadata about the authors. Very few publications contain data about the author’s ORCID iD. Focusing publishers on the need to transmit full metadata to Crossref, as well as monitoring their quality is a must for the resources like this. Also we look forward to the growing usage of ROR (Research Organization Registry) - identifiers for research organisations, similar to the way that ORCID offers identifiers for researchers. We believe that the ROR will help to obtain reliable data for analyzing the scientific activity of Ukrainian institutions.

Another issue we’ve identified in some Ukrainian journals that some of the small publishers that register content via Crossref Sponsors did not take care getting their own prefix, so it can be difficult to see their publications - this is something that showing the metadata via an index can help them see and therefore fix.

Questions?

We’ve had lots of questions about OUCI in the run up to the launch and now that it’s live. Here is a selection of our FAQs, all available on our website. You can also get in touch directly if you have another question we haven’t answered yet.

Crossref: the sustainable source of community-owned scholarly metadata

Dominika Tkaczyk — Wed, 01 Jan 2020 00:00:00 +0000

Crossref: The sustainable source of community-owned scholarly metadata

Published in Quantitative Science Studies (2020), this paper describes the scholarly metadata collected and made openly available by Crossref — its history, scale, content types, and role in the research ecosystem.

Strategists

Understand why Crossref metadata is foundational scholarly infrastructure. The history, governance, and community model that make Crossref a sustainable, neutral, member-owned source of scholarly data.

Decision-makers

Know what’s in the metadata and what it enables. 106 million records, 13 content types — not just bibliographic basics but funding, licences, citation links, corrections, and retractions.

Practitioners

Learn how to access Crossref metadata at scale. A technical overview of the REST API and OAI-PMH, with context on citation data provision and metadata quality trends.

What this paper covers

History and governance — how Crossref was founded in 2000 and why its member-owned, not-for-profit structure matters for long-term sustainability
Scale of the metadata set (in 2021) — over 106 million records across journals, conference papers, books, datasets, preprints, peer reviews, grants, and more
Richness beyond basic bibliographic data — abstracts, full-text links, funding and licence information, citation links, corrections, updates, and retractions
Role in the research ecosystem — how Crossref metadata directly supports scientometrics, research assessment, and scholarly communications research
APIs and access — the REST API and OAI-PMH as the primary routes to Crossref metadata at scale
Citation data — the evolution of Crossref’s citation data provision, including the move to open references
Metadata quality and curation — trends in completeness and accuracy over time, and plans for improvement

Read the full paper

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Metadata 20/20 outcomes: principles, personas and practices for richer open scholarly metadata

Ginny Hendricks — Mon, 30 Dec 2019 00:00:00 +0000

Metadata 20/20: Principles, personas and practices for richer open scholarly metadata

Metadata 20/20 was an international, community-led initiative bringing together researchers, publishers, librarians, funders, data repositories, and service providers around a shared goal: richer, more connected, more reusable, and more open metadata for all research outputs. The outcomes page collects the full set of deliverables from the initiative’s three phases.

Strategists

Understand why richer metadata is a community problem — and a community opportunity. The principles and use cases that make the case for investing in metadata quality across the scholarly ecosystem.

Decision-makers

Know what good metadata practice looks like for your role. Personas across six stakeholder communities — researchers, publishers, librarians, funders, data repositories, and platforms — clarify what each group needs from metadata and what each can contribute.

Practitioners

Apply the practices, evaluation frameworks, and best practices guidance. Concrete implementation guidance drawn from a multi-stakeholder survey (211 responses from 23 countries), a peer-reviewed literature review, and a 2019 workathon.

What the initiative produced

Metadata principles — aspirational guidelines for improving research communications, discoverability, and reuse across the community
Metadata personas — role-based constructs for six stakeholder communities, identifying what each needs from metadata and how each can contribute
Metadata practices — implementation guidance to help each persona act on the principles
Use cases — real-world challenges and opportunities that illustrate the cost of poor metadata and the value of richer records
Literature review — a peer-reviewed synthesis of the metadata landscape, published in RIO Journal
Multi-stakeholder survey — 211 responses from 23 countries exploring metadata awareness and attitudes (2019)
Evaluation framework — approaches for assessing and improving metadata quality
Workathon proceedings — outputs from the September 2019 community event on metadata change management
Methods paper — documentation of the community-based process used to develop the principles and personas

Explore the outcomes

Proposed schema changes - have your say

Patricia Feeney — Wed, 04 Dec 2019 00:00:00 +0000

The first version of our metadata input schema (a DTD, to be specific) was created in 1999 to capture basic bibliographic information and facilitate matching DOIs to citations. Over the past 20 years the bibliographic metadata we collect has deepened, and we’ve expanded our schema to include funding information, license, updates, relations, and other metadata. Our schema isn’t as venerable as a MARC record or as comprehensive as JATS, but it’s served us well. It’s not currently positioned to fully support everything we want to do long term - we’d like to support assertions, map cleanly to JATS and schema.org magically at the same time, and maybe even move beyond XML - but for now it’s something we can work with to empower member metadata to help find, cite, and connect scholarly content.

We’ve maintained backwards compatibility for most things since 2007 but this update will require some moderate changes to how contributors are modeled. The balance between supporting established tagging and addressing the evolution of what we collect and how it is expressed can be tricky. We want to collect good metadata without significantly disrupting the workflow of our membership, who are the source of the metadata. Even so, this is a fairly pragmatic update that will position us well for the future. I look forward to supporting new types of content and metadata in the future, but for now take a look at what I’m proposing.

Leave feedback, ask questions, and make suggestions in the feedback document or via email to feedback@crossref.org.

Next update

I’m proposing some updates and additions to the metadata we collect, and would like your feedback. To fully and elegantly support affiliation identifiers and multiple author roles, we need to break backwards compatibility. Specifically, we want to:

Add support for CRediT

The CASRAI CRediT taxonomy is increasingly used to represent roles common to contributors to research outputs. Our members are applying CRediT to contributors, so we want to capture them as well. Supporting CRediT allows Crossref and our membership to identify and credit contributors beyond authors and editors.

As most of you know, a contributor often does more than one thing - they write, they edit, they curate. We currently only allow one contributor role as an attribute, but, to realistically support CRediT and accurately capture evidence about the work, we need to allow multiple contributor roles. This will break backwards compatibility. We can potentially support the old way and the new way, but I’m trying to avoid awkward compromises wherever possible.

Supporting CRediT doesn’t mean you need to adopt CRediT. We’ll continue to support existing author roles, but they’ll be marked up differently. Details are in our request for feedback document.

Expand support for author and organisation identifiers

We collect ORCID iDs in our metadata but do not currently support other types of contributor identifiers. We also don’t support affiliation or organisation identifiers beyond those assigned within our funder and clinical trial registries. We’ve had increasing demands from both metadata suppliers and users to expand support for affiliation identifiers because…identifiers are useful. We also want to expand author identifier support as ORCID IDs may only be registered by researchers who are able to curate their own ORCID record. Adding support for ISNI and Wikidata IDs is a common request, but we anticipate there’s a need for other identifiers as well.

Our plan is to accept identifiers registered with identifiers.org as well as other identifiers upon request. We prefer to remain consistent with the identifiers.org registry as much as possible.

We’re particularly keen to support open community-led identifiers like ORCID and ROR and will continue to do so, but also want to support the metadata our members want to distribute. organisation identifiers will be particularly useful as they’ll help us populate records with ROR IDs in the future, leading to better quality affiliation metadata.

Expand support for a range of contributor names

We currently require a surname for all contributors, and don’t provide comprehensive support for contributors whose names are represented by multiple alphabets, or who have nicknames or aliases, or who don’t have a surname. To begin with, we’ll replace surname with the more widely used ‘family name’ and remove the fixed surname requirement, allowing only a given name to be provided where appropriate. We’ll also allow a variety of names to be provided for each contributor.

Expand affiliation support

We currently collect affiliation as a single string - we’re going to break that up to support affiliation names, and add in support for organisational identifiers like ROR.

Expand support for data citation

For those of you who send us references, we’re adding a few fields to better support data citation. We’re also going to allow you to (optionally) supply a specific publication type for references.

Other updates

We’re making some other small updates as well. If you have a small request, we may be able to accommodate it in our next update. Larger changes or additions will probably have to wait for future updates, but we’d love to start collecting suggestions now.

We need your feedback!

I’ll be giving a webinar on December 19 at 02:00 and 15:00 UTC to go over these changes in detail - please visit our webinars page to register.

Again, please leave feedback, ask questions, and make suggestions in the feedback document, or if you prefer send feedback via email to feedback@crossref.org. We’ll be taking feedback through January 15, 2020.

Request for feedback: Conference ID implementation

Patricia Feeney — Fri, 13 Sep 2019 00:00:00 +0000

We’ve all been subject to floods of conference invitations, it can be difficult to sort the relevant from the not-relevant or (even worse) sketchy conferences competing for our attention. In 2017, DataCite and Crossref started a working group to investigate creating identifiers for conferences and projects. Identifiers describe and disambiguate, and applying identifiers to conference events will help build clear durable connections between scholarly events and scholarly literature.

Chaired by Aliaksandr Birukou, the Executive Editor for Computer Science at Springer Nature, the group has met regularly over the past two years, collaborating to create use cases and define metadata to identify and describe conference series and events. We first asked for input on metadata specifications in April 2018. Technical implementation kicked off in February with a workshop at CERN to discuss the mechanics of making PIDs for conferences a reality.

We’ve reached another milestone and want your feedback

Crossref has supported a number of conference publication-related PIDs for years - members can currently register PIDs for conference series publications, conference proceedings, and of course individual conference papers - and that won’t change, but we will also be supporting DOI registration for conferences. A crucial step towards this is of course integrating the new identifier into our metadata input schema.

The details

We currently collect some limited metadata describing the conference itself such as theme, location, and dates as part of the conference series or proceeding metadata, but do not apply a DOI to that information. The new Conference ID records will include expanded metadata as defined by the working group. You’ll be able to register a distinct metadata record for a single conference. You’ll also be able to register a record for a conference series, and connect Conference IDs to conference proceeding metadata records and DOIs.

Changes to the conference-specific metadata are backwards compatible. Members will be able to register event metadata per usual, or can instead use the new event metadata to register an identifier for their conference event and/or series. This means a member can:

Register conference, conference series, proceedings series, proceedings, and papers in one submission
Register proceedings or proceedings series and papers without a Conference ID included
Register Conference IDs only
Update an existing conference record with a Conference PID

I’ve written up our proposal in this google doc and we want your feedback before we proceed with implementation. Please comment directly in the Google doc, open a Gitlab issue, or feedback@crossref.org. We’ll keep the document open for comments until September 30.

Building better metadata with schema releases

Patricia Feeney — Wed, 21 Aug 2019 00:00:00 +0000

This month we have officially released a new version of our input metadata schema. As well as walking through the latest additions, I’ll also describe here how we’re starting to develop a new streamlined and open approach to schema development, using GitLab and some of the ideas under discussion going forward.

What’s included in version 4.4.2

The latest schema as of August 2019 is version 4.4.2 and this release now includes:

Support for “pending publication”
Support for JATS 1.2 abstracts
Abstract support to dissertations, reports, and allow multiple abstracts wherever available
Support for multiple dissertation authors
A new acceptance_date element added to journal article, book, book chapter, and conference paper record types

“Pending publication” is the term we’ve coined for the phase where a manuscript has been accepted for publication but where the publisher needs to communicate a DOI much earlier than most article metadata is available. Some members asked for the ability to register and assign DOIs prior to online publication, even without a title, so this allows members to register a DOI with minimal metadata, temporarily, before online publication. There is of course no obligation to use this feature.

It’s worth calling out the addition of acceptance_date too. This is a key attribute that is heavily requested by downstream metadata users like universities. Acceptance dates allow people to report on outputs much more accurately, so we do encourage all members to start including acceptance dates in their metadata. It’s highly appreciated!

Schema files public on GitLab

I’ve added our latest schema to a new GitLab repository, There you’ll find the schema files, some documentation, and the opportunity to suggest enhancements. The schema has been released as bundle 0.1.1 and also includes our new Grant metadata schema for members that fund research.

The schema has been available in some form for months but at this point we consider it ‘officially’ released to kick off our new but necessary practice of formal schema releases. Any forthcoming updates will be added to the next version.

Schema management process

We’ve been adding sets of metadata and new record types over the years, but also need to have a defined process for small but vital pieces of metadata that you need to provide and retrieve from our metadata records. If you’re wondering what our procedure for updating our schema is, you are not alone! We have not had a formal process, instead relying on ad-hoc requests from our membership and working groups. Our release management and schema numbering has also not been consistent.

Going forward, I will ensure that all forthcoming versions of our metadata schema are be posted as a draft on GitLab for review and comment, and the final version will be officially released via GitLab as well.

It’s important to note that when we talk about “the schema”, we generally mean the input schema specifically i.e. what members of Crossref can register about the content they produce. As always, the output for retrieving that metadata is subject to separate development plans for our Metadata APIs. I’m working with our technical team so we can develop and introduce an ’end-to-end’ approach that doesn’t in future treat the input and the output as such separate considerations.

What’s next

Many of the updates in this latest release have been in the works for some time. Changes to our metadata both large and small are considered carefully, but I’d like to do this in a transparent and cooperative way with our community.

I recently set up the “Metadata Practitioners Interest Group” and we’ve just had our second call. A big topic was how to best manage the ideas and requests from the community. The ability for public comments on GitLab is a first step.

This most recent update contains a mix of long term projects and updates to keep our metadata current and useful. Other changes that are under discussion will require more development on our end. But stay tuned for more information about forthcoming changes, as well information about how you can contribute.

Funders and infrastructure: let’s get building

Josh Brown — Mon, 29 Jul 2019 00:00:00 +0000

Human intelligence and curiosity are the lifeblood of the scholarly world, but not many people can afford to pursue research out of their own pocket. We all have bills to pay. Also, compute time, buildings, lab equipment, administration, and giant underground thingumatrons do not come cheap. In 2017, according to statistics from UNESCO, $1.7 trillion dollars were invested globally in Research and Development. A lot of this money comes from the public - 22c in every dollar spent on R&D in the USA comes from government funds, for example. Funders really do support a LOT of research.

For that research to count, it needs to be communicated. For us to interpret those research communications critically, we need to understand how the research was done and who paid for it.

At Crossref, we’ve been working with funders for many years. The Open Funder Registry was launched (with donated support from Elsevier) in 2012, and provides a taxonomy of funders, each uniquely identified, which has grown to cover 20,000 funders around the world. This resource has helped to connect the organisations that provide research funds to resources, projects, and publications. Some are also members and have been registering content with us. This is a growing trend as more funders start to launch their own open platforms. Funders also consume metadata from Crossref members, using it to track and report on the published outputs of the researchers they support.

More recently, we have been exploring the ways that we can do more in partnership with the funding community. As our board concluded in 2017,

Crossref requires increased emphasis on funders, understanding their needs and requirements and increasingly including funders in the scholarly communication dialogue.

In response, we have explored new services and practical enhancements to our existing portfolio, such as the new grants registration system, which will also power search and lookup tools.

This new initiative will link structured information about grants with DOIs, and enable us to provide open tools to help institutions, publishers, and research supporting organisations to re-use that data and make long-lasting connections between specific funding (and other kinds of research support) and research activities and outcomes. The value of this was beautifully explained by our friends at Wellcome (now members) in this blog post, and was reinforced by a recent survey undertaken by ORCID in which linking grants to outputs was cited as one of the major challenges facing funders. The Crossref Grant Linking System launched this July with a group of early adopter funders, ably supported by the team at Europe PMC.

We’re not stopping there though: we are lucky to have a dedicated and engaged funder advisory group, and we will continue to work with them to understand how our interactions with funders can benefit the wider ecosystem that we support, and help funders to achieve their goals.

There are many platforms providing vital intelligence to funders, from Dimensions to OpenAIRE, which rely on Crossref data. Last month, I was at the OAI11 workshop in Geneva, and it was striking how many presentations included a slide that mentioned using Crossref data. There were 200 people from the open science community there, and they clearly rely on Crossref as a foundational infrastructure to build their ecosystem. That community is also just a subset of the more than 2,500 registered consumers of Crossref metadata. We need to keep asking how this metadata can improve the information available to funders, to their partners and to service providers. Adding grants to the mix will help all of these parties provide an even richer picture of research.

As we move forward with our engagement with the global funding community, new opportunities are becoming visible, and not just for funders. Better experiences for authors, reduced overhead for publishers and easier benchmarking for institutions are a selection of benefits that this work can help us realize.

When we really start to get to grips with opening up information about the inputs to research in the way we already have with its outputs, truly exciting things can happen. The really great thing about this is that, quite literally, everyone benefits: from Crossref members to everyone touched by advances in our understanding of the world. Let’s get building!

Big things have small beginnings: the growth of the Open Funder Registry

Kirsty Meddings — Sun, 21 Jul 2019 00:00:00 +0000

The Open Funder Registry plays a critical role in making sure that our members correctly identify the funding sources behind the research that they are publishing. It addresses a similar problem to the one that led to the creation of ORCID: researchers’ names are hard to disambiguate and are rarely unique; they get abbreviated, have spelling variations and change over time.

The same is true of organisations. You don’t have to read all that many papers to see authors acknowledge funding from the US National Institutes of Health as NIH, National Institutes for Health, National Institute of Health, etc. And wait, are you sure they didn’t mean National Institute for Health Research? (An entirely separate UK-based funder).

And a lot of countries have a National Science Foundation…

If each funder has a unique identifier, our members can include it in the metadata that they register with us, giving a clear and accurate link between the funder of the research and the published outcomes. And we can make that information available to everyone via our API, and build human interfaces so that you can look it up.

Many types of funding bodies are represented in the Funder Registry, from government agencies and large international foundations to small single-mission charities, and everything in between. As well as a unique DOI for each institution, the Registry contains additional metadata that can help to identify the funder such as country, abbreviated or alternate names, translated names, and so on.

The Registry also supports relationships between different funders. These can be hierarchical parent/child relationships for larger organisations, or connections between archival and current entries in instances where a funder has changed its name or become part of another body (to tell us about these kinds of changes you just need to get in touch).

The Registry was donated to Crossref by Elsevier when we first introduced funding information as part of our Content Registration schema back in 2012. We started out with a list of just over 4000 funders. Through an ongoing partnership the list has been - and continues to be - updated on a monthly basis by Elsevier, and sent to Crossref as a formatted XML file that we process and release.

In return, Crossref sends Elsevier a feed of funder names that our members have registered with us that are not present in the Registry, which a team at Elsevier validates and adds to their databases, and then puts those newly-identified funders in to the next iteration of the list they send to us. It’s nice and circular and benefits both parties.

We released v1.27 of the Funder Registry last week, and it contains entries for an impressive 21,356 funders.

I’ve been involved in this project since its inception, and have enjoyed a productive and cooperative working relationship with the team at Elsevier, headed by Peter Berkvens (Senior Product Manager) and Paul Mostert (Director Product Management). I asked them to explain a little about the process from their side:

“Our team maintains a workflow in which Acknowledgement and Funding sections from articles are scanned for appearances of funding organisations using Natural Language Processing techniques. External Elsevier vendors then edit the data and add the validated names of the funders to what is called the Funding Bodies Taxonomy. The latter feeds Crossref’s Open Funder Registry.

Currently, the Taxonomy is nearing 22,000 Funders. It is expected it will grow to 25,000 Funders eventually. When this stage is reached, Elsevier believes that all existing Funders will be covered in the Funder Registry. Elsevier will continue to maintain the list adding new Funders as soon as they appear in scientific papers.

Elsevier’s Primary Articles production workflow for ScienceDirect uses the Funder Registry during the copyediting process, validating and tagging the Funders that appear in the accepted articles for Elsevier journals hosted by ScienceDirect. We then send the funder names and IDs to Crossref as part of our metadata.”

Thanks to everyone involved for getting us ever-closer to a truly comprehensive list of funders.

And if you’re a member who’s not already registering funding information, why not look into getting started? It all leads to richer metadata which means more people can find, cite and re-use research – and we all know that’s a good thing…

License metadata FTW

Rachael Lammey — Fri, 28 Jun 2019 00:00:00 +0000

More and better license information is at the top of a lot of Christmas lists from a lot of research institutions and others who regularly use Crossref metadata. I know, I normally just ask for socks too. To help explain what we mean by this, we’ve collaborated with Jisc to set out some guidance for publishers on registering this license metadata with us.

At the most basic level, complete and accurate license metadata helps anyone interested in using a research work out how they can do so. Making the information machine-readable helps this to be done easily and at scale by all kinds of tools and services.

In this best practice guide, we’re specifically focusing on a use case for license metadata that comes from research institutions. They need to know which version of an article (or other content item) may be exposed in an open repository, and from what date, and tell anyone who comes across the piece of content in the repository what they can do with it once they find it there.

Without this being stated simply and clearly in the Crossref metadata, the institution won’t know which works they can make available and which they cannot, even if you as the publisher know that the item is open access, or is open access after a certain date. This can impact the research community’s capacity to find and use the research you publish.

The guidance offers advice on:

the kind of license information it’s useful to link out to from the Crossref metadata
what the Crossref metadata might look like for:

gold open access content
green open access content with a Creative Commons License
green open access content with a publisher-defined post-embargo license

how to add this metadata to existing or new Crossref deposits

Take a look at the full guidelines here.

Maybe there’s more to the story than this, or more information that you need as a publisher or as a research institution - if so, let us know and we can adapt this document based on your feedback. Requests for socks may be declined.

Putting content in context

Kirsty Meddings — Mon, 13 May 2019 00:00:00 +0000

You can’t go far on this blog without reading about the importance of registering rich metadata. Over the past year we’ve been encouraging all of our members to review the metadata they are sending us and find out which gaps need filling by looking at their Participation Report.

The metadata elements that are tracked in Participation Reports are mostly beyond the standard bibliographic information that is used to identify a work. They are important because they provide context: they tell the reader how the research was funded, what license it’s published under, and more about its authors via links to their ORCID profiles. And while this metadata is all available through our APIs, we also display much of it to readers through our Crossmark service.

Crossmark is also about providing context. It is a button placed on content, which when clicked on brings up a pop-up box that tells the reader about significant updates such as corrections and retractions, together with other information about the publishing and editorial processes that have been applied to the content ahead of publication.

The Crossmark box can display information about authors, funders and licenses. In addition, our members can add “More information” and often do in the form of publication history, links to supporting materials, and peer review information. All of this supporting information helps the reader assess how well the content has been - and continues to be - curated by the publisher.

Who’s in?

250 Crossref members have signed up to use Crossmark (it’s an add-on service with its own fees). Though optional, some star pupils have even added Crossmark to their back-year content and as a result have Crossmark coverage on 99% of their content (kudos to PLOS, Rockefeller University Press and the societies represented by KAMJE, to name a few).

At the other extreme, some have applied Crossmark to less than 10% - these tend to be members with back-year records going back many decades, who are just implementing Crossmark for their more recent research outputs. Crossmark coverage is one of the things tracked in Participation Reports - pop over and take a look if you want to see what your organisation is doing.

So what additional metadata has been registered by members using Crossmark? (data snapshot from our REST API April 2019):

8,711,500 content items have some Crossmark metadata
104,650 updates to content have been registered. Of these
55,000 are corrections and 28,000 errata
16,000 are new versions or new editions
2,700 are retractions and 1,280 are withdrawals
4,830,510 content items have some custom metadata, which appears in the More Information section of the Crossmark box. The most common metadata provided here is publication history, followed by copyright statements, the peer review method used, and whether the item has been checked for originality using Similarity Check.

Some news on clicks and views

We’ve been collecting usage statistics more or less since the Crossmark service launched in 2012, but have lacked a suitable way to share them. This will change later this year! In preparation, I’ve been digging around in the data and uncovered some interesting things.

I was able to do a degree of comparison between Crossmark usage against overall article views using PLOS articles as they make their usage data openly available. I spot-checked fifteen articles and found that most of them had a monthly number of clicks on the Crossmark button in the low-twenties, regardless of the number of total page views the article had received.

The highly viewed paper above shows relatively very few clicks on the Crossmark button, whereas on the paper with fewer views, below, clicks on the button follow the overall pattern of usage.

It’s not unreasonable to suppose that a paper with very high usage has a higher proportion of lay readers visiting it, whereas a more niche paper is being visited by those with a research interest. This is encouraging, as it suggests researchers are interested in checking the status of the content and the additional “trust signals” that the Crossmark box can provide.

Web pages vs PDFs

We track the number of clicks on the Crossmark button in PDFs separately to those that come from web pages. (There are some that we can’t determine, usually because the link behind the button has been incorrectly formatted, but for most members these are minimal.)

I looked at the 30 members with most Crossmark coverage, and averaged the number of clicks over a six month period in 2018. For two thirds of these members, clicks on the Crossmark button on their web pages exceed those in their PDFs, but there are also definite outliers.

Some are easily explained: member #6 hasn’t put the Crossmark button in any of their PDFs, while member #21 has only put it in their PDFs. Member 10 has the button on its article landing pages hidden in a “more information” section that the reader has to click to expand.

That said, member #20 has the button displayed prominently next to the article title but gets 85% of Crossmark clicks from PDFs. There’s no obvious subject bias - four of the members above are physics publishers - two have many more PDF clicks, two have more HTML.

None of the findings above contain nearly enough data to draw any definitive conclusions, but I hope they pique your interest to find out more when we make Crossmark usage statistics available to all members later this year. In the meantime if you have any suggestions/questions, or would be interested in helping us when we come to testing the statistics interface, please let me know.

A simpler text query form

Isaac Farley — Tue, 30 Apr 2019 00:00:00 +0000

The Simple Text Query form (STQ) allows users to retrieve existing DOIs for journal articles, books, and chapters by cutting and pasting a reference or reference list into a simple query box. For years the service has been heavily used by students, editors, researchers, and publishers eager to match and link references.

We had changes to the service planned for the first half of this year - an upgraded reference matching algorithm, a more modern interface, etc. In the spirit of openness and transparency, part of our project plan was to communicate these pending changes to STQ users well in advance of our 30 April completion date. What would users think? Could they help us improve upon our plans?

About a month ago, I reached out to the 21,000 plus users we had on record of using STQ since January 2018. We received nearly 85 responses from the messages we sent. Questions ranged from: if we were making changes, would PubMed ID matching be supported? To: What about the reliability of the returned reference links? And: Could we better accommodate larger reference lists?

Many of the users we heard from told us how STQ was critical to their work. I read all these messages. The concerns raised by users were legitimate and much appreciated. We reassessed our project timeline and plans, and decided to shift course. So, what are we doing?

What’s changing?

The previous hurdle of having to register your email address simply to return reference links was confusing and unnecessary. We removed it.
We previously limited the number of monthly reference links to 5,000 per email address. Most didn’t reach the limit, but those who did were frustrated by it and/or found ways around it. We want you to match and register as many references as possible, so we removed the monthly limit too.
Many of you with long reference lists found that you were occasionally reaching our limit of 30,000 characters per submission. Once again, we want you to match and register as many references as possible so we removed the character limit altogether and instead are just looking at the number of references per submission. We now provide space for 1,000 references per submission (We checked. The most references we have ever received via the STQ form in one submission was around 750. Thus, we rounded up.).
We did make a change to the backend of the service. We updated the algorithm we use to return reference links. We think it’s an improvement. Let us know how you find it.

What’s remaining the same?

Core functionality. It’s all in the name. Retrieve DOIs for journal articles, books, and chapters by cutting and pasting a reference or reference list into a simple query box.
PubMed ID matching. You use it. You need it. We’re keeping it.
Deposits. You’ll still need an email address for this, but we won’t ask for it until you’re at the deposit screen.
The interface. We’re still eager to give the user interface a much-needed refresh, but, as many users pointed out to us, there’s still some core functionality that’s important that we need to retain with any interface update. For instance, you need to be able to easily copy and paste reference links into your reference list. That functionality isn’t going anywhere.
Resetting reference links. Submit references, match, reset, and repeat. Many users like the reset button. It’s not going anywhere either.

XML queries

The change to the backend of the service that I mentioned above is not confined to reference matching and depositing for STQ users. XML queries for reference matching are also now powered by that new backend. We think it’s a seamless transition, but if you find it is not, please let us know.

I’m excited for these changes and hope you are too. I invite you to try the simpler and improved STQ form, and let us know what you think.

Quarterly deposit invoices: avoiding surprises

Isaac Farley — Wed, 10 Apr 2019 00:00:00 +0000

Whenever we send out our quarterly deposit invoices, we receive queries from members who have registered a lot of backlist content, but have been charged at the current year’s rate. As the invoices for the first quarter of 2019 have recently hit your inboxes, I thought I’d provide a timely reminder about this in case you spot this problem on your invoice.

This problem is usually the result of metadata being registered that makes it look as though the content was current, despite the fact that it was backlist. This post will show you what to do if you spot this problem in your latest invoice - and more importantly, how you can avoid this situation in the future.

About current and backlist Content Registration fees

There are different fees for registering content depending on whether it’s current (this year and the previous two years - 2017, ‘18, and ‘19) or backlist (older than that). As an example, it’s $1 each for a current journal article, and $0.15 for each backlist article. So, if you’ve incorrectly registered your content as published in 2019 when actually it was published in 2012, your quarterly invoice will overcharge you based on the metadata discrepancy.

We send you the quarterly deposit invoice at the end of each quarter. This example is an invoice for all deposits of the first quarter of 2018 for username ‘test’ - months January, February, and March.
The BY code represents backlist (or, back year) content (journal article, in this example). Backlist content is charged at $0.15 per content item.
The CY code represents current year content (journal article, in this example, although you can see that this invoice has charges for other content items as well). Current year content is charged at $1 per content item.

Determining whether content is current or backlist

A record is determined to be either a backlist or current year deposit based on the metadata that you deposit with us. If you use our helper tools - Metadata Manager or the web deposit form - the system looks at the information you’ve entered into the “publication date” field. If you deposit XML with us, it looks at the date in the <publication_date> element. And we look at each individual item separately—so even if you’ve put a publication date at journal level, you still need to put it at the journal article level too.

Additionally, sometimes we find that deposits mistakenly include the deposit date in place of the publication date. These two dates - the deposit date and the publication date - are not necessarily one and the same, especially if you are depositing backlist content. Please take care to double check this before you submit your deposit(s).

What to do if you think you’ve registered the wrong publication date

As you can only update a publication date by running a full redeposit, it’s important to get it right the first time. If you’ve registered the wrong publication date and have received an invoice for the wrong amount, please redeposit your content and then get in contact with us. If you do this as soon as you spot the error, we’ll be able to send a new invoice for the correct amount.

Before, during, and after - a journey through title transfers

Isaac Farley — Mon, 25 Feb 2019 00:00:00 +0000

In January, I wrote about how we’ve simplified the journal title transfer process using our new Metadata Manager tool. For those disposing publishers looking for an easy, do-it-yourself option for transferring ownership of your journal, I suggest you review that blog post. But, whether you choose to process the transfer yourself via Metadata Manager or need some help from Paul, Shayn, or myself, there’s more to a transfer than just the click of a transfer button or the submission of an email to support@crossref.org, as I’m sure those of you who have been through a title transfer can attest.

Prepping your title transfer

Sometimes members get on the other side of a title transfer and find you’re encountering problems even if you followed the process for transferring titles. You might find you can register new content for the new title against your own prefix without any issues. But you are not able to update the metadata for back-year records after we’ve made the transfer.

When we investigate, the problem is usually that the DOIs you’re trying to update don’t exist in our system yet. This means the deposit isn’t considered an update to the content, it’s considered a new deposit. And you don’t have permission to do that, since you’re effectively attempting to register new content to a prefix that is not your own.

This problem is because the former publisher didn’t ever register the DOIs with us - even though they’ve been displaying them on their website. This is bad practice and isn’t in keeping with our membership terms, but it does sometimes happen.

Before you request a title transfer, do check with the former publisher that they’ve definitely registered all the DOIs that they’ve been displaying and distributing to their readership. You can spot check this yourself by following a few of the DOI links and checking that they resolve to the right place. If you want a full list of DOIs registered to a journal title, our depositor reports are the place to start. Depositor Reports list all DOIs deposited for a title on a publisher-by-publisher basis. Or, alternatively, if you know the journal cite ID, the unique internal, Crossref identifier for the journal, you can bypass the publisher-by-publisher title list (in my example you’d need to replace my fictional 123456 journal ID with your journal’s cite ID):

`http://data.crossref.org/depositorreport?pubid=J123456`

Top tips for a pain-free title transfer

If your organisation has gained new titles, you’ve checked the depositor report for your new journal and are happy that all the existing DOIs have been registered, then you’re ready to process the transfer. Here are three key steps to ensure a pain-free transfer.

If you are not acquiring all existing journal articles as part of this transfer, you’ll need to contact us at support@crossref.org to confirm the details. Once we have those details sorted, we’ll transfer ownership for the select, specified articles.
Carefully check the existing metadata associated with your new titles - some metadata provided for text and data mining or Similarity Check are publisher-specific and must be updated or removed when content is acquired by another member.
If the metadata supplied is fine, you just need to update the URLs to direct DOIs to your content. You can do this by sending us a URL update file or by redepositing the metadata with the correct URLs.

If you need to update more than the URLs, you should redeposit the metadata with the correct information plus the correct URLs.

Note: If you, as the disposing publisher, are prepared to transfer your journal to an acquiring publisher, and would like to transfer ownership of the journal and all existing journal articles, please try your new title transfer via Metadata Manager.

On the other side

If you follow the steps I’ve outlined above, you should get to the other side of your title transfer with few problems and are likely to encounter smooth metadata seas ahead. That said, some of our members follow these steps to a tee and still are faced with occasional transfer-related problems.

Perhaps the previous journal owner used a different scheme to assign timestamps and now you’re receiving mysterious timestamp errors when you deposit. Or, that same previous owner made a mistake with a previous deposit and accidentally submitted more than one journal title record. Or, you encounter a strange, new error in Metadata Manager when working with your new titles (yes, we’re still in beta!). If so, please reach out to us at support@crossref.org and we’ll help solve what are surely confounding problems, since you’ve undoubtedly read this post in its entirety and taken heed of the above advice.

As always, if you have questions, need guidance as you’re working through this process, or have recommendations on how we can improve title transfers, please contact us at support@crossref.org.

Underreporting of matched references in Crossref metadata

Geoffrey Bilder — Tue, 05 Feb 2019 00:00:00 +0000

TL;DR

About 11% of available references in records in our OAI-PMH & REST API don’t have DOIs when they should. We have deployed a fix, but it is running on billions of records, and so we don’t expect it to be complete until mid-April.

Note that the Cited-by API that our members use appears to be unaffected by this problem.

The gory details

When a Crossref member registers metadata for a publication, they often include references. Sometimes the member will also include DOIs in the references, but often they don’t. When they don’t include a DOI in the reference, Crossref tries to match the reference to metadata in the Crossref system. If we succeed, we add the DOI of the matched record to the reference metadata. If we fail, we append the reference to an ever-growing list which we re-process on an ongoing basis.

You may have seen that the R&D team has been doing work to improve our reference matching system. We will soon be rolling out a new reference matching process that will increase recall significantly.

But while testing our new reference matching approach, we started to see inconsistent results with our existing legacy reference matching system. When we implemented new regression tests, we noticed that, even when using our legacy system, we were consistently getting better results than were reflected in the metadata we exposed via our APIs. For example, we would pick a random Crossref DOI record that included 3 matched references, and when we tried matching all the references in the record again using our existing technology, we would get more matched references than were reported in the metadata.

At first, we thought this might have something to do with sequencing issues. For example, that article A might cite article B, but somehow article A would get its DOI registered with Crossref prior to article B. In this theoretical case, we would initially fail to match the reference, but it would eventually get matched as we continued to reprocess our unmatched references. But this wasn’t the issue. And the problem was not with the matching technology we are using. Instead, we discovered a problem with the way we process references on deposit.

When a member deposits references with Crossref, each reference has to include a member-defined key that is unique to each reference they are depositing in the DOI record. When we match a reference- we report to the members that we matched the reference with key X to DOI Y. The problem is that sometimes members would deposit references with an empty key. If there was only one such reference, then, technically, it would pass our test for making sure the key was unique within the record. So we would process the reference, and match it, and report it via our Cited-by service, but later in the process, when we went to include the matched DOI in the reference section of our API metadata, we’d skip including DOIs for references that had blank keys. The reference itself would be included in the metadata, it would just appear that we hadn’t matched it to a DOI when we actually had.

Again, we estimate this to have resulted in about 11% of the references in our metadata to be missing matched DOIs. We are processing our references again and inserting the correctly matched DOIs in the metadata. We expect the process to complete in mid-April. We will keep everybody up-to-date on the progress of this fix.

We will also be integrating the new matching system that we’ve developed. As mentioned at the start of this post, this matching system will also increase the recall rate of our reference matching and so, the two changes combined, should result in users seeing a significant increase in the number of matched references included in Crossref metadata.

And finally, as part of the work that we are doing to improve our reference matching, we are putting a comprehensive testing framework that will make it easier for us to detect inconsistencies and/or regressions in our reference matching.

Please contact Crossref support with any questions or concerns.

What can often change, but always stays the same?

Isaac Farley — Thu, 24 Jan 2019 00:00:00 +0000

Hello. Isaac here again to talk about what you can tell just by looking at the prefix of a DOI. Also, as we get a lot of title transfers at this time of year, I thought I’d clarify the difference between a title transfer and a prefix transfer, and the impact of each.

When you join Crossref, you are provided with a unique prefix, you then add suffixes of your choice to your prefix and this creates the DOIs for your content.

It’s a logical step then to assume you can tell just by looking at a DOI prefix who the current publisher is—but that’s not always the case. Things can (and often do) change. Individual journals get purchased by other publishers, and whole organisations get bought and sold.

What you can tell from looking at a DOI prefix is who originally registered it, but not necessarily who it currently belongs to. That’s because if a journal (or whole organisation) is acquired, DOIs don’t get deleted and re-registered to the new owner. The update will of course be reflected in the relevant metadata, but the prefix itself will stay the same. It never changes—and that’s the whole point, that’s what makes the DOI persistent.

Here’s a breakdown of how this works internally at Crossref:

Title transfers

Member A acquires a single title from member B. We transfer the title (and all relevant reports) over to member A. Member A must then register new content for that journal on their own prefix. The existing (newly acquired) DOIs maintain the ‘old’ prefix but member A can update metadata against these existing DOIs for that journal. Back-year and current DOIs for that journal may, therefore, have different prefixes—and that’s OK!

Organisation transfers

Member C acquires member D. We move the entire prefix (and all relevant reports) over to Member C, and close down Member D’s account with Crossref. Member C can continue to register DOIs on member D’s prefix (the original prefix) if they want to, or they can use their own existing prefix. So again, back-year and current records for that journal may have different prefixes.

And, if Member C uses a service provider to register metadata on their behalf, we will simply enable their username to work with the prefix.

It’s now easier to transfer titles

We’ve recently made the process of transferring journal titles a lot easier with our new Content Registration tool, Metadata Manager.

Resolutions 2019: Journal Title Transfers = Metadata Manager

Isaac Farley — Thu, 03 Jan 2019 00:00:00 +0000

UPDATE, 12 December 2022
Due to the scheduled sunsetting of Metadata Manager, this title transfer process has been deprecated. Please find detailed guidance for transferring titles on our documentation site here.

When you thought about your resolutions for 2019, Crossref probably didn’t cross your mind—but, maybe it should have…

Because we know—with a high level of certainty—that Shayn, Paul and I will be spending the first few weeks of the year transferring the ownership of many journal titles. Last year we processed almost 60 journal transfer requests during this time, and we’re heading toward a similar number for 2019. There’s no objection; it’s a just a fact. We’re happy to do it, but there is another way.

Unlike previous years, we now have a tool that gives you the control to transfer titles without any intervention from the Crossref support team—Metadata Manager. With just a few clicks, you, as the disposing publisher, can transfer your journal to the acquiring publisher yourself. Here’s how:

Transferring your journal in five easy steps using Metadata Manager:

Log into Metadata Manager using your username and password (the same one you use for the Crossref Web Deposit form).

Find the journal you’re transferring on your Metadata Manager workspace using the “search publications” box and click to load the journal’s container (or, dashboard).

Within the journal container, select Transfer Title from the Action drop-down.

On the transfer title screen select the acquiring (destination) publisher’s name and DOI prefix of where ownership will be transferred to. Click Transfer.

(In addition to transferring ownership of the title itself, all existing journal article DOIs previously registered will also be transferred to the new owner using this mechanism. They will persist on their original prefix, but the acquiring publisher will be able to update the metadata associated with these DOIs).

Confirm the title transfer. It may take up to 24 hours for the transfer to be reflected within Metadata Manager, and we’ll send a courtesy email to the acquiring (destination) publisher’s technical contact when the transfer has been completed.

As always, if you have questions, need guidance as you’re working through this process, or have recommendations on how we can improve title transfers—or anything else within Metadata Manager (the tool is in beta)–please let us know at support@crossref.org. There’s also comprehensive support documentation available for Metadata Manager to help and guide you.

Newly approved membership terms will replace existing agreement

Ginny Hendricks — Wed, 05 Dec 2018 00:00:00 +0000

In its July 2018 meeting, the Crossref Board voted unanimously to approve and introduce a new set of membership terms. At the same meeting, the board also voted to change the description of membership eligibility in our Bylaws, officially broadening our remit beyond publishers, in line with current practice and positioning us for future growth.

Tl;dr

It’s a very good thing to have clearer terms; we want everyone to understand what Crossref is about and what you’re getting into. It’s a material change so we will be notifying members by direct email in December. Nobody needs to sign anything as the new terms are not signed, but are click-through acceptances on application, and that process is already in effect for new applicants. The new terms come into effect on 1st March 2019 for existing members and no action is needed.

If you’re a sponsored member you’ll have a slightly adapted message soon as we work with your sponsor.
If you’re an NGO or US State Actor you will receive a slightly adapted message.

This post is for background explanation and information. We will email existing members directly, but no acceptance or signature—nor any action—will be needed.

Why are we updating the terms?

Being almost 20 years old the old agreement is out-of-date with current practice and technology, and has become quite long and confusing, especially for applicants for whom English is not their first language. Specific reasons include:

1. To improve efficiency

Over the years we’ve had feedback that our application process is too long and involved. The membership agreement used to be signed manually by each new Crossref member, often days after they applied. We also now process around 180 new members each month which is too many for a wholly manual process managed by just one person.

2. To clarify the wording

People would tell us that the agreement is too long and confusing, especially when English is not their first language. There are often questions about the “legalese” style of language that takes up too much time in back-and-forth discussions to ensure everyone has understood. Also, the main structure of the agreement has been in place for over a decade and needs updating to avoid confusion and to align with up-to-date language, services, technologies, and current practices.

3. To emphasize the community aspect and our members’ obligations

It is quite a commitment to participate fully in Crossref, and we want people to understand up-front what their obligations are as part of the collective membership. And also to realize what value they are receiving as well as contributing to other members. We needed clearer terms so that every organisation can understand what they are getting into.

Additionally, moving from signing contracts to click-through acceptance of standard terms emphasizes that Crossref is not a service provider or vendor. We are a not-for-profit community organisation. We don’t have the resources to negotiate and keep track of individual custom agreements.

What’s changing, step-by-step

We consulted with former and current legal counsel, the Membership & Fees Committee, and also with the M&F organisations individually. We have also absorbed a lot of feedback from many other members of all kinds and sizes.

For new members

The manually-signed membership agreement has already—for new members— been turned into a set of click-through terms that organisations agree to as part of the initial application process. It is no longer a separate document that needs to be signed or countersigned. This will simplify the application process for both new applicants and our staff.

For existing members

The new membership terms will come into effect for existing members on March 1st, 2019. Because this is a material change to the terms, we will be emailing members with more information but it’s important to note that no action is necessary from existing members. The new terms will replace the old terms automatically.

The table below sets out clause-by-clause the precise changes. Here is the 2018 membership agreement and the new terms in full.

The nitty-gritty details

Topic	New section	Old section	Summary of change(s)
Overall			Eliminates legalese in favor of plain English. Updates defined terms to current usage. Shifts from execution by signature to acceptance by affirmative action.
Introduction	Background	1	Updates description of Crossref’s activities to be current. Provides for a new applicant’s acceptance of Terms upon acceptance of application by Crossref and payment of first annual fee.
Members’ rights	1	2(a)	Streamlines wording; eliminates reference to right to recommend working committee members.
Members’ obligations	2	2(b)	Significant revision. Old 2(b) mentioned only payment of fees and appointment of a contact person. New Sec. 2 aims to capture all of a Member’s operational obligations in one place.
Metadata deposits	2(a), (b)	3(a)(i)	Updates language regarding metadata deposits to current terminology and practice.
Rights to content	2(c)	15	Streamlines wording.
Registering identifiers	2(d)	3(a)ii)	Streamlines the language around registering identifiers.
Linking	2(e)	3(a)(iii)	States, in clearer language, the obligation to embed identifiers.
Reference linking	2(f)	3(a)(iv)	Eliminates outdated provision on Cross-Linking; replaces with a best efforts covenant to engage in Reference Linking.
Display identifiers	2(g)	N/A	Adds an obligation to comply with Crossref’s display guidelines and ensure each identifier is hyperlinked to be citable.
Maintaining and updating metadata	2(h)	3(b)	Streamlines language. Adds obligation to maintain the URL and the accuracy of identifier data. Adds common examples of failure to maintain and update metadata.
Archiving	2(i)	3(d)	Adds link to examples of third-party archive providers. Adds option for Crossref to point to a “defunct DOI” page. Inserts best efforts obligation to contract with a third-party archive.
Content-specific obligations	2(j)	N/A	Adds reference to Crossref’s record type rules and obligation to comply.
Fees	3	2(b)	Old agreement referred generally to “all membership dues and any charges or fees as established by the Board from time to time and set forth on the PILA Site.” New Section 3 aims to summarize the categories of fees associated with membership, including a reference to service fees for optional services if and when elected by the Member. Adds Member obligation to cover wire transfer fees/other payment costs.
General license	4(a)	4	Clarifies that the license grant covers only metadata and identifiers “corresponding to such Member’s Content.”
Metadata rights & limitations	4(b)	5	Significantly streamlines wording.
Crossref’s IP	4(c)	6	Significantly streamlines wording.
Distribution of metadata	5	9(b)	Updates language regarding Crossref’s rights to distribute Metadata. Adds an explicit carveout for a Member’s reference distribution preference.
	N/A	7, 8, 9(a)	Deletes extensive provision relating to obsolete “Clean-Up” and “Reverse Look-Up” services. Deletes provisions relating to obsolete “caching and transfer” activities, and local hosting.
Use of marks	6	10	Substantially rewritten, including to reflect Crossref’s more permissive approach to use of its logo.
Maintenance of the Crossref Infrastructure	7	[No analog.]	Adds covenant of Crossref to maintain the Crossref Infrastructure.
Term	8	11	Eliminates the concept of automatically renewing 12-month terms. Replaces with a perpetual term that continues until superseded by an amended version.
Termination of membership	9(a)	11	Provides for termination by the member upon written notice, rather than 90 days’ written notice, to align with the Bylaws. Adds a for-cause termination right by the Member, and corresponding right to receive a refund of fees. Sets out certain bases for termination of membership by Crossref, consistent with the Bylaws.
Appeal rights	9(b)	13	No material change.
Effect of termination of membership	9(c)	12	Adds refund right for for-cause terminations.
Enforcement	10	13	Replaces “Crossref has the right but not the obligation to enforce the terms of this Agreement …” with “Crossref shall take reasonable steps to enforce these Terms … .”
Governing law; venue	11	14(a)	Keeps New York as choice of law, but moves forum to Boston, nearer to Crossref’s US location.
Disputes	12	14(b)	No material change (but note venue provision moved to 11(a)).
	N/A	15	Eliminates mutual “warranty” provision; addresses rights to content and anti-infringement under other provisions.
Indemnification	13	16	Removes concept that Member is indemnifying other Crossref Members. Streamlines and cleans up the indemnity language.
Limitation of Liability	14	17	Adds explicit reference to the Crossref Infrastructure.
Assignment	16(c)	22	Removed language providing that Crossref’s consent to assignment of the Terms shall not be unreasonably delayed or conditioned.
Amendment	18	2(c)	Old: “The Board shall have the power to modify the terms of this Agreement by publishing amended versions that will automatically supersede prior versions … . PILA will use its reasonable discretion in deciding if a modification is material, and if so will provide written notice” to the Member of the material changes. New: “These Terms may be amended by Crossref, via updated Terms posted on the Website and emailed to each Member not less than sixty (60) days prior to effectiveness. By using the Crossref Infrastructure after the effective date of any such amendment hereto, the Member accepts the amended Terms.”
Data privacy	19	N/A	Adds a GDPR-compliant privacy provision; adds a linked reference to Crossref’s new Privacy Policy.
Compliance	20	N/A	Adds a mutual compliance covenant and an OFAC/sanctions representation.
Various legal “boilerplate” terms (taxes, waiver, independent contractor	15-17	18-28	Streamlined; replaced with more contemporary formulations; eliminated some excess verbiage.

Thanks for reading this far!

Please contact our member experience team with any questions.

Good, better, best. Never let it rest.

Jennifer Kemp — Tue, 16 Oct 2018 00:00:00 +0000

Best practices seem to be having a moment. In the ten years since the Books Advisory Group first created a best practice guide for books, the community beyond Crossref has developed or updated at least 17 best practice resources, as collected here by the Metadata 2020 initiative. (Full disclosure: I co-chair its Best Practices group.)

Books have been one of the fastest growing resource/record types at Crossref for some time, and best practices are just one of the Book Advisory Group’s efforts. Over the past ten years, the members of the books group have updated and added to the guide, and it’s now time for it to get some visibility, so we have added it to our website for easy reference.

These best practices are not documented for the sake of it. They have real value and can help guide internal conversations to evaluate current practices, for example. They can also play a role in making or changing policies, training staff and providing instructions to authors on citation formatting.

Here are a few recent changes I’d like to highlight:

A new section has been added that addresses books hosted on multiple platforms
The section on versions, (including books in multiple formats) has been expanded and clarified
A section on the use of DOIs in citations has been added

It is neither final nor comprehensive, and never will be. Best practices by their very nature must evolve over time—and those with such a broad scope as books will inevitably lack some detail—but that’s all the more reason for the community to stay engaged. Looking ahead to future work from the group, chapter-level metadata is likely to get more attention.

Over the past few years the Books Advisory Group, chaired with aplomb by Emily Ayubi of the American Psychological Association (APA), has spent a lot of time on Crossref initiatives, like Multiple Resolution and DOI display changes but also on broader industry topics like ORCID iDs for book authors, and the Books Citation Index.

As Emily’s term as chair comes to an end this year, we welcome Charles Watkinson of the University of Michigan as chair starting in 2019. The group meets next on 12 December when we will hear from Coko about Editoria and have a discussion about developing our new Metadata Manager Content Registration tool for books, and more.

If you want to share your thoughts on best practices or if you have other topics you’d like us to consider, please get in touch.

Metadata Manager: Members, represent!

Jennifer Lin — Mon, 15 Oct 2018 00:00:00 +0000

Over 100 Million unique scholarly works are distributed into systems across the research enterprise 24/7 via our APIs at a rate of around 633 Million queries a month. Crossref is broadcasting descriptions of these works (metadata) to all corners of the digital universe.

Whether you’re a publisher, institution, governmental agency, data repository, standards body, etc.: when you register and update your metadata with Crossref, you’re relaying it to the entire research enterprise. So make sure your publications are fully and accurately represented.

Metadata Manager is here to help

This year, we’ve released a new tool aimed to make this easier and give you, members, full control over your metadata. Presenting: Metadata Manager. It helps to:

Simplify and streamline the Content Registration service, with a user-friendly interface
Give you greater flexibility and control of metadata deposits
Support users who are less familiar with XML
Boost metadata quality, encourage cleaner and more complete metadata records

Metadata Manager is available to all our members and the service providers they work with, providing assistance with a wide range of metadata-related tasks:

Regular Content Registration conducted by journal staff, editors and service providers
Registering corrections, retractions, or other editorial expressions of concern
Matching references to their DOIs and registering them with the publication
Adding metadata to existing records such as license and funding information, abstracts, or data citations
Late-arriving editorial updates/corrections after initial publication
Unexpected corrections to production hiccups
Emergency editorial changes that affect publication record
Accelerated registration for special pieces published outside of regular workflow
Securely and efficiently transfer titles to another publisher as the authorized owner

Issues arise all the time in the dynamic and challenging work of scholarly communications. Metadata Manager provides a fast and easy way to meet these head-on when broadcasting new content or updating existing content. Submissions through this tool are processed immediately upon submission (i.e., no queues!).

This new tool empowers our members to “represent” in the exhilarating thrum of data reaching our API users. At this moment in time, it only supports journals, but our development team is currently working hard to include the remaining record types.

Features

Here’s a smattering of highlights from the Metadata Manager feature list:

All metadata: easily adds any and all metadata, allowing publishers to add richness and depth to their records.
Prevents rejected submissions: it ensures you have satisfied all the basic Content Registration requirements and points out any input errors.
Expedited deposit: the Content Registration system processes each submission immediately, bypassing the deposit queue.
Historic log: easy to read archive of all previous submissions.
Effortless review: provides a clean, condensed view of metadata (invariably complicated and lengthy) to support human review of the content before submission.
Aids members to follow best practices: checks for completeness and reminds users of the full breadth of metadata available for the article, volume/issue, and the journal itself.
Full control over title transfers: no need to make these requests through our support channels. Complete the transfer at your convenience, directly through the system.

For those of you that have looked at your own metadata contribution with the use of our new Participation Reports, you’ll find using Metadata Manager a quick and useful way to help you level-up your records.

Members, represent!

We invite you to register and update your publications with Metadata Manager, relay the metadata fully and accurately to the entire research enterprise. Check out the comprehensive help documentation to find out how to set up your workspace and get started right away with your usual Content Registration login details.

As mentioned, we are continuing development, adding support for all remaining record types as well as enhancing existing features. The webDeposit form will remain available throughout this time. For journal publishers, give us a whirl and let us know if you see something missing or there’s a function that would improve your Content Registration experience!

100,000,000 records - thank you!

Ed Pentz — Wed, 26 Sep 2018 00:00:00 +0000

100,000,000. Yes, it’s a really big number—and you helped make it happen. We’d like to say thank you to all our members, without your commitment and contribution we would not be celebrating this significant milestone. It really is no small feat.

To help put this number into context; the National Museum of China has just over 1 million artifacts, the British Library has around 25 million books, Napster has 40 million tracks, and Wikidata currently contains 50 million+ items.

Digging into the 100 Million

Within these 100 Million registered content records there are many different record types.

And within these record types, more than 69 million records have full-text links, 31 million+ have license information and 3 million+ contain some kind of funding information. An overview of these and other Crossref vital statistics is available on our dashboard.

100 Million—what does your contribution look like?

Our recently-launched participation reports allow anyone to see the metadata Crossref has. It’s a valuable education tool for publishers, institutions and other service providers looking to understand the availability of the metadata they have registered with us.

Through an itemized dashboard Participation Reports allows you to monitor the metadata you are registering, even if this work is done by a third party or another department. You can see for yourself where your gaps are, and what you could improve upon. Next to each metadata element, there’s a short definition, letting you know more about it, and—crucially—what practical steps you can take to improve the score.

The dashboard provides the percentage counts across ten key metadata elements: References, ORCID iDs, Funder Registry IDs, Funding award numbers, Crossmark metadata, License URLs, Text-mining links, Similarity Check URLs, and Abstracts.

And not only can you see your own metadata—the dashboard enables you to view the registered metadata of all our 11,076 members.

How are these 100 Million content records being used?

Every service we provide is based on our metadata, and our APIs expose all of that metadata. Over the past year or so we have been collecting use cases from members that actively utilize the Metadata APIs and have turned these into a Metadata APIs blog series so that we can share these stories of how our metadata is used with the wider community.

A big number. Even bigger ambitions.

Gaps or errors in metadata are passed on to thousands of other services, which causes problems downstream and means we all suffer. So it makes sense for the metadata you deposit to be as accurate and complete as possible. The more elements there are to the metadata, the higher the chance of others finding and using the content. We aim to continually find effective ways to communicate this wider story around the importance of open infrastructure and metadata.

Over the years we’ve made great progress in connecting information about researchers, their affiliations, grants, and research outputs. Imagine how much more powerful this information would be if supplemented by more comprehensive, accurate, and up-to-date metadata.

Sources - all data as of Sept 26, 2018
National Museum of China has 1,050,000 artifacts
The British Library has around 25 million books, more than any other library
Wikidata currently contains 50,290,632 items
NAPSTER currently has 40 million tracks (Napster is known as Rhapsody in the US)

Where does publisher metadata go and how is it used?

Laura J Wilkinson — Mon, 17 Sep 2018 00:00:00 +0000

Earlier this week, colleagues from Crossref, ScienceOpen, and OPERAS/OpenEdition joined forces to run a webinar on “Where does publisher metadata go and how is it used?”.

Stephanie Dawson explained how ScienceOpen’s freely-accessible, interactive search and discovery platform works by connecting and exposing metadata from Crossref. Her case study showed that articles with additional metadata had much higher average views than those without - depositing richer metadata helps you get the best value from your DOIs!

Pierre Mounier of OPERAS/OpenEdition showed us how a variety of persistent identifiers (PIDs) including DOIs, ORCID iDs, and Funder Registry IDs have been used on OA book platforms to improve citations, author attribution, and tracking of funding. He described a forthcoming annotations project with Hypothes.is, and explained how Crossref metadata is being used in both usage and alternative metrics.

Five ways to register content with Crossref

My overview of Content Registration outlined the five ways to register content with Crossref:

Via the manual web deposit form
Through Crossref’s new Metadata Manager tool (beta)
With OJS’s Crossref plugin - more information here (see OJS downloads Version 3.1.0 and above is the best option for supporting the fullest Crossref metadata)
With a manual XML upload file
Or, using HTTPS to POST XML

I also emphasized the importance of depositing, adding, and updating your metadata, and spoke about:

Basic citation metadata: titles, author names, author affiliations, funding data, publication dates, issue numbers, page numbers, ISSNs, ISBNs…
Non-bibliographic metadata: reference lists, ORCID iDs, license data, clinical trial information, abstracts, relationships…
Crossmark: errata, retractions, updates, and more
How important it is to have accurate, clean, and complete metadata
The importance of registering your back-year records

How to see the metadata you have

Anna Tolwinksa, Crossref’s Member Experience Manager, gave us an overview of the new Participation Reports tool. She explained how Participation Reports allows anyone to see the metadata Crossref members have registered with us, and how you can see for yourself where the gaps in your metadata are, and—importantly—how you can improve your coverage.

What we learnt

There are 10 key metadata elements or checks in Participation Reports that aid in Crossref members’ content discoverability, reproducibility and research integrity:
- References
- ~~Open References~~ [EDIT 6th June 2022 - all references are now open by default].
- ORCID iDs
- Funder Registry IDs
- Funding award numbers
- Text mining URLs
- License URLs
- Similarity Check URLs
Every day, research organisations around the world rely on metadata from Crossref, and use it in a variety of systems. Here are a few examples. Many organisations that enable research depend on Crossref’s metadata; we received over 650 million queries just last month
Crossref members should check Participation Reports to see what percentage of their content includes rich metadata If the percentages are low, Crossref is happy to work with you to help understand and improve your coverage
Richer metadata helps research to be found, cited, linked to, assessed, and reused
To make sure your work can be found!

Catch up with the webinar recording, and slides from Laura, Stephanie, Pierre, and Anna’s presentations, and please contact us if you have any questions.

Leaving the house - where preprints go

Jennifer Lin — Tue, 21 Aug 2018 00:00:00 +0000

“Pre-prints” are sometimes neither Pre nor Print (c.f. https://doi.org/10.12688/f1000research.11408.1, but they do go on and get published in journals. While researchers may have different motivations for posting a preprint, such as establishing a record of priority or seeking rapid feedback, the primary motivation appears to be timely sharing of results prior to journal publication.

So where in fact do preprints get published?

Although this is a simple question, we have not had an easy way to answer how this varies across disciplines, preprint repositories and journals. Until now. Crossref metadata provides not only an open and easy way to do so, but up-to-date data to get the latest results.

rOpenSci makin’ it sweet & easy

Crossref asks preprint repositories to update their metadata once a preprint has been published by adding the article link into its record via the “is-preprint-of” relation. As the record is processed, we make the link available going both directions, while preserving the provenance of the statement in the metadata output (“asserted-by”: “subject” or “asserted-by”: “object”). This results in bidirectional assertions in the Crossref REST API where search engines, analytics providers, indexes, etc. can get from the preprint to the article (“is-preprint-of”) as well as vice versa (“has-preprint”), making it easier to find, cite, link, assess, and reuse.

Using rOpenSci’s R library for the Crossref REST API (rcrossref), we pulled all articles connected to a previous preprint (https://api.crossref.org/works?filter=relation.type:has-preprint&facet=publisher-name:&rows=0) and then aggregated them based on journal via their ISSNs (https://api.crossref.org/works?filter=relation.type:has-preprint&facet=issn:), tallying the results in a tidy table with the journal name (ex: PLOS Biology (https://api.crossref.org/journals/2167-8359)).

The big reveal

So without further delay, let’s look at the results of the 20 journals with the highest number of preprints associated with its articles (data from August 21, 2018):

Publisher	Journal	Count
PeerJ	PeerJ	1184
Springer Nature	Scientific Reports	394
eLife	eLife	375
PLOS	PLOS ONE	338
Proceedings of the National Academy of Sciences	PNAS	205
PLOS	PLOS Computational Biology	196
Springer Nature	Nature Communications	187
PLOS	PLOS Genetics	169
The Genetics Society of America	Genetics	168
Oxford University Press	Nucleic Acids Research	148
Oxford University Press	Bioinformatics	138
The Genetics Society of America	Genetics	120
The Genetics Society of America	G3: Genes, Genomes, Genetics	104
Cold Spring Harbor Laboratory	Genome Research	104
Oxford University Press	Molecular Biology and Evolution	100
MDPI AG	Energies	98
MDPI AG	Sensors	96
Springer Nature	BMC Genomics	92
MDPI AG	International Journal of Molecular Sciences	86
JMIR Publications	Journal of Medical Internet Research	83

This list has not been normalized or weighted based on the size of the journal. The following observations are informed speculations, as we can only infer so much from the raw data:

Disciplinary practice: This phenomenon where preprints are a part of disciplinary practice accounts for about half of the journals represented on the list. Certain communities such as genetics and computational fields have been early adopters of preprints. As such, we see higher rates of preprint-to-article publication in journals that publish their work.
Partnerships: Partnerships that facilitate submission from the preprint repository directly to a publisher or peer review service (ex: BioRxiv B2J program) make it easier for researchers to move from preprint-sharing seamlessly to submitting their journal article manuscript.
Tie-ins: A quarter of the journals on the list are run by publishers with a preprint service, and have been able to tie together both arms of publishing. This removes barriers to journal article submission in the same manner as integrations between repositories and publishers, but does so as a single party.
Publisher support and treatment: We also see that strong proponents and early partners of preprint repositories tend to have higher counts. Some publishers have been more outspoken in their welcome of preprints, such as PNAS. Sometimes this support also comes in the form of special treatment. In the process of crafting editorial policy on publishing results previously posted in a preprint, some journals have carved out particular affordances in their publication workflow and content delivery streams that may contribute to the higher counts of articles. For example, Nature Research displays the preprints of submitted articles under consideration: https://nature-research-under-consideration.nature.com/.
Mega-journals: Mega-journals such as Scientific Reports and PLOS ONE have not discouraged preprints. As such, and due to the size of their publication output, they have easily found a place among the higher counts on the list.

Taking a closer look

One major consideration in these results, concerns what’s missing in the data. These fall into two camps: incomplete member data, and incomplete membership coverage.

We have been working with our members to deposit preprints using the proper record type, and to provide links to published articles in their metadata. However, not all have yet done so (ex: SSRN), leading to holes in our research nexus graph, which subsequently detracts from the completeness of the data.

We celebrate the preprint repositories who are required to update their metadata when an article is published from a preprint, thereby populating the map with critical bridges between preprints and articles. Crossref participation benefits not only the content owner, but the membership at large and all the systems across the research ecosystem powered by Crossref metadata.

Lastly, this data is dependent on the coverage of preprint repositories who register content with us. We are thrilled that Center for Open Science, our newest preprints addition who represents 21 community repositories, has recently filled in swaths of the map. But there remain dead zones in the research graph from repositories who are not Crossref members (ex: ArXiv). Their disciplines, as a result, are under represented in these results.

Everyone dive in!

As to the question of “where do preprints get published?”, anyone in fact can answer this question based on the metadata Crossref collects and provides to the community as an open infrastructure provider. We encourage the community to explore and analyze the data further with other available datasets to glean more insights on how scholarly communications is changing with the increasing growth of preprints. For example, the effective results across all journals represented can be weighted based on the number of articles published by each journal.

Crossref data is open for all to examine and reuse through our REST API. Please dive in and share your findings with us!

3,2,1… it’s ‘lift-off’ for Participation Reports

Anna Tolwinska — Wed, 01 Aug 2018 00:00:00 +0000

Metadata is at the heart of all our services. With a growing range of members participating in our community—often compiling or depositing metadata on behalf of each other—the need to educate and express obligations and best practice has increased. In addition, we’ve seen more and more researchers and tools making use of our APIs to harvest, analyze and re-purpose the metadata our members register, so we’ve been very aware of the need to be more explicit about what this metadata enables, why, how, and for whom.

This week we take an important step towards this goal with a much-anticipated announcement: Participation reports are in beta release—so come along and take a look!

What does this mean?

Participation Reports gives—for the first time—a clear visualization of the metadata that Crossref has. Search for any member to find out what percentage of their content includes 10 key elements of information, above and beyond the basic bibliographic metadata that all members are obliged to provide. This includes metadata such as ORCID iDs for contributors, funding acknowledgements, reference lists, and abstracts—richer metadata that makes content more discoverable, and much more useful to the scholarly community as a whole, including among members themselves.

You can filter by content such as journal articles, book chapters, datasets, and preprints, and compare current content (past two calendar years and year-to-date) to back file content (older than that). And within the journal articles view, you can drill down to view the metadata completeness for each individual journal. We hear that editorial boards are keen to see that aspect!

We’re delighted that participation reports are now available in beta. That means that while we are confident that the data shown is accurate, there could be the odd glitch as we monitor use.

Thank you to everyone who has helped us to test the reports and provided so much valuable feedback. We plan to expand and improve participation reports to include additional metadata elements, metadata quality checks, and adherence to Crossref best practice such as DOI display. We’re still listening so do get in touch if you have questions or suggestions, or would like a more detailed walk through. There is also a feedback button right in-situ in the tool.

Preprints growth rate ten times higher than journal articles

Jennifer Lin — Thu, 31 May 2018 00:00:00 +0000

The Crossref graph of the research enterprise is growing at an impressive rate of 2.5 million records a month - scholarly communications of all stripes and sizes. Preprints are one of the fastest growing types of content. While preprints may not be new, the growth may well be: ~30% for the past 2 years (compared to article growth of 2-3% for the same period). We began supporting preprints in November 2016 at the behest of our members. When members register them, we ensure that: links to these publications persist over time; they are connected to the full history of the shared research results; and the citation record is clear and up-to-date.

Summary

As of May 24, 2018 we have 44,388 works (see API query https://api.crossref.org/types/posted-content/works with a json viewer) registered as posted content. Today that number is over 150k. Preprints are part of this record type category, which is meant to house scholarly outputs that have been posted online and intended for publication in the future.

For a more granular view, see the monthly stats captured by Jordan Anaya in PrePubMed. This data is based on a slightly different set of preprint repositories, though both show the same trends.

The figure below shows the preprints registered with Crossref, broken down by repository.

We eagerly await our newest preprints member, Center for Open Science, who will soon be registering the preprints from their 18 community archives with us (~9k preprints total to date).

Metadata coverage

We accept a range of metadata for the preprints registered with us, including:

Repository name & hosting platform
Contributor names & ORCID iDs
Title
Dates (posted, accepted)
License
Funding
Abstract
Relations
References

As with all resource/record types, certain metadata is required, though others are optional. We encourage full coverage of metadata in the record where applicable and possible. So what are publishers including in their posted content records? The summary view is as follows:

License: 9926 (json), 22% (PeerJ Preprints, ChemRxiv)
Funder: 0 (json), 0%
ORCID: 19309 (json), 44% (bioRxiv, PeerJ Preprints, Preprints.org, ChemRxiv)
Abstracts: 35874 (json), 81% (bioRxiv, PeerJ Preprints, ChemRxiv)
References: 1921 (json):, 4% (JMIR)

Compared to all the published content registered with us over time, preprints have above average coverage of ORCID iDs deposited and show well above average with abstract metadata. However, they are significantly lagging behind with depositing references, license, and funding metadata. (See a summary of the full corpus stats taken two months ago in the blog post, A Lustrum over the Weekend).

Preprint-article pairs

Members registering preprints have an obligation to update the metadata record when a journal article is subsequently published, to clearly identify this work. This pairing is passed on to our metadata users: indexing platforms; recommendations engines; platforms; tools, etc. which pull from our APIs. (The preprint landing page also must link to the article.) As such, the preprint-article pairings are amassing as each week passes. We currently have a total of 12983 (json) preprints connected to articles. The figure below provides the counts based on repository.

Citations

We can see from preprint Cited-by counts that researchers are indeed citing preprints in their articles. This practice is an extension of the common citation behavior to provide evidence for and credit to previous work, a natural consequence of work shared with their peers. The most highly cited preprint papers (json) as of May 24, 2018 are as follows. In some cases, a subsequent paper was published from the results shared in the preprint. These have also accrued citations in their own right and these are also indicated in the table below.

No.	Cited-by	Preprint DOI	Preprint title	Date	Subsequent journal article	Citations of journal article
1	Cited-by 72	https://doi.org/10.1101/005165	qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots	May 14, 2014.	n/a	n/a
2	Cited-by 63	https://doi.org/10.1101/002824	HTSeq - A Python framework to work with high-throughput sequencing data	August 19, 2014	Bioinformatics, https://doi.org/10.1093/bioinformatics/btu638	2372
3	Cited-by 43	https://doi.org/10.1101/030338	Analysis of protein-coding genetic variation in 60,706 humans	May 10, 2016	Nature, https://doi.org/10.1038/nature19057	1598
4	Cited-by 38	https://doi.org/10.1101/002832	Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2	November 17, 2014	Genome Biology, https://doi.org/10.1186/s13059-014-0550-8	3284
5	Cited-by 32	https://doi.org/10.1101/021592	Salmon provides accurate, fast, and bias-aware transcript expression estimates using dual-phase inference	August 30, 2016	Nature Methods, https://doi.org/10.1038/nmeth.4197	112
6	Cited-by 22	https://doi.org/10.1101/012401	DensiTree 2: Seeing Trees Through the Forest	December 8, 2014	n/a	n/a
7	Cited-by 21	https://doi.org/10.1101/011650	FusionCatcher - a tool for finding somatic fusion genes in paired-end RNA-sequencing data	November 19, 2014	n/a	n/a
8	Cited-by 19	https://doi.org/10.1101/048991	Analysis of shared heritability in common disorders of the brain	September 6, 2017	n/a	n/a
9	Cited-by 18	https://doi.org/10.1101/006395	Error correction and assembly complexity of single molecule sequencing reads	June 18, 2014	n/a	n/a
10	Cited-by 18	https://doi.org/10.1101/032839	Spread of the pandemic Zika virus lineage is associated with NS1 codon usage adaptation in humans	November 25, 2015	n/a	n/a

The relationship between preprints and the proceeding publication is an interesting area that is not yet well understood. We invite the community to analyze the Crossref metadata using the REST API in concert with other datasets. For example, the citation lifecycle for these two research products has been one of speculation so far without a systematic investigation into patterns and timeframes of preprint citations and those of its succeeding article across the corpus. Here, submission dates would be critical data to this research question as publication windows vary significantly by publisher and by paper.

How good is your metadata?

Kirsty Meddings — Thu, 26 Apr 2018 00:00:00 +0000

Exciting news! We are getting very close to the beta release of a new tool to publicly show metadata coverage. As members register their content with us they also add additional information which gives context for other members and for services that help e.g. discovery or analytics.

Richer metadata makes content useful. Participation reports will give—for the first time—a clear picture for anyone to see the metadata Crossref has. This is data that’s long been available via our Public REST API, now visualized.

Who are participation reports for? Everyone!

It’s an opportunity to evaluate and educate. See for yourself where the gaps are, and what our members could improve upon. Understand best practice through seeing what others are doing, and learn how to level-up.

Monitor what metadata is being registered, even if this work is done by a third party or another department. And see what other organisations in scholarly communications see when they use Crossref metadata in their research, tools, and services.

The beta release—expected after acceptance testing some time late May—will let anyone look up any of our 15,000+ members and see whether they are registering ten key elements that add context and richness to the basic required bibliographic metadata.

What do we mean by ‘richer metadata’?

The ten checks for Beta, will be:

References
~~Open references~~ [EDIT 6th June 2022 - all references are now open by default].
ORCID iDs
Funder IDs
Funding award numbers
Crossmark metadata
License information
Full text links
Similarity Check URLs
Abstracts

Each of these additional metadata elements helps increase discovery and wider and more varied use—and usefulness—of research outputs.

Why are we doing this and what do we mean by ‘participation’?

Over the years when we’ve talked with our members about their metadata, we learned that many just can’t be certain exactly how they’re performing. It could be that they’ve outsourced Content Registration to another service provider or larger publisher, or it could be they just weren’t previously aware they could collect and share authors’ ORCID iDs, Funder IDs, and so on. So our primary aim is to give our members the information they need in order to make a case for improving their metadata records. Each check will come with information about why it is important and guidance on how to improve. Additionally, with the growing use of Crossref as a central source of metadata for the research community, it’s in everyone’s interest to be as transparent as possible about what metadata we have - and encourage greater understanding of what’s possible.

Member ‘participation’ is an important concept. Crossref distinguishes itself from other DOI registration agencies by providing this richer infrastructure which allows for things like funding information, license information, links between data and preprints, and so on—all contributing to the research nexus for everyone’s benefit.

Membership of Crossref is not just about getting a persistent identifier for your content, it’s about placing your content in context by providing as much metadata as possible and looking after it long-term.

Here’s a sneak preview of what the report will look like:

So whether you’re a member who wants to run a “health check” on your own metadata, or a consumer of metadata interested in what’s available and from whom, watch this space for Participation Reports!

Would you like a heads-up on your report, pre-beta?

Beta will be released some time in May or June this year, following acceptance testing with members and others. Then we’re looking for about 20 members to have a half-hour phone call with a walk-through ‘health check’. Please contact Anna if you’d like to schedule one.

Redirecting redirection

Geoffrey Bilder — Tue, 24 Apr 2018 00:00:00 +0000

Crossref has decided to change the HTTP redirect code used by our DOIs from 303 back to the more commonly used 302. Our implementation of 303 redirects back in 2010 was based on recommended best practice for supporting linked data identifiers. Unfortunately, very few other parties have adopted this practice.

What’s more, because using a 303 redirect is still unusual, it tends to throw SEO tools into a tizzy- and we spend a lot of time fielding SEO questions from our members about our use of 303s.

TL;DR

At this point, we need to emphasise that we have never seen our use of 303s actually affect page rankings. But at the same time, use of 303 redirects has not had wider uptake. Maintaining this quixotic behaviour just isn’t worth the effort. We hope that, in the future, we can use other techniques (e.g. signposting & cite-as) to achieve some of the things that 303 was supposed to do.

Note that these changes will not affect users or machines using DOIs. The change should be entirely transparent.

Below we provide some background to our decision and after that we provide some detailed technical notes from Jonathan Rees and Henry Thompson who have been very kind in helping to provide Crossref technical guidance on how we can help DOIs best support linked open data and adhere to HTTP best practice.

Background

Back in 2010, Crossref, DataCite (and later, several other RAs) responded to concerns that DOIs were not “linked-data friendly.” There were three problems with DOIs at that time:

It was not clear that DOIs could be used and expressed as HTTP URIs.
There was no standard way to ask a DOI to return a machine-readable representation of the data.
It wasn’t always clear if the DOI resolved to “the thing” (e.g. an article) or “something about the thing” (e.g. a landing page).

On the advice of several people in the linked data community, we proposed some options for fixing this. And we finally settled on:

Recommending that Crossref DOIs be expressed and displayed as HTTP (now HTTPS) URIs. This made it clear that DOIs could be used with HTTP applications.
Enabling DOI registration agencies to support content negotiation. This allowed RAs to support providing machine-readable representations of the data associated with a DOI.
Changing the underlying redirect code from the normal 302 to 303. This was designed to clarify what, at the time, was true- that most DOIs resolved to a landing page, not the article itself.

By any practical measure, machine use of DOIs has exploded since we made these decisions back in 2010. Crossref’s APIs and content negotiation handle over 800 million requests for machine readable data a month. Our sibling organisation, DataCite, has also seen a huge growth in machine use of DOIs. Many applications, from bibliographic management tools, to authoring systems and CRIS systems, make use of machine actionable DOIs all the time. So clearly our work to promote DOIs as machine actionable identifiers is working, but we are certain that our current use of 303 redirects has nothing to do with this growth.

First of all, as we said, very few parties have actually subscribed to the notion of using 303s to help distinguish “the thing” from “something about the thing”.

Secondly, even if they did try to rely on 303s to make this distinction, they would quickly get confused because the DOI is so often just the first in a chain of redirects which do not implement the same semantic distinction. At this point we should be clear - Crossref thinks these kinds of long redirect chains are a bad idea for two main reasons:

They slow down resolution.
They increase the number of potential failure points between the DOI and the item it resolves to.

But we also cannot legislate them away. They exist. And in the real world you will find plenty of DOIs that do a 303 redirect to a system that, in turn, does a 302 redirect to a system that does a 301 redirect and…eventually ends up someplace returning a 200. You get the picture. How on earth is a machine supposed to interpret a 303->302->301->302 redirect chain?

Furthermore - nowadays, after following this chain of redirects, you will often find yourself on a “page” that is both a landing page and the article itself. Dynamic, one-page applications can simply morph the one into the other without the use of additional HTTP requests.

In other words, using 303s is not helping machines interpret what the DOI is pointing at. And yet, people seem to be making good use of machine actionable DOIs and they are not complaining much about it.

Personally, I’d might have just been happy to switch back to using 302s simply so that I could cut down on my conversations with SEO hacks. But that wouldn’t be a principled approach. In 2010 we spent a lot of time considering the initial switch to 303s- we needed to consult with the LOD community on a potential switch back to 302s. At the January 2018 PIDapalooza I had a chance to talk to Henry Thomson about the 302/303 dilemma we faced, and he along with Jonathan Rees very generously provided the following feedback.

Best practices for HTTP redirection by persistent identifier resolvers: 302 vs. 303

Jonathan Rees (MIT CSAIL, https://orcid.org/0000-0001-7694-8250)
Henry Thompson (University of Edinburgh, School of Informatics, https://orcid.org/0000-0001-5490-1347)

If one goes to the trouble to organize an identifier system, then the desire that such a system should last as long as possible leads one to aspirationally say it’s a persistent identifier (PID) system. The unwillingness of the major browser suppliers to implement new URI schemes for PIDs initially hindered their use on the Web and this in turn inhibited widespread adoption. More recently a number of PID approaches have enjoyed very rapid growth as a result of a compromise: these PIDs participate in the World Wide Web by defining simple conversion rules mapping identifiers to actionable (‘http:’ and/or ‘https:’) forms and providing resolution servers that redirect requests for such forms to the appropriate destination.This approach has been widely adopted and is very successful, because it is so useful. An identifier’s actionable form leads, via the HTTP protocol and one or more redirections, to a web page that bears on the ground identity of the associated entity – or perhaps even directly to the entity itself, if the system is one for document entities that are naturally provided as web pages. The nature of the retrieved web page varies from one system to the next.

A confusion arose, however, over claims in various technical specifications (URIs, HTTP, Web Architecture) that the normal case is for the protocol to yield a “representation” of the “resource” “identified” by the URI. None of these terms is adequately defined by the specifications, and initially the language was not taken as normative. Those deploying identifier systems took the HTTP “resource” to be the entity associated with an identifier, and understood the “resource” as being “identified” by the URI, but it was never clear what was, or wasn’t, a “representation” of a given entity/resource: a description of the resource, the resource itself, a version of the resource, instructions on how to find the resource, etc. Sixteen years ago, in an attempt to clarify the intent of this part of the theory of URIs, and to allow applications to usefully and uniformly exploit the idea that an HTTP 200 response must deliver a “representation” of the “resource”, Tim Berners-Lee asked the W3C Technical Architecture Group to consider what came to be known as the httpRange-14 issue. It’s now 13 years after the TAG gave advice which almost no one was happy with, and 5 years after work on issue httpRedirections-57 (which superseded httpRange-14) ground to a halt. There’s still no consensus on whether it’s OK to return landing pages with a 200 status in response to requests for pictures or publications, but the Web seems to be working nonetheless, and no one seems to be bothered much anymore.

The provision of HTTP-based resolution services has stimulated widespread support for the use of identifier systems with Web resolution, particularly in the scholarly journal publication context. Those setting up HTTP resolvers responsible for identifier systems must decide which HTTP response code should be used. The TAG’s advice sows doubt on the use of the 200 response code when the response would have been a landing page, and many resolvers avoid 200 regardless and use redirection for administrative purposes, for example

‘https://dx.doi.org/10.1109/5.771073’ to

‘http://ieeexplore.ieee.org/document/771073/?reload=true’ for the DOI

‘10.1109/5.771073’, or ‘https://identifiers.org/uniprot/A0A022YWF9’ to

‘http://www.uniprot.org/uniprot/A0A022YWF9’ for the Uniprot identifier

‘A0A022YWF9’.

So the response should be a redirection, but what kind, 301, 302, or 303? (Or 307, which is almost the same as 302.) A 301 redirect seems to say that the URI is not persistent (since its target is deemed “more persistent”). A 302 redirect seems to say that the response could have come via a 200, and so suffers the same fate as 200. That leaves 303, as hinted at in the TAG’s advice. This idea got some traction: Ten years ago a Semantic Web interest group promoted the TAG’s advice in a published note, and seven years ago one of us wrote a blog post giving the same advice for resolvers for PIDs in publishing.

However, not only is there neither consensus nor general utility around this strict understanding of the use of the various response codes – that is, that resolution to a landing page is inconsistent with a 200 (and a posteriori therefore with a 302) – but also the range of usage patterns for redirection of HTTP requests has grown and ramified over time as the Web has grown and become more complex. It’s on the face of it unlikely that a mere three response codes can capture all the resulting complexity or cover the space of outcomes (in terms of e.g. what ends up in the browser address bar or what search engines index a page under) that a page owner might like to signal.

We find in practice that some PID redirections are ending up (usually after further publisher-local redirects) at the “identified” document, some at landing pages, and some at one or the other depending on the requesting site, for example in the case of paywalled material.

In the absence of a rethinking of the whole 3xx space, it seems to us that only the 301 vs. 302 distinct ion (roughly, 301 = permanent = please fix the link, and 302 = temporary = don’t change the link) is well understood and more or less consistently treated, whereas for 303, web servers are not very consistent and both search engine and citation crawler behaviours are at best inconsistent and at worst downright unhelpful.

So, we believe it is in both users’ and publishers’ interests for resolvers of actionable-form PIDs to use 302 redirects, not 303.

If we want to help machines better understand the resource that a DOI points at, we have to explore using more nuanced mechanisms.

Just using 302 for the first redirect doesn’t do everything necessary to effectively support the emerging PID+redirection architecture. It’s at the end of the redirect chains that we need more: a standardised way to find the PID back at the start of the chain. The ‘cite-as’ proposal does exactly this, and we hope it’s quickly approved and widely adopted. Once that happens a proposal for augmenting browser (and API) behaviour to prefer, or at least offer, the ‘cite-as’ link for bookmarking and copying will be needed.

Metadata and integrity: the unlikely bedfellows of scholarly research

Damian Pattinson — Thu, 14 Dec 2017 00:00:00 +0000

I was invited recently to present parliamentary evidence to the House of Commons Science and Technology Select Committee on the subject of Research Integrity. For those not familiar with the arcane workings of the British Parliamentary system, a Select Committee is essentially the place where governments, and government bodies, are held to account. So it was refreshing to be invited to a hearing that wasn’t about Brexit.

The interest of the British Parliament in the integrity of scientific research confirms just how far science’s ongoing “reproducibility crisis” has reached. The fact that a large proportion of the published literature cannot be reproduced is clearly problematic, and this call to action from MPs is very welcome. And why would the government not be interested? At stake is the process of how new knowledge is created, and how reliable that purported knowledge is.

The other issue driving this overview of research practices are the cases of deliberate fraud and wrongdoing that have recently created headlines (e.g., the STAP papers concerning the reprogramming of stem cells). While these cases are clearly dramatic outliers, they nevertheless serve to diminish public confidence in scholarly research and the findings that come out of this enterprise.

As with most inquiries, the question quickly boiled down to: who is to blame? As Bill Grant MP asked me directly, “Where does the responsibility lie?”

My answer was lifted from an article by Ginny Barbour and colleagues in F1000Research this November (https://doi.org/10.12688/f1000research.13060.1): publishers are responsible for the integrity of the published literature, while institutions and employers are ultimately responsible for the conduct of their staff. Misconduct entails intent, usually to deceive the reader into believing a conclusion that the researcher wishes them to believe. But journal editors can never know, and are not in a position to investigate, whether a researcher has deliberately falsified their data.

However, there are things that publishers can do to ensure high standards of integrity. Much of this involves making a study’s authors publish as much information about what they have done as possible - the more the reader can see of how data were generated, the more that reader can trust the findings communicated in the published article.

Article metadata directly supports this function. It provides structure and transparency to information pertaining to ethics and integrity. And because metadata is independent of the main article, it can be readable even if the article itself is locked behind a paywall.

Crossref already provides metadata that can demonstrate the integrity of published articles. The metadata collected on 91+ million scholarly works across publishers and disciplines is open and freely accessible to all. Bibliographic information, for example, allows readers to see who the authors of the article are, where they are from, and what else they have published. Similarly, funding data allows readers to identify potential conflicts of interest, for example if the funder has commercial or political affiliations. Even if the reader cannot see the conflict of interest statement (or if the journal has not provided one), they can use the funding statement to surface potential conflicts.

And if they wanted, publishers could provide additional metadata to add still more transparency to the research process. Ethical approval by institutional review boards, for example, could be captured, and any protocol numbers traced back to the original ethics committee approval. At present the process of ethical approval varies from country to country, and from institution to institution. Encouraging authors and journals to deposit information on the approval process would both demonstrate the high ethical standards the author is working to, and also improve the standards themselves, since institutions would have to encode their approval processes in a way that is understandable to others. This could pave the way to significantly higher international ethical standards, all through a simple addition to the indexed metadata underlying the scholarly literature.

One key recommendation that I and many others made to the Committee was, in short, “show your work”. As a researcher, that means showing your data. As a publisher, that means showing what checks you have done. In both cases, metadata can help.

A major issue that publishers and researchers can – and should – address is the provision of actual scientific data. Most papers, today, present only the end results of the authors’ (often quite extensive) analyses. The case for sharing data is an obvious one - many recent cases of misconduct could have been identified earlier, or even avoided altogether, if editors and readers had had access to underlying datasets.

With images, a requirement to submit raw images alongside the edited figures would dramatically reduce the cases of manipulation that are rife in the literature (studies suggest up to 20% of papers have some kind of inappropriate figure manipulation, with around 1 in 40 papers showing manipulation beyond that which can be expected to be a result of error). Similarly, providing the numbers that a paper’s analyses are based upon would allow readers to fully assess if datasets are distributed as would be expected through random sampling, and, if they choose, to determine if the data are sufficient to support the statistical inferences made in the paper. The Crossref schema – by providing unique identifiers to data citations - makes this link between data and paper possible. (See the recent blog post on the Research Nexus for more information.)

For publishers, showing your work also means being transparent to your readers about the editorial checks that a manuscript has undergone. Crossref has a tool that enables this editorial transparency: it’s called Crossmark. Crossmark allows readers to see the most up-to-date information about an article, even on downloaded PDFs. In most cases it is used to show whether the version of an article is most recent one, or whether any corrigenda or retractions have been subsequently added. But it can also be used to provide whatever information a publisher wishes to share about the paper. Some journals have experimented with using Crossmark to ‘thread’ publications together, for example, by linking all the outputs generated from a single clinical trial registration number (blog post here). But publishers could go further and display metadata pertaining to the editorial checks they have performed on a paper. So Crossmark could tell readers that the paper has been checked for plagiarism, or figure manipulation, or reporting standards such as CONSORT or ARRIVE guidelines. Here at Research Square we have been addressing this with a series of Badges that researchers can apply to their papers to demonstrate what checks have been performed.

Together, these implementations would provide value to the reader, who can see exactly what has been checked, and to the publisher, who can show how rigorous their editorial processes are. It would also serve to highlight the integrity of the authors who have passed all of these checks.

Research integrity is not something that can be easily measured but, unlike wit or charm, it is something that people generally know that they have.* This means that they just need to be transparent in their output to demonstrate this to the world. Metadata provides a simple way of doing this, so researchers and publishers should make sure they provide it as openly as they can.

*with apologies to Laurie Lee for the mangled quote

Changes to the 2018 membership agreement for better metadata distribution

Ginny Hendricks — Mon, 09 Oct 2017 00:00:00 +0000

We are making a change to section 9b of the standard Crossref membership agreement which will come into effect on January 1, 2018. This will not change how members register content, nor will it affect membership fees in any way. The new 2018 agreement is on our website, and the exact wording changes are highlighted below. The new membership agreement will automatically replace the previous version from January 1, 2018 and members will not need to sign a new agreement.

What’s changing?

At its July meeting the Crossref board unanimously approved recommendations from the Membership and Fees Committee to update Crossref’s metadata delivery offerings. One of the recommendations was to remove the option for case-by-case opt outs of metadata delivery through the OAI-PMH channel used for Enhanced Crossref Metadata Services.

This opt-out was only used by a small number of our members (around 40 of nearly 9,000), who have been contacted directly. This means that for the vast majority of members there is no change in how Crossref makes their metadata available but we wanted to make everyone aware of the change to the membership agreement.

So, as is currently the case, all metadata registered with Crossref is available via all the Metadata APIs under an appropriate agreement with the user or terms and conditions for the service. The one exception to this is how references are distributed - we will contact members next week about the options for references.

Why are we making this change?

Our metadata services have become very popular with users of all kinds throughout scholarly communications–including search and discovery platforms, libraries, other publishers, reference managers, sharing services, and analytics providers. More and better metadata means more and better discoverability of publisher content.
The change also brings this service into line with our mission to improve scholarly communications through quality metadata and related infrastructure services, removing the need for bilateral agreements between publishers and third parties.
Many members complained when we contacted them about opt-outs whenever a new OAI-PMH user came on board. It is better for our members and for our staff if there is a common standard across the board.

Changes to 2018 membership agreement

9) Sharing of Metadata by PILA

a) Local Hosting. [no change]

b) Other Metadata Services. Subject to compliance by the entity receiving the Metadata and Digital Identifiers with the terms and conditions ~~set forth in a separate agreement between~~ established by PILA for the particular service through which access is provided, and ~~the entity receiving the Metadata and Digital Identifiers~~, PILA may ~~license~~ authorize third parties to receive and use ~~bulk deliveries of~~ Metadata and Digital Identifiers from ~~the~~ PILA ~~System from members who have chosen to participate in Metadata Services,~~ which PILA shall provide directly to such third parties. At least thirty (30) days prior to making such Metadata delivery PILA will notify each PILA Member whose Metadata and Digital Identifiers are intended to be included in such delivery of the anticipated delivery date, the identity of the third party and the purpose for which the delivery is being made. Metadata and Digital Identifiers belonging to any PILA Member who notifies PILA in writing prior to the specified delivery date of its desire to be excluded from such delivery will be excluded or removed from such delivery.

Please contact our membership specialist if you have any feedback or questions.

Now put your hands up! (for a Similarity Check update)

Madeleine Watson — Tue, 06 Jun 2017 00:00:00 +0000

Today, I’m thinking back to 2008. A time when khaki and gladiator sandals dominated my wardrobe. The year when Obama was elected, and Madonna and Guy Ritchie parted ways. When we were given both the iPhone 3G and the Kindle, and when the effects of the global financial crisis lead us to come to terms with the notion of a ‘staycation’. In 2008 we met both Wall-E and Benjamin Button, were enthralled by the Beijing Olympics, and became addicted to Breaking Bad. And lest we forget, 2008 was also the year in which Beyoncé brought us Single Ladies; in all its sassy hand-waving, monochrome glory. For Crossref though, 2008 holds another important milestone as it was the year we launched our Similarity Check initiative. Today, the artist formerly known as CrossCheck provides our members with cost-effective access to Turnitin’s powerful text comparison tool, iThenticate.

Fast forward nearly a decade, and it’s wonderful to see just how Similarity Check membership has grown in the nine years since launch; from 16 original members in 2008 to over 1,300 today.

Figure 1.1 The number of publishers participating in the Similarity Check service each year between 2008 – 2017 (to April)

Usage of iThenticate is also consistent with this growth in membership, and throughout 2016 our members checked over four million manuscripts for similarity using the tool. As Similarity Check members contribute their full-text content into Turnitin’s database, this increase in membership also has a dramatic impact on the volume of content indexed by Turnitin. Today, members can compare their manuscripts against Turnitin’s database of over 60 million full-text works provided by Similarity Check members. With over 88 million works currently registered with Crossref, this means that 68% of all content deposited with us is now available for comparison in iThenticate.

Over the years we have worked very closely with Turnitin to help champion new iThenticate feature developments that best support our member’s use of the tool as a core function of their editorial workflow. Many of our members too have also worked together with Turnitin to provide feedback on user experience and design.

Below, Turnitin’s Product Manager for iThenticate, Sun Oh, shares an insight into their research process and how Similarity Check member’s feedback has been critical in developing new and improved functionality in iThenticate.

Read on to learn more from Sun…

Sun Oh is a Senior Product Manager at Turnitin. She is currently the Product Manager for iThenticate and backend systems including the Content Intake System and similarity reports.

Last year we surveyed our Crossref customers to find out what Similarity Check improvements they would like to see and noticed a recurring request for the ability to compare two or more personally sourced documents.

We were intrigued and decided to run with it. We contacted the respondents who had asked for this, and started conversations to find out more. This helped us gather invaluable data, which in turn helped us to build the feature based on real use cases and with a clear view of what was wanted.

The design prototypes were reviewed for usability and effectiveness each step of the way by the respondents and once we had the feature up and running, those who requested it in our initial survey were among the first to trial it.

We’re thrilled to announce that we’ve now launched the new Doc-to-Doc comparison feature, available through iThenticate’s native interface. Simply select the Doc-to-Doc comparison upload method from the document submission panel.

If you are a Crossref member using Similarity Check, you have exclusive early access to this new feature, which allows you to use iThenticate’s powerful similarity check functionality and apply it to your own, private documents.

How does Doc-to-Doc Comparison work?

Doc-to-Doc comparison allows users to upload one primary document and compare it against up to five other documents.

Figure 1.2 The document upload screen for Doc-to-Doc comparison

When the upload is complete, a similarity score is generated for the primary document based on the amount of similar content found in the comparison documents. A full comparison report is also available.

The comparison report will open in the document viewer, and will display the primary document along with a list of the comparison documents and with their similarity percentage. If one of the comparison documents doesn’t include text that matches the primary document, iThenticate will still display it anyway, with a 0% score, allowing users to rule it out of their inspection. The similarity report will be stored securely in the user’s folder until they delete it.

Figure 1.3 Similarity report for Doc-to-Doc comparison

As these documents will not be stored in a shared database, they won’t affect the similarity score of any future submissions. Primary and comparison documents remain completely private and will not be indexed into the shared iThenticate content database.

To get a better idea of how Doc-to-Doc comparison works, check out the iThenticate feature guide on the Turnitin website.

Start using Doc-to-Doc Comparison now!

If you’re a Crossref member using Similarity Check, you can log in to your iThenticate account now and select the Doc-to-Doc comparison link on the homepage.

What else is new in iThenticate in this new release?

New Look

In addition to Doc-to-Doc comparison, we decided to refresh the look and feel of iThenticate; the same tools our users know and trust, now with a modern interface. Users will also notice that iThenticate now has more readable font and friendlier styling throughout.

Report Mode Memory

To make life easier, iThenticate now remembers whether users were in the All Sources or Match Overview mode when they last used the Document Viewer. iThenticate will then open documents in this mode automatically hereafter.

Improved Submission Process

We’re also enhancing our submission process by making the upload requirements more inclusive. We’ve increased the possible file size limit from 40MB to 100MB when uploading to either the database or to Doc-to-Doc comparison, and PowerPoint (.ppt) and Excel (.xlsm) file formats are now accepted.

Developments completed in 2016

If Similarity Check members haven’t had a chance to check out the improvements we introduced in iThenticate throughout 2016, here’s a quick recap. You can always find our updates on the What’s New page of the iThenticate website.

Download User List

The ability for administrators to download a list of all the users in their account has been added. This list will allow administrators to easily send emails to users.

Similarity Score Calculation Update

We updated how the similarity score is calculated when bibliographic material is excluded from a similarity report. Now, when bibliography exclusion is enabled, the word count of the bibliography is not included when calculating the overall percentage. This update to the similarity report calculation helps to provide users with a more accurate similarity score.

Improved Security

We are fully committed to keeping user’s data safe and secure at all times. To that end, we’ve added additional security logging, put in measures to enforce stronger passwords, and enabled Captcha after failed login attempts.

Faster Report Generation

We’ve increased the number of resources dedicated to the generation of similarity reports for our iThenticate service. As a result, users should see faster turnaround times for similarity reports.

Support for Eight Additional Languages

The iThenticate user interface is now available in eight additional languages: German, Dutch, Latin American Spanish, Brazilian Portuguese, Italian, French, and both Simplified & Traditional Chinese. When adding new users to an account, administrators can specify the language of the new user, which will then send a welcome email in the selected language. Individual users can also set their preferred language by selecting a language from the Language dropdown in the Settings menu.

Content Intake System

We’ve developed a new Content Intake System which enables our publication content database to scale so that our users can compare against a constantly growing database of the most recently published content. This allows us to index Similarity Check members’ data in a much more reliable and efficient way than legacy intake methods. And recently, we’ve made the collecting and processing of content from Crossref members using Similarity Check even faster by parallelising our processors. This means that we have more processors running simultaneously to process data.

By removing the need for crawling, we will also minimize our impact on traffic to a Similarity Check member’s public-facing website. The Content Intake System is able to directly collect full text URLs from members DOI metadata. This results in a huge reduction in the time it takes from when a publisher first deposits a new DOI with Crossref, to when the content is indexed by us into our full-text publication database. To date, we’ve been able to index the content associated with 60 million Crossref DOIs, and have indexed more than 165 million published works in total which submissions are compared against in iThenticate.

Walker (web crawler)

We’ve developed a new web crawler. Referred to as “Walker”, the crawler makes it possible to provide quicker and more reliable similarity matches to content available on the web. Not to be confused with the Content Intake System mentioned above, Walker’s purpose is to crawl the public web and is not used for indexing full-text content from Similarity Check members.

Using Walker, we’re adding an average of nearly 10 million new web pages to our content database per day, ensuring we have the freshest internet content available to find matches against.

We’d love to get your feedback!

As we design and develop new features, we want to make sure we’re fully understanding Similarity Check member’s needs and would love the opportunity to engage with users for further research. If you’d like to sign up to participate in user research for upcoming feature developments, please take a few minutes to fill out our Feedback Program Form. We look forward to connecting with you!

Contact Turnitin (EDIT 30/04/24: Support for iThenticate, contact details updated )

Please go to our Get help with Similarity Check page

~~For iThenticate technical and billing support, please email tiisupport@turnitin.com~~

~~For questions about content indexing, please contact Gareth at gmalcolm@turnitin.com~~

~~For iThenticate product development questions, please contact Sun at soh@turnitin.com~~

* Sun Oh, Product Manager for iThenticate*

**Thanks to Sun and the whole team at Turnitin for sharing this update.**

For more information about Similarity Check, visit our service page.

Want to join Crossref Similarity Check? Please contact our membership specialist.

Included, registered, available: let the preprint linking commence.

Rachael Lammey — Mon, 05 Dec 2016 00:00:00 +0000

We began accepting preprints as a new record type last month (in a category known as “posted content” in our XML schema). Over 1,000 records have already been registered in the first few weeks since we launched the service.

By extending our existing services to preprints, we want to help make sure that:

links to these publications persist over time
they are connected to the full history of the shared research
the citation record is clear and up-to-date.

It’s not just collecting the metadata however, it’s also making it available so that it can be as widely used as possible. Preprint metadata is no different. As with all record types, we make the metadata available for machine and human access, across multiple interfaces (e.g. REST API, OAI-PMH, Crossref Metadata Search)

For example, you can see information on the preprint https://doi.org/10.20944/preprints201608.0191.v1 in a number of ways:

If you want to see all the preprint metadata deposited so far, try https://api.crossref.org/v1/types/posted-content/works. Over 1,000 records have already been registered in the first few weeks since we launched the service.

Crossref members depositing preprints need to make sure they:

Register content using the posted content metadata schema.
Respond to our match notifications that a manuscript / version of record (AM/VOR) has been registered and link to that within seven days.
Label the manuscript as a preprint clearly, above the scroll on the preprint landing page, and ensure that any link to the AM/VOR is also prominently displayed above the scroll.

It’s important to clearly label the record type so we can ensure that the connections between preprints and the associated literature are clearly visible, to both humans and machines.

As with other record types, there is a registration fee to include content in the Crossref system. For preprints, it’s $0.25 fee for current preprint files and $0.15 for back-year records.

Are you an existing Crossref member who wants to assign preprint DOIs? Let’s talk about getting started or migrating any existing content over to the dedicated preprint deposit schema.

Interested in becoming a Crossref member to assign DOIs to your preprints? Contact our membership specialist so we can answer any questions and get you set up as a member.

Important changes to Similarity Check

Madeleine Watson — Fri, 21 Oct 2016 00:00:00 +0000

New features, new indexing, new name - oh my!

TL;DR The indexing of Similarity Check users’ content into the shared full-text database is about to get a lot faster. Now we need members assistance in helping Turnitin (the company who own and operate the iThenticate plagiarism checking tool) to transition to a new method of indexing content.

For existing Similarity Check users: please check that your metadata includes full-text URLs so that Turnitin can quickly and easily locate and index your content. Full-text URLs need to be included in 90% of journal article metadata by 31st December 2016.

2016 has seen some exciting new developments

(And there are plenty more in store as we strive towards 2017). But first: in April we renamed the service from CrossCheck to Similarity Check and we now have a new service logo available to reference via our logo CDN using the following code.

<img src="https://assets.crossref.org/logo/crossref-similarity-check-logo-200.svg" width="200" height="98" alt="Crossref Similarity Check logo">

Earlier this year Crossref also signed a new contract with Turnitin. As part of this, we negotiated the inclusion of dedicated development time each year from Turnitin’s engineering and product teams to focus on developments in the iThenticate tool that will specifically support Similarity Check users and their needs. Many of our members will have been contacted recently by Turnitin and asked to complete a survey regarding how they use the tool and what improvements they would like to see made in the future. The results of this survey are currently being analyzed and will be used by Turnitin to inform a development plan.

Finally, throughout 2016 we have also been working with Turnitin to help them develop a new Content Intake System that provides a faster, more reliable and robust method for collecting data from Crossref and indexing users’ content into the Similarity Check full-text database. Previously Turnitin was only able to collect prefix data from Crossref’s system on a monthly basis whereas today, with the new Content Intake System up and running, they are able to pull full-text content links from deposited metadata on a daily basis. This means that if you are a Similarity Check user currently depositing full-text URLs with Crossref, your content is being indexed by Turnitin faster than ever before.

There are plenty of other benefits this new method provides. This is why we have agreed with Turnitin that from 1st January 2017 onwards, indexing via full-text URLs will be the only method supported for Similarity Check.

Not convinced? Let me share my top four reasons for advocating Turnitin’s exclusive use of the full-text URL indexing method for Similarity Check:

1. Reduced traffic to publisher servers. Indexing via full-text URLs means that the crawl is targeted specifically to the location of the full-text PDF or HTML content, thereby reducing the amount of traffic Turnitin puts through publisher’s servers.

2. Lower margin for error and simplified issue recovery. Turnitin will no longer need to make multiple fetches for any content item, meaning there are now fewer steps in the process. This means there will be fewer places for indexing errors to occur and also reduces the reliance on users setting meta tags or span tags correctly in their markup. Furthermore, if problems do arise, using the one method of indexing for all users will mean that Turnitin is able to pinpoint the issue faster and work with members to resolve it quickly.

3. Quicker turnaround on indexing with fewer delays. Turnitin will no longer need to investigate and set up bespoke indexing methods for different Similarity Check users and they will be able to access the location of full-text content from the one place (ie. within the specific resource tag in member’s metadata deposits). More accurate data from only one location will result in a quicker turnaround on indexing, meaning newly published content will be added into the Similarity Check content database sooner for all members to check other new manuscripts against.

4. Daily ingest is better than monthly! Full-text links can be collected daily from Crossref-rather than monthly for other methods-meaning a more regular ingest of content.

The presence of full-text URLs within the metadata is critical to the functioning of Turnitin’s new indexing system. All new Similarly Check participants are now asked to ensure they have these links in place within their deposited metadata before they participate in the service.

Already a user of Similarity Check?

If you’re an existing Similarity Check participant who joined the service before 2016, your content is likely to be currently indexed via different methods, such as following links contained in your page meta tags. If you’re not currently depositing full-text links with Crossref for Similarity Check, you will have received an email from us about this in August. If you’re unsure though, you can check your XML to see if you have included the full-text link in the field or you can send us an email at similaritycheck@crossref.org as we’d be happy to check for you.

Help, don’t leave me behind!

Us? Never! We’re here to help. But we really do need those full-text links… Everything existing Similarity Check publishers need to know about adding full-text links into new or existing metadata can be found on our help site. These URLs should be included as part of all standard metadata deposits going forward and can be easily added into existing files in bulk. So there’s no need to redeposit the full metadata, unless of course you would prefer to do so!

That’s a wrap

Looking back, it really has been a busy year for Similarity Check and it will continue to be so as we persevere in laying the groundwork for a more streamlined, robust and scalable service for 2017 and beyond. Remember, we need Similarity Check users to ensure they have full-text URLs in at least 90% of their journal article metadata by 31st December 2016 in order to continue using Similarity Check from 2017 onwards.

And please keep us updated! With over 1,200 publishers using Similarity Check, we’ll need a little nudge to know when metadata has been updated to include these links. So once updates have been deposited, please email similaritycheck@crossref.org to confirm. And of course, as always, if there are any questions or if some advice would help, we’re just an email away.

The article nexus: linking publications to associated research outputs

Jennifer Lin — Thu, 25 Aug 2016 00:00:00 +0000

Crossref began its service by linking publications to other publications via references. Today, this extends to relationships with associated entities. People (authors, reviewers, editors, other collaborators), funders, and research affiliations are important players in this story. Other metadata also figure prominently in it as well: references, licenses and access indicators, publication history (updates, revisions, corrections, retractions, publication dates), clinical trial and study information, etc. The list goes on.

What is lesser known (and utilized) is that Crossref is increasingly linking publications to associated scholarly artifacts. At the bottom of it all, these links can help researchers better understand, reproduce, and build off of the results in the paper. But associated research objects can enormously bolster the research enterprise in many ways (e.g., discovery, reporting, evaluation, etc.).

With all the relationships declared across all 80+ million Crossref metadata records, Crossref creates a global metadata graph across subject areas and disciplines that can be used by all.

Research article nexus

As research increasingly goes digital, more research artifacts associated with the formal publication are stored or shared online. We see a plethora of materials closely connected to publications, including: versions, peer reviews, datasets generated or analysed in the research, software packages used in the analysis, protocols and related materials, preprints, conference posters, language translations, comments, etc. Occasionally, these resources are linked from the publication. But very rarely are these relationships made available beyond the publisher platform.

Crossref will make these relationships available to the broader research ecosystem. When publishers register content for a publication, they can identify the associated scholarly artifacts directly in the article metadata. Doing so not only groups digital objects together, but formally associates with the publication. Each link is a relationship and the sum of all these relationships constitutes a “research article nexus.”

An assortment of connections already abound in the wild today. Examples include:

F1000Research article http://doi.org/10.12688/f1000research.2-198.v3 connected to initial version http://doi.org/10.12688/f1000research.2-198.v1

OECD publication http://dx.doi.org/10.1787/empl_outlook-2014-en and its German translation http://dx.doi.org/10.1787/empl_outlook-2014-de

PeerJ article http://doi.org/10.7717/peerj.1135 and its peer review http://doi.org/10.7287/peerj.1135v0.1/reviews/3

eLife article http://doi.org/10.7554/eLife.09771 and its BioArXiv preprint http://doi.org/10.1101/018317

PLOS ONE article http://doi.org/10.1371/journal.pone.0161541 with underlying data in Dryad http://doi.org/10.5061/dryad.d2vf8

Frontiers article http://doi.org/10.3389/fevo.2015.00015 with a figshare http://doi.org/10.6084/m9.figshare.1305089.v1 video

Journal of Chemical Theory and Computation article http://doi.org/10.1021/ct400399x with software archived in Zenodo http://doi.org/10.5281/zenodo.60678

Nature Biotech article http://doi.org/10.1038/nbt.3481 with a Protocols.io protocol http://doi.org/10.17504/protocols.io.dm649d

To date, almost all these relationships are not directly recorded in the article metadata (great job, PeerJ!). And as a result, they are more than likely “invisible” to the broader scholarly research ecosystem. Publishers can remedy these gaps by depositing associations when registering content with Crossref or updating the records after registration. That is how the article nexus is formed.

(Associated datasets can also be identified in the reference list as per Joint Declaration of Data Citation Principles as with the FORCE11 Software Citation Principles. Stay tuned next week for a follow up blog post on Crossref’s support for publisher data and software citations through its metadata.)

Forming the nexus

The mechanism of declaring these relationships is straightforward and a longstanding part of the standard deposit process. For each associated research object, simply provide the identifier and identifier type for the object, an optional description of it, as well as name the relationship into the metadata record. For the latter, Crossref and DataCite share a closed list of relationship types, which ensures interoperability between mappings. See Crossref technical documentation for more details.

We maintain a list of the recommended relation types for a host of associated research objects to promote standardization across publishers. If you have relationships not specified, please contact us at feedback@crossref.org to identify a suitable one considered best practice. Common adoption of relation types will make relationship metadata useful to tool builders and systems. For example, programmatic queries on supporting materials require proper tagging of their respective relationship types.

This approach is highly extensible and accommodates the introduction of new research object forms as they emerge. It also supports associated research objects regardless of identifier type. When an associated entity has a DOI, however, we can validate the relationship during metadata processing as well as provide a more reliable representation of the article nexus.

Article nexus: a far richer scholarly map

Bibliographic metadata is like a ship’s manifest that catalogs each item of cargo in a ship’s hold - crate, drum, sack, and barrel. It identifies the components that have an internal relation to the publication (contributor, funder, article update, license, etc.), each of which are well-understood points on the scholarly map. But when we integrate the article nexus into the graph, new territories become visible - not isolated islands, but places with highways connecting them to addresses already known.

When a publication has its relationships clearly identified, the connections both go out as well as lead back to it. The more connections, the more visibility on the scholarly map, as the Art of Cartography goes. Numerous systems tap into this map: publishing, funders, research institutions, research councils, indexers & repositories, indexers, research information systems, lab & diagnostics systems, reference management and literature discovery, other PID suppliers. So publishers, you can provide the fullest value to your own publishing operation, your authors, their research communities, and the overall research enterprise by ensuring that all publications are fully linked both inside and out.

Get ready for Crossmark 2.0!

Kirsty Meddings — Wed, 17 Aug 2016 00:00:00 +0000

TL;DR… In a few weeks, publishers can upgrade to the new and improved Crossmark 2.0 including a mobile-friendly pop-up box and new button. We will provide a new snippet of code for your landing pages, and we’ll support version v1.5 until March 2017.

We recently revealed a new look for the Crossmark box, bringing it up-to-date in design and offering extra space for more metadata. The new box pulls all of a publication’s Crossmark metadata into the same space, so readers no longer have to click between tabs. Linked Clinical Trials and author names (including ORCID iDs) now have their own sections alongside funding information and licenses. Feedback so far tells us that the new box is a vast improvement.

However, this was only phase one of the Crossmark makeover. We will soon complete the upgrade to display a fully responsive, mobile-friendly box. The Crossmark button has been given a facelift too, and we are excited to offer the first public preview today:

The new button brings the Crossmark icon up to date and is designed to be more “clickable” than the current button. It will be available in several different ratios and also in greyscale.

The first phase of the new design was rolled out in the existing Crossmark pop up window (Crossmark v1.5) without the need for changes within publisher systems. For the Crossmark v2.0 upgrade, publishers will need to update their landing pages with a new snippet of code, to ‘unlock’ the new button and functional enhancements.

Crossmark 2.0 will be available to adopt in a few weeks, and each publisher can decide when to switch over. We encourage members to upgrade sooner rather than later to get the benefits of the new box, but we also understand there are planned development schedules and the need for a testing period so we will continue to support Crossmark v1.5 until March 2017.

Many thanks to all of those who completed our surveys to help us shape the new button. And congratulations to Elizabeth Ramsey, a researcher from Trent University in Canada, who will be receiving a limited edition Crossref Moleskine notebook from the survey prize draw.

Our User Experience Designer, Rakesh Masih, will be blogging soon with details about the research and testing for this project, as well as more about our new approach to user experience at Crossref.

A fairer approach to waiting for deposits

Chuck Koscher — Wed, 20 Jul 2016 00:00:00 +0000

If you ever see me in the checkout line at some store do not ever get in the line I’m in. It is always the absolute slowest.

Crossref’s metadata system has a sort of checkout line, when members send in their data they got processed essentially in a first come first served basis. It’s called the deposit queue. We had controls to prevent anyone from monopolizing the queue and ways to jump forward in the queue but our primary goal was to give everyone a fair shot at getting processed as soon as possible. With many different behaviors by our members this could often be a challenge and at times some folks were not 100% happy.

We recently made a change where the queue now cycles through all waiting users and selects a job from each. This means that low-frequency users will always get a pretty fast service even if there are a lot of unique users waiting. Everyone gets one bite of the apple on each cycle through the waiting list. Of course, we still have some special controls to help deal with large quantities of files from a single user and ways to jump the queue under really special circumstances.

We believe this will, on average, yield a better experience and minimize the backups that formerly required administrator attention to resolve.

Outreach Day DC. Next Up? You Tell Us

Jennifer Kemp — Tue, 28 Jun 2016 00:00:00 +0000

Rallying the community is a key Crossref role. Sometimes this means collaborating on new initiatives but it is also an ongoing process, a cornerstone of our outreach efforts. Part of rallying the community is bringing people together, literally, in a series of outreach days around the globe. It means we encourage dialog with us and among members and non-publisher affiliates. We want to hear from the community and we hope to facilitate conversations in it. Not just about Crossref, but larger issues of scholarly communications and your particular part in it. The Crossref outreach team is doing a number of events around the world to bring together the community for updates, feedback and discussion.

On 16 June, Crossref hosted an all day session in Washington, DC where we were joined by about 35 attendees from the region, mostly publishers. The size of the group made for lots of discussion, and we are grateful for the feedback. Here is what we took away from the event:

We all need a better understanding of who is using Crossref metadata and how

Sure, we all know that, for example, submission systems, libraries and hosting platforms use Crossref metadata (‘metadata out’), but pinpointing where in workflows (often multiple instances) and the interplay between publishers and these systems? Not so much. Help us change that: take this short survey to tell us how publisher metadata quality affects your systems and workflows and we will, in turn, make use cases (anonymized if you wish) available as part of an ongoing effort to promote the value of more, better and enriched metadata.

Here I must say a big thank you to our guest speaker for the day, Carly Robinson, who provided an excellent presentation on the work of OSTI, of the U.S. Department of Energy. Carly shared examples of how OSTI uses the Crossref metadata in their systems to aid compliance and compliment the DOE public access model. A live use case is a welcome way to partner with our community!

The more things change, the more they emphasize core best practices

A good part of the day was spent on new initiatives such as: DOIs for preprints, auto-update of ORCID records, ‘early content registration’ , linked clinical trials and more. All good stuff-the industry evolves and workflows must keep pace-but none of which generated a great deal of questions or expressed concern.

One session that did spur a lot of discussion was a simple overview of where Crossref services sit in the publishing process (including pre- and post-). Perhaps this is because it was early in the day but the much-appreciated discussion underscored the need to make the case for enriched metadata in a well-understood workflow that reflects the roles of publishers and affiliate users of metadata.

Outreach is an experiment in which we are all subjects

Finally, it must be noted here that we actively seek feedback on our Community Outreach days! We are not a large team and we can’t do as many outreach days as we’d like, but we are very open to hearing from you: So, tell us in this quick survey: what should we discuss? And where should we head next?

Linked Clinical Trials initiative gathers momentum

Kirsty Meddings — Tue, 21 Jun 2016 00:00:00 +0000

We now have linked clinical trials deposits coming in from five publishers: BioMedCentral, BMJ, Elsevier, National Institute for Health Research and PLOS. It’s still a relatively small pool of metadata - around 4000 DOIs with associated clinical trial numbers - but we’re delighted to see that “threads” of publications are already starting to form.

If you look at this article in The Lancet and click on the Crossmark button you will see that in the Clinical Trials section there are links to three other articles reporting on the same trial: two from the American Heart Journal and one from BMJ’s Heart. Readers can navigate between these four articles in three separate journals using the Crossmark functionality- a new set of links and routes for discovery have appeared.

In another example, three articles from PLOS ONE are threaded together around a trial for the treatment of Type 1 diabetes. And here another PLOS journal, Neglected Tropical Diseases links through to a PLOS ONE article about the same trial.

If you publish in the health sciences please do consider joining this exciting initiative so that we can expand these threads and build up the metadata. Read the tech specs here or drop me an email if you have questions.

Distributing references via Crossref

Geoffrey Bilder — Fri, 17 Jun 2016 00:00:00 +0000

Known unknowns

If you follow this blog, you are going to notice a theme over the coming months- Crossref supports the deposit and distribution of a lot more kinds of metadata than people usually realise.

We are in the process of completely revamping our web site, help documentation, and marketing to better promote our metadata distribution capabilities, but in the mean time we think it would be useful highlight one of our most under-promoted functions- the ability to distribute references via Crossref.

One of the questions we most often get from members is- “can we distribute references via Crossref?” The answer is an emphatic yes. But to do so, you have to take an extra and hitherto obscure step to enable reference distribution. [EDIT 6th June 2022 - all references are now open by default with the March 2022 board vote to remove any restrictions on reference distribution].

How?

Many members deposit references to Crossref as part of their participation in Crossref’s Cited-by service. However - for historical reasons too tedious to go into - participation in Cited-by does not automatically make references available via Crossref’s standard APIs. In order for publishers to distribute references along with standard bibliographic metadata, publishers need to either:

Contact Crossref support and ask them to turn on reference distribution for all of the prefixes they manage.
Set the reference_distribution_opt element to any for each content item registered where they want to make references openly available.

Either of these steps will allow references for the affected member DOIs to be distributed without restriction through all of Crossrefs APIs and bulk metadata dumps.

Note that by doing this, you are not enabling the open querying of your Cited-by data- you are simply allowing the references that you already deposit to be redistributed to interested parties via our public APIs.

Who?

So who does this now? Well, at the moment not many members have enabled this feature. How could they? They probably didn’t know it existed. At the time of writing this 29 publishers have enabled reference distribution for at least some of their DOIs.

But that’s why we are writing this post. Given the interest expressed by our members, we expect the list to start growing quickly over the next few months. Particularly now that they know they can do it and have clear instructions on how to do it. 🙂

If you are of a geeky persuasion and want to see the list of publishers who are doing this, you can check via our API.

The following query will just show you the total number of members who are distributing references for at least some of their DOIs.

https://api.crossref.org/v1/members?filter=has-public-references:true&rows=0

And this query will allow you to page through the member records and see who is distributing references.

https://api.crossref.org/v1/members?filter=has-public-references:true

That cool, but can you see how many total DOIs have reference distribution enabled? No, but will will be adding that capability to our API soon.

OMG! OMG! OMG! Does this mean I can get references from api.crossref.org?

Yep. But before you get too excited- note above that not many of our members are doing this yet and that our API is still being updated to allow you to better query this information. At the moment references are not included in our JSON representation- they are only included in our XML representation. You can get the XML for a Crossref DOI either through content negotiation, or by using the following incantation on our API (using an eLife DOI as an example):

~~https://api.crossref.org/v1/works/10.7554/eLife.10288.xml~~

~~As we update our API to better support querying DOIs that include references, you will see the new functionality reflected in our documentation at:~~

Yes. 🤗. See the API docs below.

https://api.crossref.org

Beyond the DOI to richer metadata

April Ondis — Wed, 15 Jun 2016 00:00:00 +0000

The act of registering a DOI (Digital Object Identifier) for scholarly content is sometimes conflated with the notion of conferring a seal of approval or other mark of good quality upon an item of content. This is a fundamental misunderstanding.

A DOI is a tool, not a badge of honor.

The presence of a Crossref DOI on content sends a signal that:

The owner of the content would like to be formally cited if the content is used in a scholarly context.
The owner of the content considers that it is worthy of being made persistent.

Beyond the DOI

For Crossref, a DOI is just one of several types of metadata we register, albeit an important one.

Metadata about scholarly works extends beyond the DOI. In addition to bibliographic details, layers of information accompanying published works may now extend to data that describes the research, such as the source of research funding. It may also include non-descriptive information that facilitates usage, such as copyright and access permissions.

In fact, this “richer” metadata can tell you more about the context of the content deposited for a published work than you might realize.

For example:

Author data - Crossref metadata may include information specifying the author’s unique ORCID, allowing you to find other works by the same person.

Copyright and access indicators - You can view the license terms under which the full content may be available, which is very helpful for scholars who want to access the full content for research and teaching or for text and data mining.

Funding data - Metadata may also include the identity of the grant-making institution that funded the research, so that the funder and, in the case of publicly funded research, the general public and other researchers, have visibility on the resulting research outputs.

Clinical Trials data - Similarly, when research involves a clinical trial, (testing of medicines and treatments on human beings), Crossref metadata can enhance output visibility by displaying the clinical trial number and the related clinical trial registry.

Like the full content they describe, these metadata have become research resources in their own right. Unfortunately, too much metadata is entered into Crossref with missing, incomplete, or duplicated fields. This “bad” metadata slows the pace of discovery, confounding attempts to find and understand scholarly content and its context.

As a community, we really need to do something about that.

“The Map is not the Territory”

And the metadata is not the content. In Metadata (MIT Press), Jeffrey Pomerantz quotes Alfred Korzybski’s insight that a map is a simplified representation of a territory, a tool of abstraction that allows us to find our way. Jennifer Lin contributed the concept of the scholarly road map as a useful metaphor for the way we use metadata about scholarly works to find our way between and among them in the digital world.

Metadata deposited with Crossref amounts to pieces of information-structured, descriptive, administrative, contextual-about published works that humans can read and machines can use to automate linking and retrieval. The systematic development of such metadata allows us to make sense of such complex information by finding, linking, citing, and assessing scholarly content.

If you want to understand how Crossref acts as a map of scholarly metadata, try searching for content on search.crossref.org (our human API interface). Or simply talk with us @CrossrefOrg and via member@crossref.org.

Getting Started with Crossref DOIs, courtesy of Scholastica

Anna Tolwinska — Mon, 25 Apr 2016 00:00:00 +0000

I had a great chat with Danielle Padula of Scholastica, a journals platform with an integrated peer-review process that was founded in 2011. We talked about how journals get started with Crossref, and she turned our conversation into a blog post that describes the steps to begin registering content and depositing metadata with us. Since the result is a really useful description of our new member on-boarding process, I want to share it with you here as well. As always, comments and questions are welcome here, at member@Crossref.org, and @CrossrefOrg. - Anna_

The internet is in a constant state of change, with new content being added to the web by the minute and old content sometimes getting moved around. While the benefit of publishing scholarly outputs online is that it’s possible to update them at any moment, moving or modifying content can also …

Python and Ruby Libraries for accessing the Crossref API

Scott Chamberlain — Fri, 04 Mar 2016 00:00:00 +0000

I’m a co-founder with rOpenSci, a non-profit that focuses on making software to facilitate reproducible and open science. Back in 2013 we started to make an R client working with various Crossref web services. I was lucky enough to attend last year’s Crossref annual meeting in Boston, and gave one talk on details of the programmatic clients, and another higher level talk on text mining and use of metadata for research.

Crossref has a newish API encompassing works, journals, members, funders and more (check out the API docs), as well as a few other services. Essential to making the Crossref APIs easily accessible—and facilitating easy tool/app creation and exploration—are programmatic clients for popular languages. I’ve maintained an R client for a while now, and have been working on Python and Ruby clients for the past four months or so.

The R client falls squarely into the analytics/research use cases, while the Python and Ruby clients are ideal for general data access and use in web applications (the Javascript library below as well).

I’ve strived to make each client in idiomatic fashion according to the language. Due to this fact, there is not generally correspondence between the different clients with respect to data outputs. However, I’ve tried to make method names similar across Ruby and Python; although the R client is quite a bit older, so method names differ from the other clients and I’m resistant to changing them so as not to break current users’ projects. In addition, R users are likely to want a data.frame (i.e., table) of results, so we give back that - whereas with Python and Ruby we give back dictionaries and hashes, respectively.

Crossref clients

Python:
- Source: https://github.com/sckott/habanero
- Pypi: https://pypi.python.org/pypi/habanero
Ruby:
- Source: https://github.com/sckott/serrano
- Rubygems: https://rubygems.org/gems/serrano
- serrano also comes with a command line tool of the same name that’s installed when you install serrano (examples below)
R:
- Source: https://github.com/ropensci/rcrossref
- CRAN: https://cran.rstudio.com/web/packages/rcrossref/
Javascript:
- Source: https://github.com/scienceai/crossref
- NPM: https://www.npmjs.com/package/crossref

I’ll cover the Python, Ruby, and R libraries below.

Installation

Python

on the command line

pip install habanero

Ruby

on the command line

gem install serrano

in an R session

install.packages("rcrossref")

Examples

Output is indicated by the syntax #> in all examples below.

Python

in a Python REPL (e.g. iPython)

Import the Crossref module from within habanero, and initialize a client

from habanero import Crossref
cr = Crossref()

Query for the phrase “ecology”

x = cr.works(query = "ecology", limit = 5)

Index to various parts of the output

x['message']['total-results']
#> 276188

Extract similar data items from each result. The records are in the “items” slot

[ z['DOI'] for z in x['message']['items'] ]
#> [u'10.1002/(issn)1939-9170',
#> u'10.4996/fireecology',
#> u'10.5402/ecology',
#> u'10.1155/8641',
#> u'10.1111/(issn)1439-0485']

In habanero for some methods we require you to instantiate a client.

You can set a base URL and API key. This is a future looking feature

as Crossref API does not require an API key.

Note: I’ve tried to make sure habanero is Python 2 and 3 compatible. Hopefully you’ll find that’s true.

Ruby

in a Ruby repl (e.g., pry), load serrano

require 'serrano'

Query for “peerj” on the journals route

x = Serrano.journals(query: "peerj")

Collect just ISSN’s from each result

x['message']['items'].collect { |z| z['ISSN'] }
#> => [["2376-5992"], ["2167-8359"]]

Shell

The serrano command line tool is quite powerful if you are used to doing things there.

Here, search for one article; summary data is shown.

serrano works 10.1371/journal.pone.0033693
#> DOI: 10.1371/journal.pone.0033693
#> type: journal-article
#> title: Methylphenidate Exposure Induces Dopamine Neuron Loss and Activation of Microglia in the Basal Ganglia of Mice

There’s also a -json flag to give back JSON data, which can be parsed with the command line tool jq.

serrano works --filter=has_full_text:true --json --limit=5 | jq '.message.items[].link[].URL'
#> "http://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2F9781119208082.ch9"
#> "http://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2F9781119208082.index"
#> "http://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2F9781119208082.ch11"
#> "http://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2F9781119208082.ch15"
#> "http://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2F9781119208082.ch4"

In an R session, load rcrossref

library("rcrossref")

Search the works route for the phrase “science”

res <- cr_works(query = "science", limit = 5)
#> $meta
#> total_results search_terms start_index items_per_page
#> 1 4333827 science 0 5
#>
#> $data
#> Source: local data frame [5 x 23]
#>
#> alternative.id container.title created deposited DOI funder indexed
#> (chr) (chr) (chr) (chr) (chr) (chr) (chr)
#> 1 2013-11-21 2013-11-21 10.1126/science <NULL> 2015-12-27
#> 2 Science Askew 2004-11-26 2013-12-16 10.1887/0750307145/b426c18 <NULL> 2015-12-24
#> 3 2006-04-10 2010-07-30 10.1002/(issn)1557-6833 <NULL> 2015-12-25
#> 4 2013-08-27 2013-08-27 10.1002/(issn)1469-896x <NULL> 2015-12-27
#> 5 2013-12-19 2013-12-19 10.5152/bs. <NULL> 2015-12-28
#> Variables not shown: ISBN (chr), ISSN (chr), issued (chr), link (chr), member (chr), prefix (chr), publisher
#> (chr), reference.count (chr), score (chr), source (chr), subject (chr), title (chr), type (chr), URL
#> (chr), assertion (chr), author (chr)
#>
#> $facets
#> NULL

Index through to get the DOIs

res$data$DOI
#> [1] "10.1126/science" "10.1887/0750307145/b426c18" "10.1002/(issn)1557-6833"
#> [4] "10.1002/(issn)1469-896x" "10.5152/bs."

rcrossref also has faster versions of most functions with an underscore at the end (_) which only do the http request and give back json (e.g., cr_works_())

Comparison of Crossref Client Methods

After installation and loading the libraries above, the below methods are available

<th>
<span >Python</span>
</th>
<th>
<span >Ruby</span>
</th>
<th>
<span >R</span>
</th>

<td>
<span ><code>cr.works()</code></span>
</td>
<td>
<span ><code>Serrano.works()</code></span>
</td>
<td>
<span ><code>cr_works()</code></span>
</td>

<td>
<span ><code>cr.members()</code></span>
</td>
<td>
<span ><code>Serrano.members()</code></span>
</td>
<td>
<span ><code>cr_members()</code></span>
</td>

<td>
<span ><code>cr.funders()</code></span>
</td>
<td>
<span ><code>Serrano.funders()</code></span>
</td>
<td>
<span ><code>cr_funders()</code></span>
</td>

<td>
<span ><code>cr.types()</code></span>
</td>
<td>
<span ><code>Serrano.types()</code></span>
</td>
<td>
<span ><code>cr_types()</code></span>
</td>

<td>
<span ><code>cr.licenses()</code></span>
</td>
<td>
<span ><code>Serrano.licenses()</code></span>
</td>
<td>
<span ><code>cr_licenses()</code></span>
</td>

<td>
<span ><code>cr.journals()</code></span>
</td>
<td>
<span ><code>Serrano.journals()</code></span>
</td>
<td>
<span ><code>cr_journals()</code></span>
</td>

<td>
<span ><code>cr.members()</code></span>
</td>
<td>
<span ><code>Serrano.members()</code></span>
</td>
<td>
<span ><code>cr_members()</code></span>
</td>

<td>
<span ><code>cr.registration_agency()</code></span>
</td>
<td>
<span ><code>Serrano.registration_agency()</code></span>
</td>
<td>
<span ><code>cr_agency()</code></span>
</td>

<td>
<span ><code>cr.random_dois()</code></span>
</td>
<td>
<span ><code>Serrano.random_dois()</code></span>
</td>
<td>
<span ><code>cr_r()</code></span>
</td>

API Route
works
members
funders
types
licenses
journals
members
registration agency
random DOIs

Other Crossref Services

<th>
<span >Python</span>
</th>
<th>
<span >Ruby</span>
</th>
<th>
<span >R</span>
</th>

<td>
<span ><code>cn.content_negotiation()</code><a href="#footnote-1">[1]</a></span>
</td>
<td>
<span ><code>Serrano.content_negotiation()</code></span>
</td>
<td>
<span ><code>cr_cn()</code></span>
</td>

<td>
<span ><code>cn.csl_styles()</code><a href="#footnote-1">[1]</a></span>
</td>
<td>
<span ><code>Serrano.csl_styles()</code></span>
</td>
<td>
<span ><code>get_styles()</code></span>
</td>

<td>
<span ><code>counts.citation_count()</code><a href="#footnote-2">[2]</a></span>
</td>
<td>
<span ><code>Serrano.citation_count()</code></span>
</td>
<td>
<span ><code>cr_citation_count()</code></span>
</td>

Service
content negotiation
CSL styles
citation count

[1] from habanero import cn

[2] from habanero import counts

Features

These are supported in all 3 libraries:

Filters (see below)
Deep paging (see below)
Pagination
Verbose curl output

Filters

Filters (see API docs for details) are a powerful way to get closer to exactly what you want in your queries. In the Crossref API filters are passed as query parameters, and are comma-separated like filter=has-orcid:true,is-update:true . In the client libraries, filters are passed in idiomatic fashion according to the language.

Python

from habanero import Crossref
cr = Crossref()
cr.works(filter = {'award_number': 'CBET-0756451', 'award_funder': '10.13039/100000001'})

Ruby

require 'serrano'
Serrano.works(filter: {award_number: 'CBET-0756451', award_funder: '10.13039/100000001'})

library("rcrossref")
cr_works(filter=c(award_number=TRUE, award_funder='10.13039/100000001'))

Note how syntax is quite similar among languages, though keys don’t have to be quoted in Ruby and R, and in R you pass in a vector or list instead of a hash as in the other two.

All 3 clients have helper functions to show you what filters are available and what the options are for each filter.

<th>
<span >Python</span>
</th>
<th>
<span >Ruby</span>
</th>
<th>
<span >R</span>
</th>

<td>
<span ><code>filters.filter_names</code><a href="#footnote-3">[3]</a></span>
</td>
<td>
<span ><code>Serrano::Filters.names</code></span>
</td>
<td>
<span ><code>filter_names()</code></span>
</td>

<td>
<span ><code>filters.filter_details</code><a href="#footnote-3">[3]</a></span>
</td>
<td>
<span ><code>Serrano::Filters.filters</code></span>
</td>
<td>
<span ><code>filter_details()</code></span>
</td>

Action
Filter names
Filter details

[3] from habanero import filters

Deep paging

Sometimes you want a lot of data. The Crossref API has parameters for paging (see rows and offset), but large values of either can lead to long response times and potentially timeouts (i.e., request failure). The API has a deep paging feature that can be used when large data volumes are desired. This is made possible via Solr’s cursor feature (e.g., blog post on it). Here’s a run down of how to use it:

cursor: each method in each client library that allows deep paging has a cursor parameter that if you set to * will tell the Crossref API you want deep paging.
cursor_max: for boring reasons we need to have feedback from the user when they want to stop, since each request comes back with a cursor value that we can make the next request with, thus, an additional parameter cursor_max is used to indicate the number of results you want back.
limit: this parameter when not using deep paging determines number of results to get back. however, when deep paging, this parameter sets the chunk size. (note that the max. value for this parameter is 1000)

For example, cursor=”*” states that you want deep paging, cursor_max states maximum results you want back, and limit determines how many results per request to fetch.

Python

from habanero import Crossref
cr = Crossref()
cr.works(query = "widget", cursor = "*", cursor_max = 500)

Ruby

require 'serrano'
Serrano.works(query: "widget", cursor: "*", cursor_max: 500)

library("rcrossref")
cr_works(query = "widget", cursor = "*", cursor_max = 500)

Text mining clients

Just a quick note that I’ve begun a few text-mining clients for Python and Ruby, focused on using the low level clients discussed above.

Python: https://github.com/sckott/pyminer
Ruby: https://github.com/sckott/textminer

Do try them out!

Event Data: open for your interpretation

Madeleine Watson — Thu, 25 Feb 2016 00:00:00 +0000

What happens to a research work outside of the formal literature? That’s what Event Data will aim to answer when the service launches later this year.

Following the successful DOI Event Tracker pilot in Spring 2014, development has been underway to build our new service, newly re-named Crossref Event Data. It’s an open data service that registers online activity (specifically, events) associated with Crossref metadata. Event Data will collect and store a record of any activity surrounding a research work from a defined set of web sources. The data will be made available as part of our metadata search service or via our Metadata API and normalised across a diverse set of sources. Data will be open, audit-able and replicable.

We expect to include the following sources at the launch of the clearinghouse in Q3 (pending final confirmation):

[table id=1 /]

What could you achieve?

Anyone interested in metrics and analytics will have direct and open access to a single collection of DOI activity data of events occurring outside of the formal literature. As Event Data records are time-stamped, you can be assured that the data you receive is both auditable and replicable. Collected and stored by Crossref in the one location, we invite researchers, publishers, funders and altmetrics providers to consider the possibilities Event Data offers to enrich and expand your work.

With such a corpus of open, transferable and auditable raw data at your fingertips, what could you achieve?

General and altmetrics service providers

Crossref Event Data is a centrally-managed resource, therefore as a third party vendor you will have the ability to collect real-time data from a central location to enrich, analyze, interpret and report via your own tools. Using our API, you will gain regular access to our collection of raw, auditable data to feed into your own tools and services ready for aggregation and analysis. Additionally, the optional benefit of an SLA with Crossref will ensure that your clients have access to a reliable and flexible source of event data.

Journal editors

Using the data collected in our service, as an editor you can attract authors by offering data on the audience’s research interest, track the full-scope of article dissemination and gain a better understanding of how the publications you manage compare to each other. By analysing the Event Data records, you can quickly find reviewers based on publication network analysis, identify new areas to grow author submissions and track the reach of submissions selected for publication.

Funders

As a Funder, you can use Event Data to isolate and track the dissemination and usage of the research you funded outside of the scholarly literature. As the data is portable, you can be assured that should a journal move, your ability to track its dissemination moves with it. Using the Event Data records collection, you can:

Efficiently track progress of the research impact of grant awardees in an automated fashion, with the signals most relevant to your organisation

Develop measurements of research engagement at the article level which reflect your mission and current funding priorities

Gain visibility into the potent success stories highlighting the impact of your work for your development campaigns

Analyze trends of past and future funding programs

More effectively pursue your funding strategy and manage your portfolio based on data-driven decision making.

Publishers and publishing platforms

By analyzing and interpreting the Event Data collection, as a publisher or content distributor you can use the records to undertake the following metric-lead analysis to help drive your business needs:

Conduct more robust publication growth analysis across titles, subject areas, or all published literature

Gain a balanced understanding of the engagement on your publications across subject areas, titles, or managing editors

Enhance author services (personalization, content discovery, profile management, etc.)

Focused and data-driven product development of tools and services to drive audience engagement

Provide content distributors data on downstream reach of publications.

Bibliometricians

Event Data heavily supports Bibliometric research by facilitating the tracking of DOI-related research activity across different platforms and channels. As a Bibliometrician, use trusted raw data as the underlying data for your research, which you can easily obtain from Crossref in a single, normalized format across a variety of sources. Additionally, as Event Data data is replicable, portable and auditable, you will be assured of high quality results in your research projects.

Research institutions

All of the stakeholders in your institution, from the research, development and marketing offices to the researchers themselves, will benefit from access to data about where and how your research is being discussed in mainstream and social media. As a research institution, Event Data can help you:

Track dissemination of publications (types of channels, rate of growth, etc.) by members of the institution

Access up-to-date information on the research progress of faculty members, useful for tenure and promotion decisions

View data on downstream impact of publications

Roll up data for custom reporting of department’s research activities

Stay tuned, testing begins soon!

With development work on the MVP (Minimum Viable Product) scheduled to complete shortly, we will soon be releasing a small subset of data sources that are collecting event data as well as a testing environment for interested parties to explore a very preliminary version of the software as we continue to work towards implementation of the full Event Data clearinghouse release in Q3. Look out for our MVP announcement, with full technical specifications and confirmation of the selected initial pull and push sources, over the coming weeks.

Linking clinical trials = enriched metadata and increased transparency

Kirsty Meddings — Mon, 18 Jan 2016 00:00:00 +0000

We will shortly be adding a new feature to Crossmark. In a section called “Clinical Trials” we will be using new metadata fields to link together all of the publications we know about that reference a particular clinical trial.

Most medical journals make clinical trial registration a prerequisite for publication. Trials should be registered with one of the fifteen WHO-approved public trial registries , or with clinicaltrials.gov which is run by the US National Library of Medicine. Once registered, a trial is assigned a clinical trial number (CTN) which is subsequently used to identify that trial in any publications that report on it.

Publications that result from any one trial are likely to be released in multiple journals from different publishers and at different times, for example secondary analyses coming some time after the publication of the initial results. Cross-publisher collaboration is paramount to linking all of these publications together so that researchers, funders, and regulatory agencies can understand the whole set of results from clinical trials. With this in mind, a group of medical publishers, led by BioMedCentral, approached Crossref to establish a working group, and here, they designed an approach to address this problem: “thread” all the various documents together surrounding a clinical trial.

Updated upstream

To implement threaded publications, publishers extract clinical trial numbers from papers, or ask authors to submit those numbers to them. Publishers add the CTNs to the Crossref DOI metadata via three new fields: clinical trial number, clinical trial registry where trial is registered, and trial stage (pre-results, results or post-results of the trial). Crossref has assigned unique IDs to each trial registry (much the same as we have done for funders in our Funder Registry and for the same reason - trial registry names and URIs can change over time and we need a persistent identifier). Using a combination of trial registry ID and clinical trial number, we can easily identify other content in the Crossref database that cites the same trial. Finally, Crossref displays the clinical trial metadata on the respective papers for all participating Crossmark publishers. Crossmark is a convenient place for readers to access the clinical trial information and is readily accessible directly from the journal article (online and PDF versions). And of course all of the data also goes into our open API so that anyone can make use of it.

The reporting of clinical trial results is notoriously inconsistent, something that the AllTrials initiative is also seeking to address. Publishers can help by collecting this information upstream and disseminating it using the existing Crossref infrastructure.

We ask all publishers to deposit the clinical trial data which is so critical to transparency in this area of research, and have already had the first data in from Crossref member the National Institute of Health Research. Once we launch the initial set of linked clinical trials, we will expand coverage of the threaded publications to include all content that reports on or references a clinical trial, from protocol to results to supporting data and systematic reviews.

Stay tuned and watch this space as threaded publications rolls out to journal articles across publishers!

Crossref & the Art of Cartography: an Open Map for Scholarly Communications

Jennifer Lin — Fri, 08 Jan 2016 00:00:00 +0000

In the 2015 Crossref Annual Meeting, I introduced a metaphor for the work that we do at Crossref. I re-present it here for broader discussion as this narrative continues to play a guiding role in the development of products and services this year.

Metadata enable connections

At Crossref, we make research outputs easy to find, cite, link, and assess through DOIs. Publishers register their publications and deposit metadata through a variety of channels (XML, CSV, PDF, manual entry), which we process and transform into Crossref XML for inclusion into our corpus. This data infrastructure which makes possible scholarly communications without restrictions on publisher, subject area, geography, etc. is far more than a reference list, index or directory.

If research builds on what came before, one could claim that the process of knowledge production is partly the story of the very relationships between results disseminated (i.e., publications). So let’s consider each publication as a node in a graph where each has a coordinate and is connected by its citations to other publications (as well those that cite it). Additionally, each is associated with a set of people and places, along with a whole host of elements involved in the research and dissemination process.

But take a wider berth, and we begin to capture relationships between all such contributing agents and objects involved in the research process. Here we find an array of entities belonging to the scholarly graph, including different types of research artifacts, publisher and journal, funders, ORCIDs, peer reviews, publication status updates (corrections, retractions, etc.), citations, license information, additional URLs (machine destinations, hosting platforms, etc.), underlying data, software and protocols, materials, discussions and blog posts, recommendations, reference work mentions, etc. The entities on the graph multiply at an even higher rate as researchers share more outputs across more channels. And over time, the graph expands exponentially, producing a webbing that is far more dense and far more vast than we can currently imagine. Perhaps even to the point we realize Borges’ story where a cartographer builds a map so large it replicates the territory itself (On Exactitude in Science)!

From graph to cartography

At the heart of Borges’s poignant story is the map. Crossref’s graph of scholarly communications could be seen in the same light. It has a representational aspect, which is not purely abstract and can be visualized. Here, a map becomes an incredibly potent metaphor. Each link enabled by publisher-deposited metadata is a new street, bridge, or highway that takes us to a particular place (i.e., entity) of interest. These roads lead to articles, researchers, funders, institutions, etc., and in doing so, make them discoverable. They tell a story about the roles of each in the broader research in the landscape dotted with a plethora of places.

The scholarly web has a growing corpus of more than 78 million publications at this very moment registered with Crossref. On average ten to fifteen thousand new objects appear every day. Maps are all the more essential for getting around in a bewildering environment of new and unfamiliar places, even for known ones in areas of exploding growth. They are critical for orienteering, discovering relationships, identifying sets of associated objects, naming new neighborhoods that emerge (i.e., new research specialties), etc. And if each connection on the map is seen as an event, maps can also represent micro-narratives about the research process and the agents involved. A multi-dimensional map containing all these entities, which serves as an evolving representation of spacetime that is constantly updated and always available, would finally begin to depict the process of scholarly activity as a dynamic, evolving, almost living system.

An open map for scholarly communication

Crossref builds such a scholarly map of the research enterprise and makes it openly available for the entire research ecosystem. Call this a meta map or, more recently, call it metastructure. No matter what name it goes by we call it infrastructure at Crossref.

Crossref’s open map for scholarly communications is a core part of the open information infrastructure for scholarly research. Crossref map data are open, portable, as well as licensed and provisioned for maximum reuse to serve the whole community. This open resource has two entrances: one for humans, another for machines. The Crossref REST API enables machines to traverse this environment and mine it in equal measure to the humans behind them. It is configured so that a robot can learn, a phone can access, and platforms can be built.

OpenStreetMap and Google Maps, both widely used and mature infrastructure maps, are instructive examples when we consider a map of this kind for scholarly communications. Map data can be represented in unlimited ways, depending on any variety of needs and users. Third parties can add content via interactive layers that tell different stories such as health expenditure by country based on GDP and coral reefs at risk. They have a broad base of users across business models from philanthropic services aimed at disaster relief (Refugeemaps.eu) to commercial entities providing drivers with locations on open parking spaces (AppyParking on Google Map, PocketParker on OpenStreetMap). They power platforms and services that build maps for others (MapQuest, MapBox). They have applications far beyond the business of maps. For example, Place picker is a Google Maps widget that supports easy auto-complete the entry of any place or location on a mobile app where typing is a chore. And as far use cases close to home, the two have served as raw data for academic research (ex: workflow for generating multi-agent traffic simulation scenarios, automatic classification of GPS trajectories for transportation modes, etc.).

In kind, the Crossref infrastructure map also supports: the development of any variety of new maps which re-present the data, the makers of map platforms that power the research enterprise, tools that use map data, as well as academic research (bibliometrics). We extract slices of data of common interest from the map and add them as additional layers by which anyone can access and create applications on or across these bands of data:

Contributors (authors, editors, reviewers)
Funding information (funding body, grant number)
Trial & study information (clinical trials registry number, registered report, replication study)
Publication history (versions, updates, revisions, corrections, retractions, dates received/accepted/published)
Peer review (status, type, reviews)
Access indicators (publication license for text & data mining, machine mining URLs)
Resources & associated research artifacts (preprints, figures & tables, datasets, software, protocols, research resource IDs)
Activity surrounding the publication (peer reviews, comments & discussions, bookmarks, social shares, recommendations).

Today, the map powers a host of public and commercial organisations alike for a wide range of scholarly and non-scholarly purposes:

<td style="border: 1px solid #ffffff;">
<ul>
<li>
<span >Indexing services</span>
</li>
<li>
<span >Publishing vendors</span>
</li>
<li>
<span >Peer review systems</span>
</li>
<li>
<span >Reference manager systems</span>
</li>
<li>
<span >Lab & diagnostics suppliers</span>
</li>
<li>
<span >Info management systems</span>
</li>
<li>
<span >Educational tools</span>
</li>
<li>
<span >Data analytics systems</span>
</li>
<li>
<span >Literature discovery services</span>
</li>
</ul>
</td>

Publishers
Funders
Research institutions
Archives & repositories
Research councils
Data centres
Professional networks
Patent offices
Registration Agencies

We will follow up this post to highlight a cross-section of these consumers in the Crossref map ecosystem and elaborate on what & how they have built from our data. An infrastructure map offers endless potential to third parties across publishers, funders, research institutions, and vendors working to serve the scholarly research enterprise.

The art of cartography

In the Crossref Product Management team, we have ambitious plans for map enhancements this year. They focus on expanding information density and ease of access to the data. In the former case, we will introduce a new class of locations where activity surrounding the publications are occurring when we launch the DOI Event Tracker. We will also initiate an extensive publisher campaign to achieve full metadata deposit completeness across our membership. No one can keep pace with the sheer volume of research activity happening online nor wander the Lonely Web of research alone. The more metadata publishers provide for a publication, the more roads lead to its map location. After all, discoverability is closely associated with connectedness on a map. And finally, in the latter case, we will refresh and enhance the user interface to make it more powerful for humans to traverse the ever-changing landscape (as easily as the REST API enables machines!).

I gratefully acknowledge the feedback received from the following who served as generous and insightful sounding boards: Virginia Barbour, Theo Bloom, Martin Eve, Daniel S. Katz, Amye Kenall, Catriona MacCullum, Cameron Neylon, Mark Patterson, Kristen Ratan, Carly Strasser, and Kaitlin Thaney.

A healthy infrastructure needs healthy funding data

Kirsty Meddings — Wed, 16 Dec 2015 00:00:00 +0000

We’ve been talking a lot about infrastructure here at Crossref, and how the metadata we gather and organize is the foundation for so many services - those we provide directly - and those services that use our APIs to access that metadata, such as Kudos and CHORUS, which in turn provide the wider world of researchers, administrators, and funders with tailored information and tools.

The initiative formerly known as FundRef

Together Crossref’s funding data (previously known as FundRef – we simplified the name) and the Open Funder Registry, our taxonomy of grant-giving organisations, comprise a hub for gathering and querying metadata related to the questions:

“Who funded this research?” and “Where has the research we funded been published?”

To support the funding data initiative, three key pieces of metadata are needed from publishers:

Funder ID
Funder Name
DOI

Unfortunately only around half of the 950,000 Crossref DOIs with funding data contain funder IDs, the unique funder identifiers from the Open Funder Registry that are needed to link up all of the data. So, only half of the data is useful. (And 950,000 DOIs is only a fraction of the 77 million DOIs in our database, but more on that later).

When we looked at the funding data that was coming in without funder IDs we were a little surprised. We had expected that most of these would be names that simply aren’t in the Open Funder Registry yet, and we thought there would be a certain amount of incorrect information that had been entered into the “funder_name” field.

Instead, what we found was that many of the names were correct, and the funder IDs were just missing.

Tidying the data

To help correct this, we decided to match incoming names to funder IDs where we could do so with the highest level of confidence. After much testing to minimize false positives, we switched this on at the end of August 2015.

Throughout September and October, we inserted funder IDs for about 25% of the names that have been deposited without IDs. For October, the real numbers were 68,000 funder names with no IDs deposited, and 18,000 funder IDs inserted by Crossref.

In the same period 42,000 funder IDs were deposited by publishers. With our matching on top of this, we are achieving a little over a 50% overall success rate of “good” funding data (funder names and funder IDs together).

We have been very careful to distinguish the funder IDs that we have added from those deposited by publishers - provenance of data is an extremely important part of what we do. All funder IDs are tagged as provided either by the publisher or Crossref. Every time we insert an ID into a deposit, the publisher is notified in the deposit report.

We have also now added these tags to our REST API so that publishers can query to find out exactly which DOIs we have amended*. The ideal scenario at this point is that the publisher checks that they are happy with the matching and then redeposits the funding data for those DOIs, over-writing the doi-asserted-by: “crossref” tag and claiming the metadata as their own.

Setting some limits

The second largest problem with funding data was incorrectly entered funder name – e.g. concatenation of several names or authors entering overly long or vague program names instead of the official funder name.

To help weed this out, we have made a couple of changes to the funding data deposit system:

Funder_name field can no longer contain a numerical string over 4 digits
Funder_name field can no longer contain a text string over 200 characters
Funder names that that do not adhere to these two rules will now cause the funding data section of the metadata deposit (not the whole deposit) to fail and return an error message.

Getting the growth we need

As of today, 198 publishers deposit funding data with Crossref. This amounts to about 3.5% of Crossref’s membership (although it’s a larger proportion of our total deposits). We need more publishers to deposit funding data so that funding data search can become a truly useful tool for the community. There’s no sign-up process or additional fee - read about how to get started, and take a look at our best practices for depositing funding data.

Finally, we ask you: how can we get more and better funder metadata in 2016?

This is not a rhetorical question. Please tweet your thoughts @CrossrefOrg or email your replies to info@crossref.org. You will receive something special via snail mail if you reply to us – just Crossref’s way of saying thank you.

^{*At the time of posting our database is re-indexing and the “asserted-by” tags are still filtering through to the API. Check back in a day or two for the full picture.}

Scheduled Booth Presentations at the Frankfurt Book Fair

Anna Tolwinska — Tue, 29 Sep 2015 00:00:00 +0000

Oktoberfest is in full swing and that makes me think that it’s almost Frankfurt Book Fair time again!

This year in addition to individual meetings we’ll have scheduled flash presentations on our booth, M91 in Hall 4.2. These short (10-minute) presentations are great for anyone wanting a quick intro to what Crossref is all about. Running on Wednesday, Thursday, and Friday - at the following times each of those days:

10am - Small Publisher Tools
12pm - DOIs & Metadata Basics
3pm - Exploring through APIs

If you’d like to meet with us (Ed Pentz, Ginny Hendricks, Rachael Lammey, or Anna Tolwinska) please contact Rosa Morais Clark to set up a meeting.

We look forward to seeing you there!

Crossref to Auto-Update ORCID Records

Ginny Hendricks — Thu, 24 Sep 2015 00:00:00 +0000

In the next few weeks, authors with an ORCID iD will be able to have Crossref automatically push information about their published work to their ORCID record. It’s something that ORCID users have been asking for and we’re pleased to be the first to develop the integration. 230 publishers already include ORCID iDs in their metadata deposits with us, and currently there are 248,000 DOIs that include ORCID iDs.

What this means for researchers

More visibility for your work! Crossref represents over 5000 scholarly publishers and many of them ask authors for their ORCID iD and include it in the publication information they send us. Also it will mean less manual searching and adding; you’ve always been able to search crossref metadata for your name and/or publications and manually add them to your ORCID record, this auto-update simply means that when your publishers include the info we can update and add work(s) to your ORCID record automatically for you. You can still choose to hide/show whatever works you choose, and, of course, you’ll have the opportunity to authorize or switch off the integration completely (though future publications may trigger a new request). Overall, you’ll benefit from a more complete and up-to-date ORCID record to showcase your work.

What this means for publishers

If you’re one of the 230 Crossref publishers who already supply ORCID iDs along with the usual metadata submissions, then you’re all good. If you don’t offer this yet, you might want to think about starting - it’s beneficial for funders, publishers, other researchers, libraries, and universities to be able to integrate with complete researcher records. You can ask for ORCIDs upon manuscript submission or acceptance and tag it in your metadata deposits with Crossref. We’ll ensure the rest.

Various caveats and important details to be aware of

Apparently not all publishers are members of Crossref (we know, crazy), and in addition only a subset of Crossref publishers (230 in total) are asking authors for ORCID iDs and/or including them in their metadata deposits.
Some publishers may choose to opt out of passing through the details to ORCID using the Crossref auto-update (perhaps they plan to send this directly at some point) but if you’ve included your ORCID with your submission and it isn’t automatically updated, then check with your publisher.
We have a “backlog” of almost 250,000 DOIs that include ORCID iDs so that may mean we do some bulk updates at a later date where authors will receive an email with a long list of works to add. Even if the works have been listed before, it’s worth accepting as it will add the most up-to-date metadata to ensure the most accurate record.

Any questions can be directed to our support team.

Best Practices for Depositing Funding Data

Kirsty Meddings — Tue, 01 Sep 2015 00:00:00 +0000

Crossref’s funding data initiative (FundRef) encourages publishers to deposit information about the funding sources of authors’ research as acknowledged in their papers. The funding data comprises funder name and identifier, and grant number or numbers. Funding data can be deposited on its own or with the rest of the metadata for an item of content.

There are two ways that publishers can collect this funding information for any given piece of content: by asking authors to input the funder name(s) and award number(s) via their submission system, or extracting the funder names and award numbers from the acknowledgements in the paper.

The funding data is only useful if it is standardised, and so it is absolutely critical that funder names are deposited with their associated funder IDs from the Funder Registry.

For publishers considering or about to start collecting and depositing funding data, and for those already doing so, we have drawn up some guidelines that will help you to ensure good quality metadata.

If you are collecting funding information from authors via your submission system:

Provide very clear instructions for your authors. Your submission system should prompt the author towards the canonical name from Crossref’s Funder Registry as they type, or guide them through a pick-list. Make it clear to authors that they should choose funder names from this list and not copy and paste from their manuscript.
Work with your submission system vendor or adapt your in-house system to make it easy for authors to select from the Funder Registry, and more difficult to paste incorrect names or ignore the suggested names. Consider a warning message if an unknown name is entered, and offer a list of close matches.
Instruct authors to look for the name of the funding body rather than a specific program or project.

If you or one of your vendors is extracting funding information from papers:

Provide the same clear instructions to your vendor(s). Stress the importance of matching the funder names in the acknowledgements to the names in the Funder Registry.
Look for common text-extraction errors such as concatenated funder names, punctuation errors, and stop words such as “of/for” that are commonly used interchangeably, or the presence or absence of “the” at the start of a funder name.

For both workflows:

Add QA into your workflow. Many of the names sent to Crossref without IDs are very obviously funders that are in the Registry, and a check by editorial or production staff could correct misspellings or fill in blanks. Check that grant numbers have been separated and are not being deposited as one long string.
Be aware that funder names deposited without IDs are not valid funding data and will be hidden from Crossref’s search tools and APIs until such time as they are updated with a funder ID.
The funding data section of a deposit (but not the rest of the deposit) will be rejected by the Crossref deposit system if
- The funder_name field contains a numerical string longer than 4 digits
- The funder_id field contains a number that is not an ID from the Funder Registry
- The funder_name contains text that exceeds 200 characters
Consider only depositing data that has funder IDs and holding the rest to re-poll against the Funder Registry at a later date when more funder names have been added. The Funder Registry is updated at approximately two-monthly intervals. You can sign up to be alerted to updates here.
If there are funders that appear regularly in your particular subject or geographical area that are not in the Registry, send a list to funder.registry@crossref.org.

Introducing the Crossref Labs DOI Chronograph

Joe Wass — Mon, 12 Jan 2015 00:00:00 +0000

tl;dr http://chronograph.labs.crossref.org

At Crossref we mint DOIs for publications and send them out into the world, but we like to hear how they’re getting on out there. Obviously, DOIs are used heavily within the formal scholarly literature and for citations, but they’re increasingly being used outside of formal publications in places we didn’t expect. With our DOI Event Tracking / ALM pilot project we’re collecting information about how DOIs are mentioned on the open web to try and build a picture about new methods of citation.

As part of the preparation for collaborating with Wikipedia, we looked at our statistics about when DOIs are clicked and discovered that Wikipedia was, over a two year period from 2012, the eighth largest referrer of DOIs. This means that not only does Wikipedia have a lot of DOIs, but people click them too. This bit of one-off data analysis (which surprised us) gave us enough of a prod to kickstart our collaboration with Wikipedia.

At the ALM Workshop 2014 in San Francisco we talked to some Wikipedians and bibliometricians and realised that we were sitting on a really interesting data-set and that it would be churlish not to share it. At the hackathon (read the report here) we started work on a service to gather information about DOIs and, a month later, we’re ready to unveil the DOI Chronograph.

Show me the goods

You can see:

Daily referrals (clicks) from top level domains, e.g. Wikipedia.org: http://chronograph.labs.crossref.org/domain.html?domain=wikipedia.org

Daily referrals from specific subdomains, e.g. fr.wikipedia.org: http://chronograph.labs.crossref.org/domain.html?domain=fr.wikipedia.org

Daily resolutions per DOI: http://chronograph.labs.crossref.org/doi.html?doi=10.1787%2F20752288

And, the chart that kicked this all off: DOI referring domains league tables. This shows that Wikipedia is the 3rd or 4th non-traditional referrer of DOIs (i.e. excluding referrals from Publishers’ domains): http://chronograph.labs.crossref.org/top.html

Try it out

Visit the Chronograph and give it a try chronograph.labs.crossref.org on your favourite DOI (everyone has one).

More data

Talking to a bibliometrician we also realised we can correlate other data for DOIs. We’re getting the issue date (approximately the publication date) from our own metadata, as well as the date that the Crossref metadata was updated. This gives interesting results, like the resolutions for 10.1038/ncomms2953, which peak after publication and then tails off. We are attempting to collect the following information:

daily resolution counts
day on which resolution was first successful
day on which it’s possible to resolve the DOI (we’ve got a bot running for new publications)
day on which the publisher says the article was published
day on which the metadata was most recently deposited with us
day on which the metadata was first deposited with us

We’re not there yet, but we’ve made a start and we’ve already got some pretty interesting data!

Weasel words

It’s a labs project so the usual weasel words apply. Specifically, we currently have the logs for 2012 to 2014 (we’re working at digging out the rest), and the referral information for 50 million DOIs (out of 71 million). That number will be higher by the time you read this. If your page is slow to load, be patient, as it’s currently working hard crunching numbers.

This project is focused on exploring the use of DOIs outside of the formal literature. As such, we are only looking at referrals from domains that do not appear to belong to primary publishers (i.e. our members). If you try a domain and it doesn’t work, it could be that the domain belongs to one of our members. If you’ve notice any mistakes, please email us at labs@crossref.org .

Finally, these numbers contain all DOI resolutions. That’s human clicks but also content negotiation to retrieve metadata, robots etc. We might try to filter them in future, but for now be aware that not every visitor is a human.

I’ll detail some of the the technical stuff (it’s very interesting) and what happened next with Wikipedia in a future post. Watch this space.

♫ Researchers just wanna have funds ♫

Geoffrey Bilder — Thu, 10 Apr 2014 00:00:00 +0000

photo credit

Summary

You can use a new Crossref API to query all sorts of interesting things about who funded the research behind the content Crossref members publish.

Background

Back in May 2013 we launched Crossref’s FundRef service. It can be summarized like this:

Crossref keeps and manages a canonical list of Funder Names (ephemeral) and associated identifiers (persistent).
We encourage our members (or anybody, really- the list is available under A CC-Zero license waiver) to use this list for collecting information on who funded the research behind the content that our members publish.
We then ask that our members deposit this data in their normal Crossref metadata deposits.

And that was cool.

But then people started asking us awkward questions. Questions like “what can I do with the funder data?” and “how do I query it?”.

Stoopit people.

Can’t you just let us bask for a few minutes in the sunny glow of actually conceiving of and launching a project within a year?

But seriously, funders, were interested to see how they could use the funder metadata being collected in Crossref. In particular, some funding agencies were interested in being able to measure Key Performance Indicators (“KPIs” to management wonks) related to recent mandates such as the February 22nd 2013 OSTP memo, Public Access to the Results of Federally Funded Research. Two groups also approached us, CHORUS and SHARE. Both are interested in exploring how to build reporting tools for funders, institutions and researchers and each brought us a gigantic hairball of use-cases they were hoping we would be able to meet.

Conveniently, we were in the process of creating a revised, modern Crossref API that is entirely buzzword-compliant, and so we set to work…

We thought people might be interested in seeing what you can do with the Crossref REST API in relation to funding information and the expectations that are increasingly being attached to them. CHORUS is already using the Crossref REST API heavily and we expect that SHARE will soon start making use of it as well. The feedback from both groups has been very useful, but we are looking for broader feedback as well. The API is still in development, so now is your chance to help us shape it.

Brief Examples

Please note, the following are APIs calls, although you can copy and paste the URIs into your browser, the data is returned in a machine readable representation called JSON. If you want the results to look a little more presentable, we advise you install the JSONView plugin:

Firefox Users: JSONView
Chrome Users: JSONView

Also note that publishers have only just started to deposit the metadata needed for these APIs to work, so the data is currently sparse. We know that many of our members are working feverishly to populate more of the needed metadata, but this requires updates to the their manuscript tracking systems, production systems and hosting systems. It takes time.

But for now you can paste the relevant URIs below into your browser and see the results that we do have. Expect these numbers to increase sharply over the next few months

To start with, you might want to know how many articles in Crossref have FundRef metadata:

https://api.crossref.org/v1/works?filter=has-funder:true&rows=0

You could then be interested in knowing how many works in Crossref use FundRef to credit the United States’ National Science Foundation (NSF) for funding their research? First you need to find out what the FundRef identifier is for the NSF:

https://api.crossref.org/v1/funders?query=NSF

You can see that there are several entries that match “NSF”, and that the one we are looking for has the identifier http://dx.doi.org/10.13039/100000001. Remember, funding agency names can change frequently, the ID provides a persistent link to the funder even if their name changes.

If you are curious, you can see the details for the NSF entry, including its location, parent and child organisations:

https://api.crossref.org/v1/funders/10.13039/100000001

Notice that the results also lists the work-count. This is the number of works in the Crossref metadata that list the US NSF as having funded the research.

So perhaps you would like to see the list of works. The following will list the first twenty:

https://api.crossref.org/v1/funders/10.13039/100000001/works

You can page through the results with the offset argument:

https://api.crossref.org/v1/funders/10.13039/100000001/works?offset=20
https://api.crossref.org/v1/funders/10.13039/100000001/works?offset=40
...

How many works that have listed the NSF as a funder have license information:

https://api.crossref.org/v1/funders/10.13039/100000001/works?filter=has-license:true&rows=0

Lets see the first batch that have license information:

https://api.crossref.org/v1/funders/10.13039/100000001/works?filter=has-license:true

Lets look at the metadata for one of the DOIs returned:

https://api.crossref.org/v1/works/10.1063/1.3593378

Interesting, the metadata shows an article published by AIP. It includes license information (CC-BY 3.0) as well as a link to the full text. If you follow the link to the full text, you can retrieve it:

http://link.aip.org/link/applab/v98/i21/p216101/pdf/CHORUS

Wow- A pretty short article. But you can see that it does credit the NSF and that the award number recorded in the text is the same as the award number recorded in the FundRef section of the Crossref metadata. Yay.

You can see in the brief examples above that there is a lot of other metadata you may want to query on and explore. It can include ORCIDS, information about archiving arrangements- even abstracts. It all depends on what the Crossref member has decided to provide.

You can get a simple overview of what a Crossref member has provided by looking at a member summary. Here is an example for Hindawi:

https://api.crossref.org/v1/members?query=hindawi

Note again that names are fickle, so the above query can also be accomplished using the member identifier like this:

https://api.crossref.org/v1/members/98

Groovy init?

If you want more pointers on where you can learn how to use the API, read on…

The Future of the Crossref REST API.

Our aim is for the Crossref REST API to go into production this Summer (2014). As with most of our newer APIs, there will be a free API for public use and a paid for API for professional use. The only difference between the two will be that the professional version will come with a service level agreement (SLA) covering uptime, response time and support. Naturally, this also means that the professional one will be on dedicated hosting equipment so that we can meet these SLAs, whereas the performance of the free version will be subject to the vicissitudes inherent in using a shared, constrained resource (i.e. the server and network it is running on).

Again, the basics of the API are in place. It should be fairly stable, but we do reserve the right to make changes to it over the next few months. Please send us feedback.

— The Weasel

PDF-Extract

Geoffrey Bilder — Tue, 17 Apr 2012 00:00:00 +0000

PDF-EXTRACT

Crossref Labs is happy to announce the first public release of “pdf-extract” an open source set of tools and libraries for extracting citation references (and, eventually, other semantic metadata) from PDFs. We first demonstrated this tool to Crossref members at our annual meeting last year. See the pdf-extract labs page for a detailed introduction to this new set of tools.

If you are unable to download and install the tool, you can play with a experimental web interface called “Extracto.” Be warned, Extracto is running on very feeble server using an erratic and slow internet connection. The only guarantee that we can make about using it is that it will repeatedly fall over and annoy you. The weasel has spoken.

Turning DOIs into formatted citations

Karl Ward — Mon, 28 Nov 2011 00:00:00 +0000

Today two new record types were added to dx.doi.org resolution for Crossref DOIs. These allow anyone to retrieve DOI bibliographic metadata as formatted bibliographic entries. To perform the formatting we’re using the citation style language processor, citeproc-js which supports a shed load of citation styles and locales.

In fact, all the styles and locales found in the CSL repositories, including many common styles such as bibtex, apa, ieee, harvard, vancouver and chicago are supported. First off, if you’d like to try citation formatting without using content negotiation, there’s a simple web UI that allows input of a DOI, style and locale selection. If you’re more into accessing the web via your favorite programming language, have a look at these content negotiation curl examples. To make a request for the new “text/bibliography” record type: $ curl -LH “Accept: text/bibliography; style=bibtex” http://dx.doi.org/10.1038/nrd842 @article{Atkins_Gershell_2002, title={From the analyst’s couch: Selective anticancer drugs}, volume={1}, DOI={10.1038/nrd842}, number={7}, journal={Nature Reviews Drug Discovery}, author={Atkins, Joshua H. and Gershell, Leland J.}, year={2002}, month={Jul}, pages={491-492}} A locale can be specified with the “locale” record type parameter, like this: $ curl -LH “Accept: text/bibliography; style=mla; locale=fr-FR” http://dx.doi.org/10.1038/nrd842 Atkins, Joshua H., et Leland J. Gershell. « From the analyst’s couch: Selective anticancer drugs ». Nature Reviews Drug Discovery 1.7 (2002): 491-492. You may want to process metadata through CSL yourself. For this use case, there’s another new record type, “application/citeproc+json” that returns metadata in a citeproc-friendly JSON form: $ curl -LH “Accept: application/citeproc+json” http://dx.doi.org/10.1038/nrd842 {“volume”:“1”,“issue”:“7”,“DOI”:“10.1038/nrd842”,“title”:“From the analyst’s couch: Selective anticancer drugs”,“container-title”:“Nature Reviews Drug Discovery”,“issued”:{“date-parts”:[[2002,7]]},“author”:[{“family”:“Atkins”,“given”:“Joshua H.”},{“family”:“Gershell”,“given”:“Leland J.”}],“page”:“491-492”,“type”:“article-journal”} Finally, to retrieve lists of supported styles and locales, see:

* https://crosscite.org

style and locale repositories. There’s one big caveat to all this. The CSL processor will do its best with Crossref metadata which can unfortunately be quite patchy at times. There may be pieces of metadata missing, inaccurate metadata or even metadata items stored under the wrong field, all resulting in odd-looking formatted citations. Most of the time, though, it works.

Content Negotiation for Crossref DOIs

Geoffrey Bilder — Tue, 19 Apr 2011 00:00:00 +0000

So does anybody remember the posting DOIs and Linked Data: Some Concrete Proposals?

Well, we went with option “D.”

From now on, DOIs, expressed as HTTP URIs, can be used with content-negotiation.

Let’s get straight to the point. If you have curl installed, you can start playing with content-negotiation and Crossref DOIs right away:

curl -D - -L -H   “Accept: application/rdf+xml” “http://dx.doi.org/10.1126/science.1157784”

curl -D - -L -H   “Accept: text/turtle” “http://dx.doi.org/10.1126/science.1157784”

curl -D - -L -H   “Accept: application/atom+xml” “http://dx.doi.org/10.1126/science.1157784”

Or if you are already using Crossref’s “unixref” format:

curl -D - -L -H “Accept: application/unixref+xml” “http://dx.doi.org/10.1126/science.1157784&#8221;

This will work with over 46 million Crossref DOIs as of today, but the beauty of the setup is that from now on, any DOI registration agency can enable content negotiation for their constituencies as well. DataCite- we’re looking at you 😉 .

It also means that, as registration agency members (Crossref publishers, for instance) start providing more complete and richer representations of their content, we can simply redirect content-negotiated requests directly to them.

We expect that that this development will round-out Crossref’s efforts to support standard APIs including OpenURL and OAI_PMH and we look forward to seeing DOIs increasingly used in linked data applications.

Finally, Crossref would just like to thank the IDF and CNRI for their hard work on this as well as Tony Hammond and Leigh Dodds for their valuable advice and persistent goading.

Add Crossref metadata to PDFs using XMP

Geoffrey Bilder — Wed, 09 Dec 2009 00:00:00 +0000

In order to encourage publishers and other content producers to embed metadata into their PDFs, we have released an experimental tool called “pdfmark”, This open source tool allows you to add XMP metadata to a PDF. What’s really cool, is that if you give the tool a Crossref DOI, it will lookup the metadata in Crossref and then apply said metadata to the PDF. More detail can be found on the pdfmark page on the Crossref Labs site. The usual weasels words and excuses about “experiments” apply.

Recommendations on RSS Feeds for Scholarly Publishers

Geoffrey Bilder — Mon, 19 Oct 2009 00:00:00 +0000

We’re pleased to announce that a Crossref working group has released a set of best practice recommendations for scholarly publishers producing RSS feeds.

Variations in practice amongst publisher feeds can be irritating for end-users, but they can be insurmountable for automated processes. RSS feeds are increasingly being consumed by knowledge discovery and data mining services. In these cases, variations in date formats, the practice of lumping all authors together in one <dc:creator> element, or generating invalid XML can render the RSS feed useless to the service accessing it.

The recommendations intended to facilitate good practice in the production and provision of TOC RSS Feeds. The guidelines include general recommendations for good practice, specific recommendations on the use of RSS Modules and an example RSS TOC feed. Ultimately, we expect that industry wide adoption of these best practices will help drive more traffic to publisher web sites. Note that most of these recommendation can also be applied to non-TOC RSS feeds such as thematic feeds, automated search result feeds, etc.

Citation Typing Ontology

Geoffrey Bilder — Fri, 20 Mar 2009 00:00:00 +0000

I was happy to read David Shotton’s recent Learned Publishing article, Semantic Publishing: The Coming Revolution in scientific journal publishing, and see that he and his team have drafted a Citation Typing Ontology.^*

Anybody who has seen me speak at conferences knows that I often like to proselytize about the concept of the “typed link”, a notion that hypertext pioneer, Randy Trigg, discussed extensively in his 1983 Ph.D. thesis.. Basically, Trigg points out something that should be fairly obvious- a citation (i.e. “a link”) is not always a “vote” in favor of the thing being cited.
In fact, there are all sorts of reasons that an author might want to cite something. They might be elaborating on the item cited, they might be critiquing the item cited, they might even be trying to refute the item cited (For an exhaustive and entertaining survey of the use and abuse of citations in the humanities, Anthony Grafton‘s, The Footnote: A Curious History, is a rich source of examples)
Unfortunately, the naive assumption that a citation is tantamount to a vote of confidence has become inshrined in everything from the way in which we measure scholarly reputation, to the way in which we fund universities and the way in which search engines rank their results. The distorting affect of this assumption is profound. If nothing else, it leads to a perverse situation in which people will often discuss books, articles, and blog postings that they disagree with without actually citing the relevant content, just so that they can avoid inadvertently conferring “wuffie” on the item being discussed. This can’t be right.
Having said that, there has been a half-hearted attempt to introduce a gross level of link typology with the introduction of the “nofollow” link attribute- an initiative started by Google in order to try to address the increasing problem of “Spamdexing”. But this is a pretty ham-fisted form of link typing- particularly in the way it is implemented by the Wikipedia where Crossref DOI links to formally published scholarly literature have a “nofollow” attribute attached to them but, inexplicably, items with a PMID are not so hobbled (view the HTML source of this page, for example). Essentially, this means that, the Wikipedia is a black-hole of reputation. That is, it absorbs reputation (through links too the Wikipedia), but it doesn’t let reputation back out again. Hell, I feel dirty for even linking to it here ;-).
Anyway, scholarly publishers should certainly read Shotton’s article because it is full of good, and practical ideas about what can can be done with today’s technology in order to help us move beyond the “digital incunabula” that the industry is currently churning out. The sample semantic article that Shotton’s team created is inspirational and I particularly encourage people to look at the source file for the ontology-enhanced bibliography which reveals just how much more useful metadata can be associated with the humble citation.
And now I wonder whether CiteULike, Connotea, 2Collab or Zotero will consider adding support for the CItation Typing Ontology into their respective services?
* Disclosure:
a) I am on the editorial board of Learned Publishing
b) Crossref has consulted with David Shotton on the subject of semantically enhancing journal articles

Poorboy Metadata Hack

Tony Hammond — Tue, 06 Jan 2009 00:00:00 +0000

I was playing around recently and ran across this little metadata hack. At first, I thought somebody was doing something new. But no, nothing so forward apparently. (Heh! 🙂

I was attempting to grab the response headers from an HTTP request on an article page and was using by default the Perl LWP library. For some reason I was getting metadata elements being spewed out as response headers - at least from some of the sites I tested. With some further investigation I tracked this back to LWP itself which parses HTML headers and generates HTTP pseudo-headers using an X-Meta- style header. (This can be viewed either as a feature of LWP or a bug as this article bemoans.)

What this means anyway is that I can issue a simple call like this to get the HTML metadata - shown here for doi:10.1087/095315108X288947:

``I was playing around recently and ran across this little metadata hack. At first, I thought somebody was doing something new. But no, nothing so forward apparently. (Heh! 🙂

What this means anyway is that I can issue a simple call like this to get the HTML metadata - shown here for doi:10.1087/095315108X288947:

This shows a simple (read lazy) means of accessing metadata added as <meta> tags in HTML headers, such as those we added for Nature. (Of course, machine readable metadata is best added using RDFa as noted earlier, but does not preclude also adding in <meta> tags which are also usable with HTML as well as XHTML.)

(Btw, wouldn’t it be fun if Crossref had a random DOI facility? That would be real handy for testing as well as giving users a feel for what real-life DOIs look like and what lies at the other end of them.)

And the DOI is …

Tony Hammond — Mon, 22 Dec 2008 00:00:00 +0000

Once structured metadata is added to a file then retrieving a given metadata element is usually a doddle. For example, for PDFs with embedded XMP one can use Phil Harvey’s excellent Exiftool utility.

Exiftool is a Perl library and application which I’ve blogged about here earlier which is available as a ‘.zip‘ file for Windows (no Perl required) or ‘.dmg‘ for MacOS. Note that Phil maintains this actively and has done so over the last five years. (And when I say actively I mean just that. I once made the mistake of printing out the change file.)

If Perl’s not your thing, then there’s a Ruby wrapper gem (MiniExiftool) to access the Exiftool command in trouper OO fashion. Here’s an example Ruby one-liner to get the DOI from a PDF (broken here to meet column width restriction):

% ruby -rubygems -e 'require "mini_exiftool";     puts MiniExiftool.new("test.pdf")["doi"]' 10.1038/nphoton.2008.200

Of course, that could also have been run against an image, audio or video file with XMP packet.

(Makes one wonder vaguely about the feasibility of having a Swiss Army knife type of utility that could read any file to get the DOI using the embedded XMP, RDFa, RDF, HTML headers, COiNS, etc. Possibly even as last resort fall back to scanning the raw text - if any.)

Machine Readable: Are We There Yet?

Tony Hammond — Wed, 19 Nov 2008 00:00:00 +0000

The guidelines for Crossref publishers (“DOI Name Information and Guidelines” - [PDF, 210K][1]) has this to say in “Sect. 6.3 The response page” regarding the response page for a DOI:

“A minimal response page must contain a full bibliographic citation displayed to the user. A response page without bibliographic information should never be presented to a user.”

which would seem to be all fine and dandy. But if that user is a machine (or an agent acting for a user) they’ll likely be out of luck as the metadata in the bibliographic citation is generally targeted at human users.

So here’s a quick and dirty implementation of what a machine readable page could look like using RDFa. (The demo uses Jeni Tennison’s wonderful [rdfQuery][2] plugin which I [blogged][3] about earlier.)

Clicking the DOI link below will bring up in a sub-window a bibliographic citation which might be found in a typical DOI repsonse page. If you now click the “Read Me” link you should see an alert message which presents the bibliographic metadata as a complete RDF document (in a simple N3 – or Notation3 – format). This document is assembled on the fly by rdfQuery using the RDFa markup embedded in the page.

See the “View Source” link to list the actual XHTML markup and the RDFa properties which have been added. And note also that some of the properties are partially “hidden” to the human reader, e.g. a publication date is given in year form only whereas the machine record has the date in full, and some of the properties are fully “hidden”: print and electronic ISSNs, issue number, ending page, etc.

(Continues below.)

So, what’s new about this? There are already various means of adding metadata to pages using e.g. metadata tags (see [here][4] for an earlier post on this), or COinS objects, or even RDF/XML in comment sections. All of these have their various utilities but are still just early attempts at automation. What makes this new and compelling is that RDFa allows publishers to embed machine readable metadata that can be read as a complete machine description in RDF using pretty much off-the-shelf tools and that this markup is embedded unobtrusively into the content in the proper context.

Note that there are some similarities here between embedding an XMP packet (which includes metadata) into an arbitrary binary object, e.g. a PDF file, and embedding RDF into a section of a web page – or perhaps “draping” the RDF over the document markup would be a better term – so that the metadata travels along with the actual content.

By the way, the RDFa can be processed to yield valid RDF (as is shown in the demo) and which can also be seen by running the web page through the [RDFa Distiller][5]. (You just need to cut and paste the link of the demo page given above into the Distiller form box.) This will produce RDF in various serializations (N3, XML, Triples) from the RDFa.

So, is there really any longer any reason not to have machine readable metadata at the end of the DOI? Are we there yet?

[1]: Crossref DOI display guidelines [2]: http://code.google.com/p/rdfquery/wiki/RdfPlugin [3]: /blog/rdfquery [4]: /blog/natures-metadata-for-web-pages [5]: http://www.w3.org/2007/08/pyRdfa/

rdfQuery

Tony Hammond — Mon, 17 Nov 2008 00:00:00 +0000

Whaddya know? I was just on the point of blogging about the real nice demo given by Jeni Tennison at last week’s SWIG UK meeting at HP Labs in Bristol of rdfQuery (an RDF plugin for jQuery - the zip file is here). And there today on her blog I see that she has a full writeup on rdfQuery, so I’ll defer to the expert. :~)

All I can really add to that is that rdfQuery is a pretty darn cool way to add and manipulate RDFa using jQuery. Does it get any better?

And now that RDFa is a W3C Rec since last month (see Primer and Syntax) it will be interesting to see how Crossref members might begin to deploy it on their pages - especially on DOI landing pages.

PRISM 2.1

Tony Hammond — Fri, 24 Oct 2008 00:00:00 +0000

Yesterday a new PRISM spec (v2.1) was released for public comment. (Comment period lasts up to Dec. 3, ’08.)

Changes are listed in pages 8 and 9 of the Introduction document. Some highlights:

New PRISM Usage Rights namespace
- Accordingly usage of prism:copyright, prism:embargoDate, and prism:expirationDate no longer recommended
  - New element prism:isbn introduced for book serials
  An updated mod_prism RSS 1.0 module is available which lists all versions of PRISM specs including the forthcoming v2.1 spec. I will see about getting this added now to a more permanent location. Current version of PRISM remains at v2.0. Versions 2.0 and 2.1 are especially of interest to users of Crossref because of their support for prism:doi and prism:url and users should consider upgrading their applications, e.g. RSS feeds.

Metadata Matters

Tony Hammond — Mon, 21 Jul 2008 00:00:00 +0000

Andy Powell has published on Slideshare this talk about metadata - see his eFoundations post for notes. It’s 130 slides long and aims

“to cover a broad sweep of history from library cataloguing, thru the Dublin Core, Web search engines, IEEE LOM, the Semantic Web, arXiv, institutional repositories and more.”

Don’t be fooled by the length though. This is a flip through and is a readily accessible overview on the importance of metadata. Slides 86-91 might be of interest here. 😉

PRISM Press Release

Tony Hammond — Wed, 09 Jul 2008 00:00:00 +0000

The PRISM metadata standards group issued a press release yesterday which covered three points:

PRISM Cookbook

The Cookbook provides “a set of practical implementation steps for a chosen set of use cases and provides insights into more sophisticated PRISM capabilities. While PRISM has 3 profiles, the cookbook only addresses the most commonly used profile #1, the well-formed XML profile. All recipes begin with a basic description of the business purpose it fulfills, followed by ingredients (typically a set of PRISM metadata fields or elements), and, closes with a step-by-step implementation method with sample XMLs and illustrative images.”

PRISM 2.0 Errata

The Errata “addresses a range of issues, from editorial to technical, that have been reported by the PRISM user community.”

PRISM 2.1: The next version of the PRISM Specification, PRISM 2.1, is slated for release in late 2008. “This release will address complex rights for multi-platform and global distribution channels.”

Exposing Public Data: Options

Tony Hammond — Tue, 01 Jul 2008 00:00:00 +0000

This is a follow-on to an earlier post which set out the lie of the land as regards DOI services and data for DOIs registered with Crossref. That post differentiated between a native DOI resolution through a public DOI service which acts upon the “associated values held in the DOI resolution record” (per ISO CD 26324) and other related DOI protected and/or private services which merely use the DOI as a key into non-public database offering.

Following the service architecture outlined in that post, options for exposing public data appear as follows:

Private Service
1. Publisher hosted – Publisher private service
Protected Service
1. Crossref hosted – Industry protected service
2. Crossref routed – Publisher private service
Public Service
1. Handle System (DOI handle) – Global public service (native DOI service)
2. Handle System (DOI ‘buddy’ handle) – Publisher public service

(Continues below.)

<p>

Option #1 would make public data available through a private service at a publisher host based on the DOI. This places certain constraints on service discovery and persistence. Autodiscovery links can be placed into Web pages, but there is no opportunity to ‘embed’ the services into the DOI itself, and hence these cannot be considered native DOI services. Without a published API (and hence some degree of commitment from the publisher) the service access points (and possibly the services, too) are fragile.
Option #2 would require Crossref to develop a service which would either a) deliver some public data on behalf of the publisher, or b) route requests through to a bespoke publisher service. Both options would require development at Crossref and an upload mechanism for the publisher to pass along data or service address. Both options would be offered as a new member service and would thus likely be subject to membership policy arrangements. One should consider that there would be some restrictions on service operation. One possible restriction might be that this would be a one-time service registration at Crossref and that any additional services would need to be added at the publisher end.
Option #3 uses the existing Handle System infrastructure and provides a public read service. There are two possibilities: a) add a record (or records) to the DOI handle, or b) add records to a DOI ‘buddy’ handle under publisher control. Both require further explanation:
Option #3a would require Crossref consent. Unless these records (handle values) were registered by Crossref there would be concerns over interoperability. That and security concerns would almost certainly require that Crossref writes the record. But this would then need to be developed as per Option #2 above. And if a mechanism were put in place it could be restrictive in practice, e.g. not allowing additional records to be inserted (as already noted in Option #2).
Option #3b requires no prior Crossref consent. It is an option available to publishers who run a handle server. This can best be viewed as deploying a platform (a DOI ‘buddy’ handle) for hosting service access points with an intention to upload into the DOI handle (effectively Option #3a) as common public services are developed. In short, a public service incubator. Meantime the platform provides for an independent deployment and multiple services can be added as required. An uplink from a so-called DOI ‘buddy’ handle to the DOI handle would be maintained, and also as Crossref allows a down link from the DOI handle to the DOI ‘buddy’ handle (a ‘see also’ type link) could be established thus pairing off these two handles. (Of course, additional values whether held in the DOI resolution record or especially in an associated DOI ‘buddy’ record would be subject to common typing constraints for semantic interoperability.)
My personal feeling is that public data is best exposed via a public resolution record with no strings attached. That is the surest way to guarantee both data persistence and accessibility.

Metadata Reuse Policies

Tony Hammond — Tue, 20 May 2008 00:00:00 +0000

Following on from yesterday’s post about making metadata available on our Web pages, I wanted to ask here about “metadata reuse policies”. Does anybody have a clue as to what might constitute a best practice in this area? I’m specifically interested in license terms, rather than how those terms would be encoded or carried. Increasingly we are finding more channels to distribute metadata (RSS, HTML, OAI-PMH, etc.) but don’t yet have any clear statement for our customers as to how they might reuse that data.

Time to put the caveats aside and focus on the actuals.

Nature’s Metadata for Web Pages

Tony Hammond — Mon, 19 May 2008 00:00:00 +0000

Well, we may not be the first but wanted anyway to report that Nature has now embedded metadata (HTML meta tags) into all its newly published pages including full text, abstracts and landing pages (all bar four titles which are currently being worked on). Metadata coverage extends back through the Nature archives (and depth of coverage varies depending on title). This conforms to the W3C’s Guideline 13.2 in the Web Content Accessibility Guidelines 1.0 which exhorts content publishers to “provide metadata to add semantic information to pages and sites”.

Metadata is provided in both DC and PRISM formats as well as in Google’s own bespoke metadata format. This generally follows the DCMI recommendation “Expressing Dublin Core metadata using HTML/XHTML meta and link elements, and the earlier RFC 2731 “Encoding Dublin Core Metadata in HTML”. (Note that schema name is normalized to lowercase.) Some notes:

The DOI is included in the “dc.identifier” term in URI form which is the Crossref recommendation for citing DOI.
- We could consider adding also “prism.doi” for disclosing the native DOI form. This requires the PRISM namespace declaration to be bumped to v2.0. We might consider synchronizing this change with our RSS feeds which are currently pegged at v1.2, although note that the RSS module mod_prism currently applies only to PRISM v1.2.
  - We could then also add in a “prism.url” term to link back (through the DOI proxy server) to the content site. The namespace issue listed above still holds.
    - The “citation_” terms are not anchored in any published namespace which does make this term set problematic in application reuse. It would be useful to be able to reference a namespace (e.g. “rel="schema.gs" href="..."“) for these terms and to cite them as e.g. “gs.citation_title“.
    The HTML metadata sets from an example landing page are presented below.

If you view the page source you should see something like the text below. (Note that you may have to scroll past whitespace which is emitted by the HTML template generator.)

 <pre>&lt;link title="schema(DC)" rel="schema.dc" href="http://purl.org/dc/elements/1.1/" /&gt;

 While it is not expected that search engines will index these terms directly and that no direct SEO is intended, we think there is enough value for applications to make use of these terms. The terms are reasonably accessible to simple scripts, etc. Note that even in [RFC 2731][4] (published in 1999) there is a Perl script listed in Section 9 which allows the metadata name/value pairs to be easily pulled out. Running this over the example page yields the following output:
<pre>@(urc;

@|MISSING ELEMENT NAME; text/css @|MISSING ELEMENT NAME; text/html; charset=iso-8859-1 @|robots; noarchive @|keywords; Nature, science, science news, biology, physics, genetics, astronomy, astrophysics, quantum physics, evolution, evolutionary biology, geophysics, climate change, earth science, materials science, interdisciplinary science, science policy, medicine, systems biology, genomics, transcriptomics, palaeobiology, ecology, molecular biology, cancer, immunology, pharmacology, development, developmental biology, structural biology, biochemistry, bioinformatics, computational biology, nanotechnology, proteomics, metabolomics, biotechnology, drug discovery, environmental science, life, marine biology, medical research, neuroscience, neurobiology, functional genomics, molecular interactions, RNA, DNA, cell cycle, signal transduction, cell signalling. @|description; Nature is the international weekly journal of science: a magazine style journal that publishes full-length research papers in all disciplines of science, as well as News and Views, reviews, news, features, commentaries, web focuses and more, covering all branches of science and how science impacts upon all aspects of society and life. @|dc.publisher; Nature Publishing Group @|dc.language; en @|dc.rights; #169; 2008 Nature Publishing Group @|dc.title; Crystal structure of squid rhodopsin @|dc.creator; Midori Murakami @|dc.creator; Tsutomu Kouyama @|dc.identifier; doi:10.1038/nature06925 @|prism.copyright; © 2008 Nature Publishing Group @|prism.rightsAgent; permissions@nature.com @|prism.publicationName; Nature @|prism.issn; 0028-0836 @|prism.eIssn; 1476-4687 @|prism.volume; 453 @|prism.number; 7193 @|prism.startingPage; 363 @|prism.endingPage; 367 @|citation_journal_title; Nature @|citation_publisher; Nature Publishing Group @|citation_authors; Midori Murakami, Tsutomu Kouyama @|citation_title; Crystal structure of squid rhodopsin @|citation_volume; 453 @|citation_issue; 7193 @|citation_firstpage; 363 @|citation_doi; doi:10.1038/nature06925 @)urc;

Word Add-in for Scholarly Authoring and Publishing

Crossref — Wed, 26 Mar 2008 00:00:00 +0000

Last week Pablo Fernicola sent me email announcing that Microsoft have finally released a beta of their Word plugin for marking-up manuscripts with the NLM DTD. I say “finally” because we’ve know this was on the way and have been pretty excited to see it. We once even hoped that MS might be able to show the plug-in at the ALPSP session on the NLM DTD, but we couldn’t quite manage it.

The plugin is targeted at production/editorial staff, but, of course, it will be interesting to see if any of this work can be pushed back to the author. I won’t hold my breath on the latter score, but it will be fun to watch.

One thing I would note is that the NLM DTD can also be used in the humanities and social sciences, so, frankly, I think they should market it more broadly.

Anyway- the plugin can be downloaded from the Microsoft site.

And Pablo has setup a blog where testers can discuss the add-in.

And there is also an entry for the project on the Microsoft Research site (an interesting place to peruse, if you have a moment).

Congatulations to Pablo and his team.

prism:doi

Tony Hammond — Fri, 22 Feb 2008 00:00:00 +0000

The new PRISM spec (v. 2.0) was published this week, see the press release. (Downloads are available here.)

This is a significant development as there is support for XMP profiles, to complement the existing XML and RDF/XML profiles. And, as PRISM is one of the major vocabularies being used by publishers, I would urge you all to go take a look at it and to consider upgrading your applications to using it.

One caveat. There’s a new element <tt>prism:doi</tt> (PRISM Namespace, 4.2.13) which sits alongside another new element <tt>prism:url</tt> (PRISM Namespace, 4.2.55). Unfortunately the <tt>prism:doi</tt> element is shown to take DOI proxy URL as its value - and not the DOI string itself, e.g.

Model #1
<prism:doi rdf:resource=”http://dx.doi.org/10.1030/03054”/>
Model #2
<prism:doi>http://dx.doi.org/10.1030/03054</prism:doi>

This seems to me to just plain wrong. The DOI in itself is not a URL (or URI) - although can, and should, be represented in URI form when used in Web contexts (i.e. pretty much most of the time). As a literal it should be used in its native form as specified in ANSI/NISO Z39.84 - 2005 Syntax for the Digital Object Identifier. This would only satisfy Model #2 above.

To satisfy Model #1 above a URI form for DOI would be required. And this is not the service URI denoted by the proxy. It would either have to be:

Model #1 - Registered URI Form
<prism:doi rdf:resource=”info:doi/10.1030/03054”/> * Model #1 - Unregistered URI Form
<prism:doi rdf:resource=”doi:10.1030/03054”/>

Any comments? Some guidelines from Crossref would be useful - although maybe further discussion is required. It is, of course, a constant bugbear that “doi:” remains an unregistered URI scheme.

Crossref Citation Plugin (for WordPress)

Crossref — Sat, 09 Feb 2008 00:00:00 +0000

OK, after a number of delays due to everything from indexing slowness to router problems, I’m happy to say that the first public beta of our WordPress citation plugin is available for download via SourceForge. A Movable Type version is in the works.

And congratulations to Trey at OpenHelix who became laudably impatient, found the SourceForge entry for the plugin back on February 8th and seems to have been testing it since. He has a nice description of how it works (along with screenshots), so I won’t repeat the effort here.

Having said that, I do include the text of the README after the jump. Please have a look at it before you install, because it might save you some mystification.

Description

A WordPress plugin that allows you to search Crossref metadata using citations or partial citations. When you find the reference that you want, insert the formatted and DOI-linked citation into your blog posting along with supporting COINs metadata. The plugin supports both a long citation format and a short (op. cit.) format.

Warnings, Caveats and Weasel Words

Please note the following about this plugin:

We are releasing this as a test. It is running on R&D equipment in a non-production environment and so it may disappear without warning or perform erratically. If it isn’t working for some reason, come back later and try again. If it seems to be broken for a prolonged period of time, then please report the problem to us via sourceforge.
There is currently a 20 item limit on the number of hits returned per query. This might seem arbitrary and stingy, but please remember- we are not trying to create a fully blown search engine- we’re just trying to create a citation lookup service. Of course, if, after looking at how the service is used, it looks like we need to up this limit, we will.
If you look in the plugin options (or at the code), you will see that the system includes an API key. At the moment we have no restrictions on use of this service, but have included this in case we need to protect the system from abuse.
The bulk of the functionality we have developed is actually at the back-end. This plugin is just a lightweight interface to that back-end. You can examine the guts of the plugin in order to easily figure out how to create similar functionality for your favorite blog platform, wiki, etc. If you do create something, please let us know. We’d love to see what people are building.
We are continuing to experiment with the metadata search function in order to increase its accuracy and flexibility. Again, this might result in seemingly inconsistent behavior. Did we mention that this is a test?
Please note that this API is not meant for bulk harvesting of Crossref metadata. If you need such facilities, then please look at our web site for information about our metadata services.
The data currently behind the plugin is *just* a December 2007 snapshot of our our complete journal article metadata. We have not added books or proceedings yet. We will do so soon and we will start updating the metadata weekly.

We welcome your ideas for tools that we can provide to help researchers. Please, please, please send comments, requests, queries and ideas to us at:

citation-plugin@crossref.org

DC in (X)HTML Meta/Links

Tony Hammond — Tue, 06 Nov 2007 00:00:00 +0000

This message posted out yesterday on the dc-general list (with following extract) may be of interest:

_“Public Comment on encoding specifications for Dublin Core metadata in HTML and XHTML

2007-11-05, Public Comment is being held from 5 November through 3 December 2007 on the DCMI Proposed Recommendation, “Expressing Dublin Core metadata using HTML/XHTML meta and link elements” «http://dublincore.org/documents/2007/11/05/dc-html/» by Pete Johnston and Andy Powell. Interested members of the public are invited to post comments to the DC-ARCHITECTURE mailing list «http://www.jiscmail.ac.uk/lists/dc-architecture.html» , including “[DC-HTML Public Comment]” in the subject line. Depending on comments received, the specification may be finalized after the comment period as a DCMI Recommendation.”

OpenDocument Adds RDF

Tony Hammond — Sun, 14 Oct 2007 00:00:00 +0000

Bruce D’Arcus left a comment here in which he linked to post of his: “OpenDocument’s New Metadata System“. Not everybody reads comments so I’m repeating it here. His post is worth reading on two counts:

He talks about the new metadata functionality for OpenDocument 1.2 which uses generic RDF. As he says:

> _&#8220;Unlike Microsoft’s custom schema support, we provide this through the standard model of RDF. What this means is that implementors can provide a generic metadata API in their applications, based on an open standard, most likely just using off-the-shelf code libraries.&#8221;_
This is great. It means that description is left up to the user rather than being restricted by any vendor limitation. (Ideally we would like to see the same for XMP. But Adobe is unlikely to budge because of the legacy code base and documents. It’s a wonder that Adobe still wants XMP to breathe.)
* He cites a wonderful passage from Rob Weir of IBM (something which I had been considering to blog but too late now) about the changing shape of documents. Can only say, go read [Bruce’s post][2] and then [Rob’s post][3]. But anyway a spoiler here:
> _&#8220;The concept of a document as being a single storage of data that lives in a single place, entire, self-contained and complete is nearing an end. A document is a stream, a thread in space and time, connected to other documents, containing other documents, contained in other documents, in multiple layers of meaning and in multiple dimensions.&#8221;_</ol>
I think the ODF initiative is fantastic and wish that Adobe could follow suit. However, I do still hold out something for XMP. After all, nobody else AFAICT is doing anything remotely similar for multimedia. Where’s the W3C and co. when you really need them? (Oh yeah, [faffing][4] about the new [Semantic Web logo][5]. 😉

Scholarly DC

Tony Hammond — Fri, 05 Oct 2007 00:00:00 +0000

This This was just sent out to the DC-GENERAL mailing list about the new DCMI Community for Scholarly Communications. As Julie Allinson says:

“The aim of the group is to provide a central place for individuals and organisations to exchange information, knowledge and general discussion on issues relating to using Dublin Core for describing items of ‘scholarly communications’, be they research papers, conference presentations, images, data objects. With digital repositories of scholarly materials increasingly being established across the world, this group would like to offer a home for exploring the metadata issues faced.”

There’s also a DC-SCHOLAR mailing list (subscribe here). Not too much there yet, but it may be useful to track - or even to participate. 🙂

Custom Panel for CC

Tony Hammond — Sat, 15 Sep 2007 00:00:00 +0000

Creative Commons now have a custom panel for adding CC licenses using Adobe apps - see here.

Interesting on two counts:

Machine readable licenses
- XMP metadata
But I still think that batch solutions for adding XMP metadata are really required for publishing workflows. And ideally there should be support for adding arbitrary XMP packets if we’re going to have truly rich metadata. I rather fear the constraints that custom panels place upon the publisher.

Last Orders Please!

Tony Hammond — Thu, 13 Sep 2007 00:00:00 +0000

Public comment period on the PRISM 2.0 draft ends Saturday (Sept. 15) ahead of next week’s WG meeting to review feedback and finalize the spec.

(I put in some comments about XMP already. Hope they got that.)

The Second Wave

Tony Hammond — Tue, 11 Sep 2007 00:00:00 +0000

You might have been wondering why I’ve been banging on about XMP here. Why the emphasis on one vendor technology on a blog focussed on an industry linking solution? Well, this post is an attempt to answer that.

Four years ago we at Nature Publishing Group, along with a select few early adopters, started up our RSS news feeds. We chose to use RSS 1.0 as the platform of choice which allowed us to embed a rich metadata term set using multiple schemas - especially Dublin Core and PRISM. We evangelized this much at the time and published documents on XML.com (Jul. ’03) and in D-Lib Magazine (Dec. ’04) as well as speaking about this at various meetings and blogging about it. Since that time many more publishers have come on board and now provide RSS routinely, many of them choosing to enrich their feeds with metadata.

Well, RSS can be seen in hindsight as being the First Wave of projecting a web presence beyond the content platform using standard markup formats. With this embedded metadata a publisher can expand their web footprint and allow users to link back to their content server.

Now, XMP with its potential for embedding metadata in rich media can be seen as a Second Wave. Media assets distributed over the network can now carry along their own metadata and identity which can be leveraged by third-party applications to provide interesting new functionalities and link-back capability. Again a projection of web presence.

(Continues.)

XMP has much in common with RSS 1.0. They are both profiles of RDF/XML. They are both flawed in certain respects because of self-imposed limitations. But they both build on a robust and open data model for the web (RDF) and are reasonably open, at least they are extensible. One (RSS 1.0) was defined in an open process by committee, the other is an open (i.e published) specification provided by a vendor.

From our point of view both specifications are sufficiently advanced to be immediately useful. I’m not sure how one could interact with the further development of either specification. RSS 1.0 is essentially frozen with Atom being posed as a successor technology, although Atom does not conform to the RDF model. (The upshot is that an RSS 1.0 feed can be consumed completely by an RDF-aware application, while an Atom feed would need to be pre-processed before any RDF “goodness” could be gleaned from it.) By contrast, XMP is a vendor-defined technology and alive, if not perhaps kicking. I am unaware of any process to formally contribute to the XMP development apart from shouting from the terraces. None the less, both technologies are usable as is.

It is curious that no consistent packaging (and delivery) of metadata has yet been achieved with HTML, the original web interface. The HTML </tt> and <tt><meta></tt> elements are employed by publishers with various degrees of consistency. There are also RDF islands that can be embedded within HTML comments (as used e.g. by <a href="http://creativecommons.org/" target="_blank">CC licenses</a>). And then there are <a href="https://web.archive.org/web/20090927174724/http://ocoins.info/" target="_blank">COinS</a> objects. But it’s all a bit of a mish-mash to date. Certainly, I don’t recall seeing any guidelines from Crossref as to how machine readable metadata (even markup for the DOI itself) may be embedded within HTML pages, rather than on HTML pages for human readers. This lack of uniform metadata deployment for HTML pages could be something to do with context. With RSS and XMP we are dealing with remote objects, whereas with HTML we are generally accessing this directly on the content server and so have a semantic context. It could be though that metadata delivery from HTML pages will finally be more uniformly available with the further development of standards such as <a href="http://microformats.org/" target="_blank">microformats</a> and especially <a href="http://www.w3.org/2006/07/SWD/RDFa/syntax/" target="_blank">RDFa</a>, <a href="http://www.w3.org/2004/01/rdxh/spec" target="_blank">GRDDL</a>, etc. It is also interesting to note that an XMP packet could just as easily be embedded within the HTML page, and if this technology were to be adopted more widely for embedding in other media assets then why not consider the same technology for ordinary web pages? I can’t help feeling though that XMP has a lot of promise and is very timely. There are only three real obstacles: creating XMP packets, writing them and reading them. To my mind, once one has a good grasp of XMP then creating the packets can be done with common tools. The same, more or less, for reading the packets. I have shown earlier that this is readily achievable. The only major block is writing the packets into media files although there is support for create/write (if patchy) by open source libraries, as well as there being support (perhaps limited) from products for create/write. But, anyway, it’s certainly do-able. </article> <article> <h1>Stop Press</h1> Tony Hammond — Tue, 28 Aug 2007 00:00:00 +0000 Boy, was I ever so wrong! Contrary to what I said in yesterday’s post, the new PRISM 2.0 spec does support XMP value type mappings for its terms. See the table below which lists the PRISM basic vocabulary terms and the XMP value types. Many thanks to Dianne Kennedy and the rest of the PRISM Working Group for having added this support to PRISM 2.0. <table border="1" cellpadding="3"> <tr> <th> Section </th> <pre><code><th> PRISM Term </th> <th> XMP Value Type </th> </code></pre> </tr> <tr> <td> 4.2.1 </td> <pre><code><td> prism:alternateTitle </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.2 </td> <pre><code><td> prism:byteCount </td> <td> Integer </td> </code></pre> </tr> <tr> <td> 4.2.3 </td> <pre><code><td> prism:channel </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.4 </td> <pre><code><td> prism:complianceProfile </td> <td> Choice: “one”, “two”, “three” </td> </code></pre> </tr> <tr> <td> 4.2.5 </td> <pre><code><td> prism:copyright </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.6 </td> <pre><code><td> prism:corporateEntity </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.7 </td> <pre><code><td> prism:coverDate </td> <td> Date </td> </code></pre> </tr> <tr> <td> 4.2.8 </td> <pre><code><td> prism:coverDisplayDate </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.9 </td> <pre><code><td> prism:creationDate </td> <td> Date </td> </code></pre> </tr> <tr> <td> 4.2.10 </td> <pre><code><td> prism:distributor </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.11 </td> <pre><code><td> prism:edition </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.12 </td> <pre><code><td> prism:eIssn </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.13 </td> <pre><code><td> prism:embargoDate </td> <td> bag Date </td> </code></pre> </tr> <tr> <td> 4.2.14 </td> <pre><code><td> prism:endingPage </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.15 </td> <pre><code><td> prism:event </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.16 </td> <pre><code><td> prism:expirationDate </td> <td> bag Date </td> </code></pre> </tr> <tr> <td> 4.2.17 </td> <pre><code><td> prism:hasAlternative </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.18 </td> <pre><code><td> prism:hasCorrection </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.19 </td> <pre><code><td> prism:hasTranslation </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.20 </td> <pre><code><td> prism:industry </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.21 </td> <pre><code><td> prism:isCorrectionOf </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.22 </td> <pre><code><td> prism:issn </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.23 </td> <pre><code><td> prism:issueIdentifier </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.24 </td> <pre><code><td> prism:issueName </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.25 </td> <pre><code><td> prism:isTranslationOf </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.26 </td> <pre><code><td> prism:killDate </td> <td> Date </td> </code></pre> </tr> <tr> <td> 4.2.27 </td> <pre><code><td> prism:location </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.28 </td> <pre><code><td> prism:modificationDate </td> <td> Date </td> </code></pre> </tr> <tr> <td> 4.2.29 </td> <pre><code><td> prism:number </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.30 </td> <pre><code><td> prism:object </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.31 </td> <pre><code><td> prism:origin </td> <td> Choice: “email”, “mobile”, “broadcast”, “web”, “print”, “recordableMedia”, “other” </td> </code></pre> </tr> <tr> <td> 4.2.32 </td> <pre><code><td> prism:organisation </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.33 </td> <pre><code><td> prism:pageRange </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.34 </td> <pre><code><td> prism:person </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.35 </td> <pre><code><td> prism:postDate </td> <td> Date </td> </code></pre> </tr> <tr> <td> 4.2.36. </td> <pre><code><td> prism:publicationDate </td> <td> Date </td> </code></pre> </tr> <tr> <td> 4.2.37 </td> <pre><code><td> prism:publicationName </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.38 </td> <pre><code><td> prism:receptionDate </td> <td> Date </td> </code></pre> </tr> <tr> <td> 4.2.39 </td> <pre><code><td> prism:rightsAgent </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.40 </td> <pre><code><td> prism:section </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.41 </td> <pre><code><td> prism:startingPage </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.42 </td> <pre><code><td> prism:subsection1 </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.43 </td> <pre><code><td> prism:subsection2 </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.44 </td> <pre><code><td> prism:subsection3 </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.45 </td> <pre><code><td> prism:subsection4 </td> <td> bag Text </td> </code></pre> </tr> <tr> <td> 4.2.46 </td> <pre><code><td> prism:teaser </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.47 </td> <pre><code><td> prism:versionIdentifier </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.48 </td> <pre><code><td> prism:volume </td> <td> Text </td> </code></pre> </tr> <tr> <td> 4.2.49 </td> <pre><code><td> prism:wordCount </td> <td> Integer </td> </code></pre> </tr> </table> </article> <article> <h1>ExifTool</h1> Tony Hammond — Mon, 27 Aug 2007 00:00:00 +0000 (Update - 2007.08.28: I inadvertently missed out the term names in the last example of XMP as RDF/N3 with QNames and have now added these in. Also - a biggie - I said that PRISM had no XMP schema defined. This is actually wrong and as I blogged <a href="https://www.crossref.org/blog/stop-press/">here</a> today, the new PRISM 2.0 spec does indeed have a mapping of PRISM terms to XMP value types. Should actually have read the spec instead of just blogging about it earlier <a href="https://www.crossref.org/blog/prism-2.0/">here</a>. :~) Having previously stooped to an extremely crass hack for pulling out a document information dictionary from PDFs (for which no apologies are sufficient but it does often work) I feel I should make some kind of amends and mention the wonderful <a href="http://www.sno.phy.queensu.ca/~phil/exiftool/">ExifTool</a> by Phil Harvey for reading and writing metadata to media files. This is both a Perl library and command-line application (so it’s cross-platform - a Windows .exe and Mac OS .dmg are also provided.) Besides handling EXIF tags in image files this veritable swissknife of metadata inspectors can also read PDFs for the information dictionary and the document XMP packet. And moreover, intriguingly, can dump the raw (document) XMP packet. I’m still experimenting with it. There’s quite a number of features to explore. But some preliminary finds are listed below. Taking one of our standard (metadata poor) PDFs we get this dump: <pre class="">% exiftool nature05428.pdf ExifTool Version Number : 6.95 File Name : nature05428.pdf Directory : . File Size : 367 kB File Modification Date/Time : 2007:07:26 14:01:23 File Type : PDF MIME Type : application/pdf Page Count : 3 Producer : Acrobat Distiller 6.0.1 (Windows) Mod Date : 2006:12:19 15:03:23+08:00 Creation Date : 2006:12:18 16:57:58+08:00 Creator : 3B2 Total Publishing System 7.51n/W Creator Tool : 3B2 Total Publishing System 7.51n/W Modify Date : 2006:12:19 15:03:23+08:00 Create Date : 2006:12:18 16:57:58+08:00 Metadata Date : 2006:12:19 15:03:23+08:00 Document ID : uuid:f598740b-ad11-41c5-a49e-7caffea783f0 Format : application/pdf Title : untitled </pre> By way of comparison, if we take a demo (metadata rich) PDF with added descriptive DC and PRISM metadata terms, we then get this dump: <pre>% exiftool 445037a.pdf ExifTool Version Number : 6.95 File Name : 445037a.pdf Directory : . File Size : 265 kB File Modification Date/Time : 2007:07:26 16:18:17 File Type : PDF MIME Type : application/pdf Page Count : 1 Creator Tool : InDesign: pictwpstops filter 1.0 Metadata Date : 2006:12:22 12:10:07Z Document ID : uuid:4cd39128-2c8e-41c0-9cad-eea2a1fdb64f Identifier : doi:10.1038/445037a Description : doi:10.1038/445037a Source : Nature 445, 37 (2007) Date : 2007:01:04 Format : application/pdf Publisher : Nature Publishing Group Language : en Rights : © 2007 Nature Publishing Group Publication Name : Nature Issn : 0028-0836 E Issn : 1476-4679 Publication Date : 2007-01-04 Copyright : © 2007 Nature Publishing Group Rights Agent : permissions@nature.com Volume : 445 Number : 7123 Starting Page : 37 Ending Page : 37 Section : News and Views Modify Date : 2006:12:22 12:10:07Z Create Date : 2006:12:22 11:46:18Z Title : 4.1 N&V NS NEW.indd Trapped : False Creator : InDesign: pictwpstops filter 1.0 GTS PDFX Version : PDF/X-1:2001 GTS PDFX Conformance : PDF/X-1a:2001 Author : x Producer : Acrobat Distiller 6.0.1 for Macintosh </pre> Note that the DC and PRISM terms are encoded as my earlier examples and do not take account of a) how DC is defined as an XMP schema (i.e. the XMP value types for the seperate terms), or b) how PRISM might (because it isn’t yet) be defined as an XMP schema. Nor are identifier considerations fully taken into account. Nonetheless this gives more than an idea of what things could look like. Now, with ExifTool it is also possible to list out the terms by group, e.g. <pre>% exiftool -g1 445037a.pdf ---- ExifTool ---- ExifTool Version Number : 6.95 ---- File ---- File Name : 445037a.pdf Directory : . File Size : 265 kB File Modification Date/Time : 2007:07:26 16:18:17 File Type : PDF MIME Type : application/pdf ---- PDF ---- Page Count : 1 Modify Date : 2006:12:22 12:10:07Z Create Date : 2006:12:22 11:46:18Z Title : 4.1 N&V NS NEW.indd Trapped : False Creator : InDesign: pictwpstops filter 1.0 GTS PDFX Version : PDF/X-1:2001 GTS PDFX Conformance : PDF/X-1a:2001 Author : x Producer : Acrobat Distiller 6.0.1 for Macintosh ---- XMP-xmp ---- Creator Tool : InDesign: pictwpstops filter 1.0 Metadata Date : 2006:12:22 12:10:07Z ---- XMP-xmpMM ---- Document ID : uuid:4cd39128-2c8e-41c0-9cad-eea2a1fdb64f ---- XMP-dc ---- Identifier : doi:10.1038/445037a Description : doi:10.1038/445037a Source : Nature 445, 37 (2007) Date : 2007:01:04 Format : application/pdf Publisher : Nature Publishing Group Language : en Rights : © 2007 Nature Publishing Group ---- XMP-prism ---- Publication Name : Nature Issn : 0028-0836 E Issn : 1476-4679 Publication Date : 2007-01-04 Copyright : © 2007 Nature Publishing Group Rights Agent : permissions@nature.com Volume : 445 Number : 7123 Starting Page : 37 Ending Page : 37 Section : News and Views </pre> Going back to the first example we can extract the (document) XMP packet as: <pre class="">% exiftool -xmp -b nature05428.pdf <?xpacket begin='' id='W5M0MpCehiHzreSzNTczkc9d' bytes='1753'?> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#' xmlns:iX='http://ns.adobe.com/iX/1.0/'> <rdf:Description about='uuid:3d686cee-18e6-483c-b1c9-e128e9f0d009' xmlns='http://ns.adobe.com/pdf/1.3/' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Producer>Acrobat Distiller 6.0.1 (Windows)</pdf:Producer> <pdf:ModDate>2006-12-19T15:03:23+08:00</pdf:ModDate> <pdf:CreationDate>2006-12-18T16:57:58+08:00</pdf:CreationDate> <pdf:Title>untitled</pdf:Title> <pdf:Creator>3B2 Total Publishing System 7.51n/W</pdf:Creator> </rdf:Description> <rdf:Description about='uuid:3d686cee-18e6-483c-b1c9-e128e9f0d009' xmlns='http://ns.adobe.com/xap/1.0/' xmlns:xap='http://ns.adobe.com/xap/1.0/'> <xap:CreatorTool>3B2 Total Publishing System 7.51n/W</xap:CreatorTool> <xap:ModifyDate>2006-12-19T15:03:23+08:00</xap:ModifyDate> <xap:CreateDate>2006-12-18T16:57:58+08:00</xap:CreateDate> <xap:Format>application/pdf</xap:Format> <xap:Title> <rdf:Alt> <rdf:li xml:lang='x-default'>untitled</rdf:li> </rdf:Alt> </xap:Title> <xap:MetadataDate>2006-12-19T15:03:23+08:00</xap:MetadataDate> </rdf:Description> <rdf:Description about='uuid:3d686cee-18e6-483c-b1c9-e128e9f0d009' xmlns='http://ns.adobe.com/xap/1.0/mm/' xmlns:xapMM='http://ns.adobe.com/xap/1.0/mm/'> <xapMM:DocumentID>uuid:f598740b-ad11-41c5-a49e-7caffea783f0</xapMM:DocumentID> </rdf:Description> <rdf:Description about='uuid:3d686cee-18e6-483c-b1c9-e128e9f0d009' xmlns='http://purl.org/dc/elements/1.1/' xmlns:dc='http://purl.org/dc/elements/1.1/'> <dc:format>application/pdf</dc:format> <dc:title>untitled</dc:title> </rdf:Description> </rdf:RDF> <?xpacket end='r'?>% </pre> Note that this PDF also included XMP packets for illustrations but the tool extracted the main, or document, XMP packet. And now that it’s easier to extract the metadata one can look to do something more interesting. For example, if one has <a href="http://www.w3.org/2000/10/swap/doc/cwm">cwm</a> installed (Tim BL’s Closed World Machine for semweb dabblings - a Python application, so again cross-platform) one can pipe the XMP packet into cwm as RDF/XML, verify it as valid RDF and read out in another format, e.g. RDF/N3. For the above example we can so this as follows. But let me first define a pipeline to extract the XMP, a couple filters to strip out processing instructions (includes the open and close bracketing <?xpacket> XMP PI’s as well as an undocumented - legacy? - <?adobe> Adobe PI), and then fed into cwm as RDF/XML and read out as RDF/N3. (Note that instead of ExifTool to extract the XMP another tool could have been used, e.g. something based on the sample apps shipped with the Adobe XMP SDK, or something bespoke.) <pre>% alias get_n3 exiftool -xmp -b !$ | grep -v "<?" | grep -v xmpmeta | cwm --rdf --n3 </pre> We can then simply request to get the metadata from this PDF in RDF/N3 format: <pre class="">% get_n3 nature05428.pdf #Processed by Id: cwm.py,v 1.164 2004/10/28 17:41:59 timbl Exp # using base file:/Users/tony/Xcode/xmp/dev/ # Notation3 generation by # notation3.py,v 1.166 2004/10/28 17:41:59 timbl Exp # Base was: file:/Users/tony/Xcode/xmp/dev/ @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . <uuid:3d686cee-18e6-483c-b1c9-e128e9f0d009> <http://ns.adobe.com/pdf/1.3/CreationDate> "2006-12-18T16:57:58+08:00"; <http://ns.adobe.com/pdf/1.3/Creator> "3B2 Total Publishing System 7.51n/W"; <http://ns.adobe.com/pdf/1.3/ModDate> "2006-12-19T15:03:23+08:00"; <http://ns.adobe.com/pdf/1.3/Producer> "Acrobat Distiller 6.0.1 (Windows)"; <http://ns.adobe.com/pdf/1.3/Title> "untitled"; <http://ns.adobe.com/xap/1.0/CreateDate> "2006-12-18T16:57:58+08:00"; <http://ns.adobe.com/xap/1.0/CreatorTool> "3B2 Total Publishing System 7.51n/W"; <http://ns.adobe.com/xap/1.0/Format> "application/pdf"; <http://ns.adobe.com/xap/1.0/MetadataDate> "2006-12-19T15:03:23+08:00"; <http://ns.adobe.com/xap/1.0/ModifyDate> "2006-12-19T15:03:23+08:00"; <http://ns.adobe.com/xap/1.0/Title> [ a rdf:Alt; rdf:_1 "untitled"@x-default ]; <http://ns.adobe.com/xap/1.0/mm/DocumentID> "uuid:f598740b-ad11-41c5-a49e-7caffea783f0"; <http://purl.org/dc/elements/1.1/format> "application/pdf"; <http://purl.org/dc/elements/1.1/title> "untitled" . #ENDS </pre> Or writing that out again with QNames for readability (and dropping the UUID as RDF subject as recommended by latest XMP spec) we have: <pre class="">#Processed by Id: cwm.py,v 1.164 2004/10/28 17:41:59 timbl Exp # using base file:/Users/tony/Xcode/xmp/dev/ # Notation3 generation by # notation3.py,v 1.166 2004/10/28 17:41:59 timbl Exp # Base was: file:/Users/tony/Xcode/xmp/dev/ @prefix dc: <http://purl.org/dc/elements/1.1/> . @prefix pdf: <http://ns.adobe.com/pdf/1.3/> . @prefix xmp: <http://ns.adobe.com/xap/1.0/> . @prefix xmpMM: <http://ns.adobe.com/xap/1.0/mm/> . <> pdf:CreationDate "2006-12-18T16:57:58+08:00"; pdf:Creator "3B2 Total Publishing System 7.51n/W"; pdf:ModDate "2006-12-19T15:03:23+08:00"; pdf:Producer "Acrobat Distiller 6.0.1 (Windows)"; pdf:Title "untitled"; xmp:CreateDate "2006-12-18T16:57:58+08:00"; xmp:CreatorTool "3B2 Total Publishing System 7.51n/W"; xmp:Format "application/pdf"; xmp:MetadataDate "2006-12-19T15:03:23+08:00"; xmp:ModifyDate "2006-12-19T15:03:23+08:00"; xmp:Title [ a rdf:Alt; rdf:_1 "untitled"@x-default ]; xmpMM:DocumentID "uuid:f598740b-ad11-41c5-a49e-7caffea783f0"; dc:format "application/pdf"; dc:title "untitled" . #ENDS </pre> Now just imagine that there were something a little more interesting in there. Like a DOI. Like descriptive metadata, perhaps. 🙂 </article> <article> <h1>Weird Scenes Inside the Gold Mine</h1> Tony Hammond — Wed, 22 Aug 2007 00:00:00 +0000 So, following up on my recent posts here on Metadata in PDFs (<a href="https://www.crossref.org/blog/metadata-in-pdf-1.-strategies/">Strategies</a>, <a href="https://www.crossref.org/blog/metadata-in-pdf-2.-use-cases/">Use Cases</a>, <a href="https://www.crossref.org/blog/metadata-in-pdf-3.-deployment/">Deployment</a>), I finally came across PDF/A and PDF/X, two ISO standardized subsets of PDF. the former (<a href="http://www.iso.org/iso/catalogue_detail?csnumber=38920">ISO 19005-1:2005</a>) for archiving and the latter (<a href="http://www.iso.org/iso/catalogue_detail?csnumber=34607">ISO 15929:2002</a>, <a href="http://www.iso.org/iso/catalogue_detail?csnumber=29061">ISO 15930-1:2001</a>, etc.) for prepress digital data exchange. Both formats share some common ground such as minimizing surprises between producer and consumer and keeping things open and predictable. But my interest here is specifically in metadata and to see what guidance these standards might provide us. Not unsurprisingly, metadata is a key issue for PDF/A, less so for PDF/X. I’ll discuss PDF/X briefly but the bulk of this post is focussed on PDF/A. See below. PDF/X The main reference I am using here is the “Application Notes for PDF/X Standards” cited below [PDF/X 2]. There are two key sections which deal with metadata in PDF/X: “2.3 Identification and conformance”, and “2.20 Document identification and metadata”. Section 2.3 states that a conforming PDF/X file has the key “<tt>/GTS_PDFXVersion</tt>” in the document information dictionary, and (depending on version) may or may not have the key “<tt>/GTS_PDFXConformance</tt>“. Section 2.20 then talks about inclusion of a document ID within the document trailer to ensure correct identification of the file. It then goes on specifically to say: <blockquote> “Additionally, the use of the PDF version 1.4 Metadata key is allowed. Note that although information placed using this mechanism may be beneficial to production processes, any reader that is not PDF version 1.4 compliant may ignore this information.” </blockquote> That is, PDF/X requires the use of a document information dictionary with the key “<tt>/GTS_PDFXVersion</tt>” (and as version demands also the key “<tt>/GTS_PDFXConformance</tt>“) to signal conformance. It is lukewarm, though with regard to the inclusion of XMP metadata (as would be indicated by the “<tt>/Metadata</tt>” key in the document catalog). PDF/A The main reference I’m using here is the “ISO DIS 19005-1:2005” draft cited below [PDF/A, 1]. Completely differently from PDF/X, PDF/A puts all its attention on the XMP metadata, while at the same time acknowledging that the document information dictionary may be used. Note 1 in Section 6.7.3 notes that: <blockquote> “Since a document information dictionary is allowed within a conforming file, it is possible for a single file to be both PDF/A-1 and PDF/X [12, 13] conformant.” </blockquote> The non-normative Annex B also has this to say: <blockquote> “Use of non-XMP metadata at the file level is strongly discouraged as there is no assurance that such metadata can be preserved in accordance with this specification. In cases where non-XMP metadata is present, the preference is to convert it to XMP, embed it in the file, and describe the conversion in the xmpMM:History property.” </blockquote> It’s not fully clear here whether “file level” is intended to be the same as “document level”. But note that this anyway is from a non-normative section and does not reflect the actual normative wording used in the standard (Section 6.7.3) which allows the use of the document information dictionary. The key section for our purposes in the standard is “6.7 Metadata”. Section “6.7.2 Properties” says: <blockquote> “The document catalog dictionary of a conforming file shall contain the Metadata key. The metadata stream that forms the value of that key shall conform to XMP Specification. All metadata properties pertaining to a file that are embedded in that file, except for document information dictionary entries that have no analogue in predefined XMP schemas as defined in 6.7.3, shall be in the form of one or more XMP packets as defined by XMP Specification, 3. Metadata properties shall be specified in predefined XMP schemas or in one or more extension schemas that comply with XMP requirements. Metadata object stream dictionaries shall not contain the Filter key.” </blockquote> This is quite something. Not only is PDF/A fully supportive of XMP (even if Adobe sometimes appear to be less than enthusiastic) it actually requires it. Further it says that the XMP packets shall be human readable (well, apart from the small matter of XML, that is :). Section “6.7.3 Document information dictionary” then goes on to say: <blockquote> “A document information dictionary may appear within a conforming file. If it does appear, then all of its entries that have analogous properties in predefined XMP schemas, as defined by Table 1, shall also be embedded in the file in XMP form with equivalent values. Any document information dictionary entry not listed in Table 1 shall not be embedded using a predefined XMP schema property.” </blockquote> This says that the primary source of metadata will be the XMP packet and that, as far as possible, metadata properties in the document information dictionary will be mapped directly to the XMP packet as specified and will not cause any conflict. I’m not quite sure how to read the last sentence. Does that mean that is one were to use an “<tt>/Identifier</tt>” key in the document information dictionary then one couldn’t map it as “<tt>dc:identifier</tt>“, say, in the XMP. I think that would be OK. My read is that it precludes the use of a predefined term within the information dictionary, so one couldn’t have something like “<tt>dc:identifier</tt>” in the information dictionary. Note also that the one quirky mapping in Table 1 which arises from the need to sync the information dictionary entries with the XMP properties is this: <blockquote> “If the dc:creator property is present in XMP metadata then it shall be represented by an ordered Text array of length one whose single entry shall consist of one or more names. The value of dc:creator and the document information dictionary Author entry shall be equivalent.” </blockquote> This means that: <blockquote> “The document information dictionary entry: <pre>/Author (Peter, Paul, and Mary)</pre> </blockquote> <blockquote> is equivalent to the XMP property: <pre><dc:creator> </blockquote> <rdf:Seq> <rdf.:li>Peter, Paul, and Mary</rdf:li> </rdf:Seq> </dc:creator> </pre> <blockquote> “ </blockquote> Weird, or what? Well, of course, I see the rationale, but … The remaining sections of interest here are “6.7.6 File identifiers” which says that: <blockquote> “A conforming file should have one or more metadata properties to characterize, categorize, and otherwise identify the file. This part of ISO 19005 does not mandate any specific identification scheme. Identifiers may be externally based, such as an International Standard Book Number (ISBN) or a Digital Object Identifier (DOI), or internally based, such as a Globally Unique Identifier/Universally Unique Identifier (GUID/UUID) or another designation assigned during workflow operations.” </blockquote> Hmm, not that DOI is a file identifier necessarily. And certainly not in the Crossref usage where is denotes a work rather than a manifestation. Section “6.7.8 Extension schemas” talks about the need to rigorously declare any extension (undefined) schema with the following PDF/A extension schema description schema properties: <ul> <li> pdfaSchema:schema </li> <li> pdfaSchema:namespaceURI </li> <li> pdfaSchema:prefix </li> <li> pdfaSchema:property </li> <li> pdfaSchema:valueTypeI think this means that were PRISM terms to be used the extension schema terms would need to be defined. And finally, the section “6.7.11 Version and conformance level identification” says that: <blockquote> “The PDF/A version and conformance level of a file shall be specified using the PDF/A Identification extension schema defined in this clause.” </blockquote> This uses the PDF/A identification schema properties: <ul> <li>pdfaid:part</li> </ul> </li> <li> pdfaid:amd </li> <li> pdfaid:conformanceSummary What does this all mean? Main lessons are to be learned from PDF/A which endorses (well, actually mandates) the use of XMP. Moreover, it requires that the document information dictionary and the XMP packet be in sync. Why it signals conformance through the XMP packet rather than through the information dictionary (as does PDF/X) is a mystery. Or at least not specify a means to also signal conformance through the information dictionary. The latter is readily get-at-able. A very crude hack to extract a PDF information dictionary can be as simple as <pre>% strings <filename.pdf> | grep "/Producer" </li> </ul> </pre> <pre><code>or some other likely key. That will usually pull a line containing the full dictionary. The XMP packet is much harder to extract and then you’re still left with XML to parse. My gut feeling is that both mechanisms should be required (and sync’ed). And it’s hard not to see the DOI being required in both sections. Leads to considerations on which schemas/terms to use and how to render the DOI. I am biased and would prefer to see it rendered in URI form, i.e. in an inclusive rather than an exclusive representation. DOI is special - but not that special. Other identifiers are also useful. As per my <a href="/blog/metadata-in-pdf-1.-strategies/">earlier post</a>, I could imagine that both DC and PRISM terms could be added to an XMP packet. I’m not sure whether there is any real interest at this time to follow the PDF/A specification or rather to be informed by it. There seems to be a lot of overhead and I’m still looking to meet up with some examples (either in the wild or fabricated) to see what it might look like in practice. Interested as always in others’ views. References So, note that these are ISO documents and as such are available for purchase from the <a href="https://web.archive.org/web/20070614003151/http://www.iso.org/iso/en/prods-services/ISOstore/store.html">ISO Store</a>. (The citations above are linked to the relevant ISO Store pages.) See also this recent post (August 1, 2007) by Rick Jelliffe on XML.com: <a href="http://www.oreillynet.com/xml/blog/2007/08/where_to_get_iso_standards_on.html">Where to get ISO Standards on the Internet free</a>. There appear to be three main sources of information for these technologies: the ISO standards, application notes and FAQs. NPES (The Association for Suppliers of Printing, Publishing and Converting Technologies) hosts pages with relevant links - see <a href="https://web.archive.org/web/20050504132522/http://www.npes.org/standards/">here</a>. Below are listed specific links to freely available documentation that may be useful. Note that I have not purchased the ISO standards but have made use of an ISO DIS (draft international standard) for PDF/A and Application Notes for PDF/X by CGATS. (As yet there are no links to Application Notes for PDF/A.) <a href="http://www.npes.org/standards/toolspdfx.html">PDF/X</a> 1. (No Draft International Standard found.) </code></pre> <ul> <li><a href="">Application Notes for PDF/X Standards Version 3</a>, September 2002, CGATS Application Notes for PDF/X Standards Version 4 (PDF/X-1a:2003, PDF/X-2:2003 & PDF/X-3:2003)</a>, September 2006 , CGATS</li> <li><a href="http://www.npes.org/LinkClick.aspx?fileticket=qStx8zxAyHA%3d&tabid=158&mid=669">Frequently Asked Questions</a>, November 2005, Martin Bailey, Chair, ISO/TC130/WG2/TF2 (PDF/X)<a href="http://www.npes.org/standards/toolspdfa.html">PDF/A</a> <ol> <li><a href="https://web.archive.org/web/20060426194815/http://www.archivists.org.au/pubs/ISO_DIS_19005-1.pdf">Draft International Standard ISO/DIS 19005-1</a>, ISO/TC171/SC2, Document management— Electronic document file format for long-term preservation — Part 1: Use of PDF 1.4 (PDF/A-1)</li> </ol> </li> <li>(No Application Notes for PDF/A available yet.)</li> <li><a href="https://web.archive.org/web/20070107093446/http://www.npes.org/standards/Tools/19005-1_FAQ.pdf">Frequently Asked Questions (FAQs), ISO 19005-1:2005, PDF/A-1</a>, July 2006, PDF/A Joint Working Group </li> </ul> </article> <article> <h1>Metadata in PDF: 3. Deployment</h1> Tony Hammond — Thu, 02 Aug 2007 00:00:00 +0000 So, assuming we know the form of the metadata we wish to add to our PDFs (or else to comply with if there is already a set of guidelines, or some industry initiative in effect) how can we realize this? And, on the flip side, how can we make it easier for consumers to extract metadata we have embedded in our PDFs. Below are some considerations on deploying metadata in PDFs and consumer access. Write New Obviously the best option would be to speak to one’s suppliers and to get metadata added to the PDF at create time. This leads to questions such as: <ul> <li>What metadata do we have available in the workflow process? Do we have the full set we wish to write, or just a subset? <ul> <li>Do we include metadata in the document information dictionary, or in the document metadata stream, or both? <ul> <li> OK, so we’ve decided to (also) include an XMP packet. So, now do we make that XMP packet read only or write? That is, do we allow the possibility of further edits by adding in trailing whitespace and marking it as “write”? </ul> Write Update What possibilities exist for updating legacy PDF archives? The cleanest means of updating a PDF is in-place edits. This maintains the number of PDF objects together with their lengths and byte offests. Specifically we are interested in metadata objects. There isn’t too much one can do with the document information dictionary apart from overwriting a field value or substituting a field. This is something that may be possible on a “one off” basis only. On the other hand, XMP packets are ripe for updating if they are set in “write” mode and have trailing whitespace. This can be used to supplement the metadata already contained in the packet. There is some “wiggle” room, however, even in read-only XMP packets which have no trailing whitespace. Some XMP packets may include unused default namespace declarations and/or empty elements. These could be safely stripped and used for more positive purposes. This may not be enough to write in a full metadata set, but could be enough to squeeze in the DOI. The usual way to update a PDF file is to append new objects. This means that a replacement document information dictionary and (document) metadata stream can be provided without worrying about shoe-horning the data into any leftover space in the original objects. And this would be just fine, but for the small matter of Linerarized PDFs. These are widely deployed as web friendly PDFs ready for byte serving and are written out in a strictly determined ordering. (See Appendix F, “Linearized PDF” in the <a href="http://www.adobe.com/devnet/pdf/pdf_reference.html" target="_blank">PDF Reference Manual</a>.) The manual does, however, say (Section F.4.6, “Accessing an Updated File”) this about updating a Linearized PDF: <blockquote> _“As stated earlier, if a Linearized PDF file subsequently has an incremental update appended to it, the linearization and hints are no longer valid. Actually, this is not necessarily true, but the viewer application must do some additional work to validate </blockquote> <blockquote> the information. … For a PDF file that has received only a small update, this approach may be worthwhile. Accessing the file this way is quicker than accessing it without hints or retrieving the entire file before displaying any of it.”</blockquote> This may warrant some further investigation. </blockquote> <blockquote> Read </blockquote> <blockquote> Now for consumers, how can publishers help users to read the metadata embedded in a file? The document information dictionary is reasobaly accessible and is in the clear. It probably would not provide for much in terms of metadata but should anyway hopefully contain the DOI. </blockquote> <blockquote> The XMP SDK is still far too unwieldy for wide use. Things would be much improved if there were even some <a href="http://www.swig.org/" target="_blank">SWIG wrappers</a> for more popular languages such as Perl, Python, Ruby, etc. around the C++ code. The other thing to bear in mind is that the XMP SDK is dealing with generalities such as constructing and parsing XMP objects for reading and updating in a range of binary files. A consumer metadata app would only be interested in extracting the RDF/XML from the PDF. This can then be dealt with as appropriate to the application. Another problem concerns multiple XMP packets occurring in the same PDF, only one of them being the main (or document) XMP packet. This may be a non-problem in that all the RDF/XML could be extracted and the main XMP packet would be identifiable through the metadata it provided. </blockquote> <blockquote> I suggest the best way to really help consumers is to go ahead and embed metadata in the first place, then there would be a clear impetus for extracting it. Even if a fuller metadata set is not being considered at this time, then at least the DOI should be considered for embedding in the PDF as a “hook” for further services. The handle plugin is a really good example of just such a downstream application. </blockquote> </li> </ul> </li> </ul> </li> </ul> </article> <article> <h1>PRISM 2.0</h1> Tony Hammond — Thu, 02 Aug 2007 00:00:00 +0000 Only just caught up with this but the PRISM 2.0 draft is now available (since July 12) for public comment. See this posted by Dianne Kennedy: <blockquote> _“Just a note to let you know that PRISM 2.0 has just been posted at <a href="https://web.archive.org/web/20070929195327/http://www.prismstandard.org/" target="_blank">www.prismstandard.org</a> . This is the first major revision to PRISM. We have incorporated new elements to support online content and have expanded and revised our controlled vocabularies. In addition we have added a profile to support PRISM in an XMP environment. We invite you to review the new specification (in 6 documents organized by namespace) and provide your comments before September 15. Please just email comments and questions to me, <a href="mailto:dkennedy@idealliance.org">dkennedy@idealliance.org</a>. “</blockquote> </blockquote> </article> <article> <h1>Metadata in PDF: 1. Strategies</h1> Tony Hammond — Wed, 01 Aug 2007 00:00:00 +0000 Emboldened by my own researches, by the recent handle plugin announcement from CNRI (on which, more in a follow-on post), and by Alexander Griekspoor’s comment to my earlier post, I thought I’d write a more extensive piece about embedding metadata in PDF with a view to the following: <ul> <li>Discover what other publishers are currently doing</li> <li>Stimulate discussions between content providers and/or consumers</li> <li>Lay groundwork for a Crossref best practice guidelines</li> </ul> Why should Crossref be interested? Well, at minimum to embed the DOI along with the digital asset would seem to be inherently “a good thing”. (And, in fact, this is precisely the approach that CNRI have taken for their plugin demos. I’ll look later at what they actually did and consider whether that is a model that Crossref publishers might usefully follow.) Why include the DOI as an explicit piece of metadata rather than have it included by virtue of its appearance in a content section? The main reason is that it is then unambiguously accessible. Content sections in PDFs are typically filtered and sometimes encrypted), whereas metadata is usually plain text and moreover is marked up as to field type. Another question concerns whether to add in the identifier alone, or to embed a full metadata set. Why not just embed the identifier and visit Crossref for the metadata? This is feasible in some cases although it does involve an extra network trip, requires an application to service the identifier and is obviously not workable in offline contexts. Seems like a “no-brainer” to include a fuller description from the outset. Note that publishers frequently make some of this information available anyway in other metadata delivery channels, e.g. RSS feeds. There are two (complementary) approaches to embedding document-level metadata in a PDF: <ul> <li>A - Document Information Dictionary This is an optional object (a dictionary) referenced from the PDF trailer dictionary. Example:</li> </ul> <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-1" data-lang="1"><< /Title ( PostScript Language Reference, Third Edition ) /Author ( Adobe Systems Incorporated ) /Creator ( Adobe FrameMaker 5.5.3 for Power Macintosh® ) /Producer ( Acrobat Distiller 3.01 for Power Macintosh ) /CreationDate ( D:19970915110347-08'00' ) /ModDate ( D:19990209153925-08'00' ) >> endobj </code></pre></div><ul> <li>B - (Document) Metadata Stream This is an optional object (a stream) referenced from the document catalog, itself referenced from the PDF trailer dictionary. Example:</li> </ul> <pre tabindex="0"><code>2 0 obj << /Type /Metadata /Subtype /XML /Length 1706 >> stream <?xpacket begin='' id='W5M0MpCehiHzreSzNTczkc9d'?>  <?xpacket end='w'? > endstream endobj </code></pre>Both approaches usually make the embedded metadata in the PDF available in the clear, whereas content is frequently filtered and sometimes encrypted. (Note that the information dictionary is always in the clear, while the metadata stream can be filtered and rendered unreadable although in practice this tends not to be filtered.) Below I examine both approaches and see how they can be used to encode the kind of metadata that scholarly publishers are accustomed to. A - Document Information Dictionary Note that keys in the document information dictionary divide equally between the logical document description (non-asterisked keys) and the physical asset description (asterisked keys): <pre tabindex="0"><code>Title Author Subject Keywords   * Creator * Producer * CreationDate * ModDate * Trapped </code></pre>This is the complete listing of keys in the PDF specification, although foreign keys are allowed (and ignored). What is missing here is any document identifier and/or any other descriptive metadata. From a Crossref point of view the identifier (the DOI) is a “hook” into the metadata record and so at minimum this could usefully be added. The question then is how? Either the identifier can be squeezed into one of the existing fields (“Title”, “Author”, “Subject”, “Keywords”) or else a new foreign key could be created. IMO if an existing keyword is used then I would opt for “Subject” or “Keywords”, and probably the former. If, on the other hand, a new foreign key were to be created I would choose something generic and (in keeping with the other terms) use something like “Identifier” (rather than, say, “DOI”). Of preference, I think I would go for the latter (“Identifier”) but if one wanted to make this more robust one could think of also adding in a known term (e.g. “Subject” or “Keywords”). So, to include metadata for the news article “Cosmology: Ripples of early starlight” printed in Nature magazine Nature 445, 37 (2007): doi:10.1038/445037a, we might include the following terms in the document information dictionary as: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-1" data-lang="1"><< /Title ( Cosmology: Ripples of early starlight ) /Author ( Craig J. Hogan ) /Subject ( doi:10.1038/445037a ) /Keywords ( cosmology infrared protogalaxy starlight ) /Identifier ( doi:10.1038/445037a ) /Creator ( ... ) /Producer ( ... ) /CreationDate ( ... ) /ModDate ( ... ) >> endobj </code></pre></div>where the bolded term represents a foreign key/value pair. Note: This (including the DOI in the “Subject” field) is a fix intended to get the DOI listed by Adobe apps which would not otherwise recognize the foreign key “Identifier”. Since it is not really feasible to include separate enumerated fields within the information dictionary (although it could be done), one might also consider including a descriptive citation field as a foreign key, e.g., something like: <pre tabindex="0"><code>/Source (Nature 445, 37 $2007$) </code></pre>Aternatively that might better be presented as the “Subject” along with the DOI. Which would then limit the number of foreign keys to one (“Identifier”). B - (Document) Metadata Stream The metadata stream with its use of XMP packets (wrapping RDF/XML instances) is a much more flexible approach to embedding metadata and allows multiple schemas to be used. As noted in my <a href="https://www.crossref.org/blog/xmp-first-hacks/">previous post</a> here on XMP, PDFs with XMP packets mostly use media-specific terms and schemas, although there is also a token showing of DC. From a descriptive metadata point of view we would more likely make use of DC and PRISM for our schemas. Reprising the example from the <a href="https://www.crossref.org/blog/xmp-first-hacks/">previous post</a> (and again using citation example listed above) this would mean we may be inclined to include the following terms for a scholarly work (here in RDF/N3 for readability): <pre tabindex="0"><code class="language-dc:creator" data-lang="dc:creator">dc:title "Cosmology: Ripples of early starlight" ; dc:identifier "doi:10.1038/445037a" ; dc:source "Nature 445, 37 (2007)" ; dc:date "2007-01-04" ; dc:format "application/pdf" ; dc:publisher "Nature Publishing Group" ; dc:language "en" ; dc:rights "© 2007 Nature Publishing Group" ;   prism:publicationName "Nature" ; prism:issn "0028-0836" ; prism:eIssn "1476-4679" ; prism:publicationDate "2007-01-04" ; prism:copyright "© 2007 Nature Publishing Group" ; prism:rightsAgent "permissions@nature.com" ; prism:volume "445" ; prism:number "7123" ; prism:startingPage "37" ; prism:endingPage "37" ; prism:section "News and Views" ; </code></pre>This would look something like the following as an XMP packet within a PDF metadata stream (the RDF now being serialized as RDF/XML): <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-2" data-lang="2"><< /Type /Metadata /Subtype /XML /Length 1706 >> stream <?xpacket begin='' id='W5M0MpCehiHzreSzNTczkc9d'?> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"> <rdf:Description rdf:about="" xmlns:dc=http://purl.org/dc/elements/1.1/> <dc:creator>Craig J. Hogan</dc:creator> <dc:title>Cosmology: Ripples of early starlight</dc:title> <dc:identifier>doi:10.1038/445037a</dc:identifier> <dc:source>Nature 445, 37 (2007)</dc:source> <dc:date>2007-01-04</dc:date> <dc:format>application/pdf</dc:format> <dc:publisher>Nature Publishing Group</dc:publisher> <dc:language>en<dc:language> <dc:rights>© 2007 Nature Publishing Group</dc:rights> </rdf:Description>   <rdf:Description rdf:about="" xmlns:prism=[https://web.archive.org/web/20140228105237/http://prismstandard.org/namespaces/1.2/basic/](https://web.archive.org/web/20140228105237/http://prismstandard.org/namespaces/1.2/basic/)> <prism:publicationName>Nature</prism:publicationName> <prism:issn>0028-0836</prism:issn> <prism:eIssn>1476-4679</prism:eIssn> <prism:publicationDate>2007-01-04</prism:publicationDate> <prism:copyright>© 2007 Nature Publishing Group</prism:copyright> <prism:rightsAgent>permissions@nature.com</prism:rightsAgent> <prism:volume>445</prism:volume> <prism:number>7123</prism:number> <prism:startingPage>37</prism:startingPage> <prism:endingPage>37</prism:endingPage& <prism:section>News and Views</prism:section> </rdf:Description> <?xpacket end='w'?> endstream endobj </code></pre></div>References Some useful references are: <ul> <li> Adobe® Portable Document Format, Version 1.7, November 2006 (see <a href="http://www.adobe.com/devnet/pdf/pdf_reference.html" target="_blank">http://www.adobe.com/devnet/pdf/pdf_reference.html</a>). </li> <li> Adobe® XMP Specification, September 2005 (see <a href="http://partners.adobe.com/public/developer/en/xmp/sdk/XMPspecification.pdf" target="_blank">http://partners.adobe.com/public/developer/en/xmp/sdk/XMPspecification.pdf</a> </li> <li> Embedding XMP Metadata in Application Files, September 2001 (see <a href="http://xml.coverpages.org/XMP-Embedding.pdf" target="_blank">http://xml.coverpages.org/XMP-Embedding.pdf</a> </li> </ul> Note a): See Section 10.2, “Metadata” in Ref. <a href="https://www.crossref.org/blog/xmp-first-hacks/">1</a>. Note b): Ref. [3] is a fairly brief draft which covers both the Information Dictionary and Metadata Dictionary (XMP) approaches. There is an Adobe-hosted update to this document from June 2002 but that only discusses the XMP approach. </article> <article> <h1>Metadata in PDF: 2. Use Cases</h1> Tony Hammond — Wed, 01 Aug 2007 00:00:00 +0000 Well, this is likely to be a fairly brief post as I’m not aware of many use cases of metadata in PDFs from scholarly publishers. Certainly, I can say for Nature that we haven’t done much in this direction yet although are now beginning to look into this. I’ll discuss a couple cases found in the wild but invite comment as to others’ practices. Let me start though with the CNRI handle plugin demo for Acrobat which I blogged <a href="https://www.crossref.org/blog/handle-acrobat-reader-plugin/">here</a>. Handle Plugin First off, the handle plugin PDF samples do include an embedded (test) DOI in both the document information dictionary <pre>5 0 obj << /CreationDate (D:20070614140125-04'00') /Author (Simon) /Creator (PScript5.dll Version 5.2.2) /Producer (Acrobat Distiller 8.1.0 $Windows$) /ModDate (D:20070614140240-04'00') /HDL (10.5555/pdftest-crossref) /Title (Microsoft Word - crossref-rev.doc) >> endobj </pre> and in the (document) metadata stream <pre><rdf:Description rdf:about="" xmlns:pdfx="http://ns.adobe.com/pdfx/1.3/"> <pdfx:HDL>10.5555/pdftest-crossref</pdfx:HDL> </rdf:Description> </pre> Bar any fuller disclosure of metadata terms at large (and one of the demo cases makes use of DOI to retrieve metadata form Crossref) this is excellent. I would, however, quibble with the use of “HDL” as a foreign key for the information dictionary. I realize this is just a test but the term “HDL” (or “DOI”, for that’s what it really is) is somewhat specific and a more general term such as “Identifier” would probably have more mileage, e.g. <pre>5 0 obj << ... /Identifier (doi:10.5555/pdftest-crossref) ... >> endobj </pre> In the second example from the metadata dictionary I don’t think the term “HDL” from the PDF extension schema “pdfx” is very helpful. (Is that namespace actually defined anywhere?) From a descriptive metadata viewpoint a more usual schema such as DC would have wider coverage. So again the second example would be better rendered as <pre><rdf:Description rdf:about="" xmlns:dc="http://purl.org/dc/elements/1.1/"> <dc:identifier>doi:10.5555/pdftest-crossref</dc:identifier> </rdf:Description> </pre> or, alternately, <pre><rdf:Description rdf:about="" xmlns:dc="http://purl.org/dc/elements/1.1/"> <dc:identifier>info:hdl/10.5555/pdftest-crossref</dc:identifier> </rdf:Description> </pre> Elsevier Well, we have Alexander Griekspoor’s <a href="https://www.crossref.org/blog/xmp-first-hacks/">comment earlier</a> that Elsevier are including the DOI in their PDFs. I don’t know how consistently this is being done but I’ve checked a couple sample articles and it would seem that they have embedded the DOI (here from Cancer Cell, doi:0.1016/j.ccr.2007.06.004) in the title element which shows up in the information dictionary as <pre>361 0 obj << /Producer (Adobe LiveCycle PDFG 7.2) /Creator (Elsevier) /Author () /Keywords () /Title (doi:10.1016/j.ccr.2007.06.004) /ModDate (D:20070630031637+05'30') /Subject () /CreationDate (D:00000101000000Z) >> endobj </pre> and in the (document) metadata dictionary as <pre>365 0 obj << /Type /Metadata /Subtype /XML /Length 1526 >> stream <?xpacket begin='' id='W5M0MpCehiHzreSzNTczkc9d' bytes='1526'?> <rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#' xmlns:iX='http://ns.adobe.com/iX/1.0/'> <rdf:Description about='' xmlns='http://ns.adobe.com/pdf/1.3/' xmlns:pdf='http://ns.adobe.com/pdf/1.3/'> <pdf:Producer>Adobe LiveCycle PDFG 7.2</pdf:Producer> <pdf:ModDate>2007-06-30T03:16:37+05:30</pdf:ModDate> <pdf:Title>doi:10.1016/j.ccr.2007.06.004</pdf:Title> <pdf:Creator>Elsevier</pdf:Creator> <pdf:Author></pdf:Author> <pdf:Keywords></pdf:Keywords> <pdf:Subject></pdf:Subject> <pdf:CreationDate>0-01-01T00:00:00Z</pdf:CreationDate> </rdf:Description> <rdf:Description about='' xmlns='http://ns.adobe.com/xap/1.0/' xmlns:xap='http://ns.adobe.com/xap/1.0/'> <xap:CreatorTool>Elsevier</xap:CreatorTool> <xap:ModifyDate>2007-06-30T03:16:37+05:30</xap:ModifyDate> <xap:Title> <rdf:Alt> <rdf:li xml:lang='x-default'>doi:10.1016/j.ccr.2007.06.004</rdf:li> </rdf:Alt> </xap:Title> <xap:Author></xap:Author> <xap:Description> <rdf:Alt> <rdf:li xml:lang='x-default'/> </rdf:Alt> </xap:Description> <xap:CreateDate>0-01-01T00:00:00Z</xap:CreateDate> <xap:MetadataDate>2007-06-30T03:16:37+05:30</xap:MetadataDate> </rdf:Description> <rdf:Description about='' xmlns='http://purl.org/dc/elements/1.1/' xmlns:dc='http://purl.org/dc/elements/1.1/'> <dc:title>doi:10.1016/j.ccr.2007.06.004</dc:title> <dc:creator/> <dc:description/> </rdf:Description> </rdf:RDF> <?xpacket end='r'?> endstream endobj </pre> Kudos anyway to Elsevier for emebedding this piece of information in their PDFs (if indeed it is a general practice). This has the merit of being picked up by Adobe apps and displayed in e.g. Reader. Also third party apps can pull this and use this to retrieve the metadata record from Crossref. The only downside is that technically this seems to be a kludge to satisfy Adobe apps and is not the correct field for filing this information. I would have thought that some other information dictionary field (e.g. “Subject”) would be a better kludge, and then reserve the “Title” and “Author” fields for their proper purposes. The RDF/XML title fields would appear to be inherited from the “Title” field in the information dictionary. It’s a bit of a shame really because the DOI is embedded - it’s just in the wrong place(s). (OK, so that’s still way better, maybe, than not providing this information at all.) Hopefully, with more examples to mull over and experiences to learn from we can arrive at a much better and more systematic way of including the DOI, and other key metadata fields, within a PDF so that this information can be gleaned easily and unambiguously by third party apps. </article> <article> <h1>Handle Acrobat Reader Plugin</h1> Tony Hammond — Tue, 31 Jul 2007 00:00:00 +0000 Just announced on the <a href="http://www.handle.net/mailman/listinfo/handle-info" target="_blank">handle-info</a> list is a new plugin from CNRI for Acrobat Reader - see <a href="http://www.handle.net/hs-tools/adobe/" target="_blank">here</a>. The announcement says: <blockquote> _“It is intended to demonstrate the utility of embedding a identifying </blockquote> <blockquote> handle in a PDF document. </blockquote> <blockquote> </blockquote> <blockquote> … </blockquote> <blockquote> </blockquote> <blockquote> A set of demonstration documents, each with an embedded identifying </blockquote> <blockquote> handle, is packaged with the plug-in to show potential uses. To make </blockquote> <blockquote> productive use of this technology, a given industry or community of </blockquote> <blockquote> users would have to agree on one or more specific applications and </blockquote> <blockquote> populate the relevant handle records accordingly.”_ </blockquote> Two immediate comments: <ul> <li>This is a Windows-only plugin (realized that right after hitting the download button and seeing the ‘.exe’ file) and also needs admin rights to install. (So I solved the first hurdle and am trying to clear the second hurdle. Lockdown is not an uncommon practice for enterprise or institutional computers.) (Update: Actually, I think I got this wrong. I need admin privileges to install Adobe Acrobat 8. Still scuppered, though. Can’t even see the sample PDF files.) <ul> <li>The plugin seems to be aimed at the user rather than at the user agent and thus is necessarily limited in scope, i.e. it needs a human driver. (Ideally content providers would embed metadata within media files using structured markup techniques which would be readily accessible to any downstream app which could leverage this data transparently to provide enhanced user services.) </ul> Anyway, I’ll add something more when I can get it installed. I think this tool could be a useful addition to publishing toolkits but also that content providers could do much more for consumers by disclosing metadata for their digital assets in a neutral, structured form.</li> </ul> </li> </ul> </article> <article> <h1>XMP: First Hacks</h1> Tony Hammond — Fri, 27 Jul 2007 00:00:00 +0000 <code></code>(<code></code>Update - 2007.07.28:<code></code> I meant to reference in this entry Pierre Lindenbaum’s post back in May <code><a href="http://plindenbaum.blogspot.com/2007/05/is-there-any-xmp-in-scientific-pdf-no.html"></code>Is there any XMP in scientific pdf ? (No)<code></a></code>, which btw also references Roderic Page’s post on <code><a href="http://iphylo.blogspot.com/2007/05/xmp.html"></code>XMP<code></a></code> but forgot to add in the links in my haste to scoot off. Well, truth is we still can’t answer Pierre in the affirmative but at least we can take the first steps towards rectifying this.) <code></code>I’ve been revisiting Adobe’s <code><a href="http://www.adobe.com/products/xmp/"></code>XMP<code></a></code> just recently. (I blogged <code><a href="/blog/xmp-capabilities-extended//"></code>here<code></a></code> about the new <code><a href="http://www.adobe.com/devnet/xmp/"></code>XMP Toolkit 4.1<code></a></code> back in March.) <code></code>I wanted to share some of my early experiences. First off, after a couple of previous attempts which got pushed aside due to other projects, I managed to compile the libraries and the sample apps that ship with the C++ SDK under Xcode on the Mac. I also needed to compile <code><a href="https://libexpat.github.io/"></code>Expat<code></a></code> first which doesn’t ship with the distribution. <code></code>OK, so far, so good. What this basically leaves one with is a couple of XMP dump utilities (<code></code>DumpMainXMP<code></code> and <code></code>DumpScannedXMP<code></code>) and two others (<code></code>XMPCoreCoverage<code></code> and <code></code>XMPFilesCoverage<code></code>) which is a good start anyways for exploring. And turns out that our PDFs already have some workflow metadata in them. This is encouraging because the SDK allows apps to read and update existing XMP packets from files, though not to write new packets into files (as far as I understand). <code></code>I thought I would take this opportunity anyway to: <ol> <li><code></code>See what XMP metadata terms we might consider adding</li> </ol> <ul> <li> <code></code>Try and add these to existing XMP packets<code></code>Ugly details are presented below, but by updating the XMP packet metadata in one of our PDFs (<code></code>Nature 445, 37 (2007), C.J. Hogan<code></code>) we can teach Acrobat Reader to read - see the “before” (<code><a href="https://web.archive.org/web/20130815224916/http://nurture.nature.com/"></code>PDF here<code></a></code>) and “after” (<code><a href="https://web.archive.org/web/20130815224916/http://nurture.nature.com/"></code>PDF here<code></a></code>) screenshots in the figure. <code><img src="/wp/blog/images/acrobats.png" alt="acrobats.png" width="583" height="466" /></code> <code></code>Of course, this is really about much more than getting Adobe apps to read/write metadata. It’s about using XMP as a standard platform for embedding metadata in digital assets for <code></code>third-party apps<code></code> to read/write. If we can put ID3 tags into our podcasts then why not XMP packets into other media?<code></code> </li> </ul> <code></code>First a brief digression on XMP packets, which look essentially like this: <pre class=""><?xpacket begin="..." id="..."?> <x:xmpmeta xmlns:x="adobe:ns:meta/"> <rdf:RDF xmlns:rdf="..." xmlns:...> ... </rdf:RDF> </x:xmpmeta> ... XML whitespace as padding ... <?xpacket end="w"?> <rdf:RDF>" element which is optionally wrapped by an "`<tt>`<x:xmpmeta>`</tt>`" element. This XML fragment with trailing XML whitespace is topped and tailed by "`<tt>`<?xpacket>`</tt>`" processing instructions with "`<tt>`begin`</tt>`" and "`<tt>`end`</tt>`" attributes, respectively. The RDF supported is a simple profile of RDF with only certain constructs recognized: scalars, arrays, structures. It is not a means to embed arbitrary RDF/XML structures. But I'll pass on that for now. At first blush it's at least suitable to get a simple dictionary of key/value terms written in, and more besides. The XMP metadata from the `<a href="https://web.archive.org/web/20130815224916/http://nurture.nature.com/">`PDF file`</a>` listed above looks as follows in RDF/N3 (which is a more chipper serialization of RDF than is RDF/XML):`</pre>` <pre><code>`<pre>`<uuid:...> </code></pre> dc:creator “x” ; dc:format “application/pdf” ; dc:title “19.7 N&V.indd NEW.indd”@x-default ; pdf:GTS_PDFXConformance “PDF/X-1a:2001” ; pdf:GTS_PDFXVersion “PDF/X-1:2001” ; pdf:Producer “Acrobat Distiller 6.0.1 for Macintosh” ; pdf:Trapped “False” ; pdfx:GTS_PDFXConformance “PDF/X-1a:2001” ; pdfx:GTS_PDFXVersion “PDF/X-1:2001” ; xap:CreateDate “2007-07-16T09:25:20+01:00” ; xap:CreatorTool “InDesign: pictwpstops filter 1.0” ; xap:MetadataDate “2007-07-16T11:40:21+01:00” ; xap:ModifyDate “2007-07-16T11:40:21+01:00” ; xapMM:DocumentID “uuid:be3a9be5-4e3a-4b66-a50b-26f0a0bfc89d” ; xapMM:InstanceID “uuid:73dcd021-d40a-4cb7-a99b-44f8e90624f4” . <code></pre></code> <pre><code>``(``Note:`` I’ve omitted namespaces here and dropped some of the structuring info that was present on the “`<tt>`dc:creator`</tt>`” and “`<tt>`dc:title`</tt>`” elements thus leaving all values as simple strings. Back to that in a bit. ) ``What this says is simply that all these properies expressed in key/value pairs apply to the current document denoted by the resource identifier “`<tt>`[uuid:...](uuid:...)`</tt>`“, and terms are taken from the schemas indicated by the prefixes. So, for example, the term “`<tt>`creator`</tt>`” from the schema referenced by the placeholder “`<tt>`dc`</tt>`” (there is a namespace URI for this but I haven’t shown it here) has the value “`<tt>`x`</tt>`” for this document, and so on. ``So, salting away the media- and XMP-specific metadata, we are left with the following work metadata in our main XMP packet. `<pre>`<uuid:...> </code></pre> dc:creator “x” ; dc:format “application/pdf” ; dc:title “19.7 N&V.indd NEW.indd”@x-default ; <code></pre></code> <pre><code>``Not wildly impressive, i must admit. Ideally we would like to pump this up with a fuller descriptive and rights metadata set such as we routinely syndicate with our web feeds. This would make use of both DC and PRISM vocabularies. In RDF/N3 we might expect to see something like: `<pre>`<uuid:...> </code></pre> dc:creator “Craig J. Hogan” ; dc:title “Cosmology: Ripples of early starlight” ; dc:identifier “doi:10.1038/445037a” ; dc:description “doi:10.1038/445037a” ; dc:source “Nature 445, 37 (2007)” ; dc:date “2007-01-04” ; dc:format “application/pdf” ; dc:publisher “Nature Publishing Group” ; dc:language “en” ; dc:rights “© 2007 Nature Publishing Group” ; prism:publicationName “Nature” ; prism:issn “0028-0836” ; prism:eIssn “1476-4679” ; prism:publicationDate “2007-01-04” ; prism:copyright “© 2007 Nature Publishing Group” ; prism:rightsAgent “<a href="mailto:permissions@nature.com">permissions@nature.com</a>” ; prism:volume “445” ; prism:number “7123” ; prism:startingPage “37” ; prism:endingPage “37” ; prism:section “News and Views” ; <code></pre></code> <pre><code>``So, taking this RDF and doing a quick and dirty substitution of it for the existing DC description in the PDF XMP packet (i.e. more or less “lobotomizing” the PDF) we then get an updated XMP packet which can be dumped with the ``DumpMainXMP`` utility as (with some schemas removed): `<pre>`// ---------------------------------- </code></pre> // Dumping main XMP for 445037a.pdf : File info : format = " “, handler flags = 00000260 Packet info : offset = 267225, length = 3651 Initial XMP from 445037a.pdf Dumping XMPMeta object "” (0x0) … <a href="http://purl.org/dc/elements/1.1/" target="_blank">http://purl.org/dc/elements/1.1/</a> dc: (0x80000000 : schema) dc:rights (0x1E00 : isLangAlt isAlt isOrdered isArray) [1] = " 2007 Nature Publishing Group" (0x50 : hasLang hasQual) ? xml:lang = “x-default” (0x20 : isQual) dc:language (0x200 : isArray) [1] = “en” dc:publisher (0x200 : isArray) [1] = “Nature Publishing Group” dc:format = “application/pdf” dc:date (0x600 : isOrdered isArray) [1] = “2007-01-04” dc:source = “Nature 445, 37 (2007)” dc:description (0x1E00 : isLangAlt isAlt isOrdered isArray) [1] = “doi:10.1038/445037a” (0x50 : hasLang hasQual) ? xml:lang = “x-default” (0x20 : isQual) dc:identifier = “doi:10.1038/445037a” dc:title (0x1E00 : isLangAlt isAlt isOrdered isArray) [1] = “Cosmology: Ripples of early starlight” (0x50 : hasLang hasQual) ? xml:lang = “x-default” (0x20 : isQual) dc:creator (0x600 : isOrdered isArray) [1] = “Craig J. Hogan” <a href="https://web.archive.org/web/20211021092941/http://prismstandard.org/namespaces/1.2/basic/" target="_blank">https://web.archive.org/web/20211021092941/http://prismstandard.org/namespaces/1.2/basic/</a> prism: (0x80000000 : schema) prism:section = “News and Views” prism:endingPage = “37” prism:startingPage = “37” prism:number = “7123” prism:volume = “445” prism:rightsAgent = “<a href="mailto:permissions@nature.com">permissions@nature.com</a>” prism:copyright = " 2007 Nature Publishing Group" prism:publicationDate = “2007-01-04” prism:eIssn = “1476-4679” prism:issn = “0028-0836” prism:publicationName = “Nature” <code></pre></code> <pre><code>``Full dumps of the “before” and “after” PDFs are available here: *``DumpMainXMP`` - `<a href="https://web.archive.org/web/20080821103510/http://nurture.nature.com/tony/xmp/445037a.xmpp.0">`before`</a>` and `<a href="https://web.archive.org/web/20080821103719/http://nurture.nature.com/tony/xmp/445037a.xmpp.1">`after`</a>` `<pre></pre>` </code></pre> <ul> <li> <code></code>DumpScannedXMP<code></code> - <code><a href="https://web.archive.org/web/20080821103510/http://nurture.nature.com/tony/xmp/445037a.xmpp.0"></code>before<code></a></code> and <code><a href="https://web.archive.org/web/20080821103719/http://nurture.nature.com/tony/xmp/445037a.xmpp.1"></code>after<code></a></code>Note also that in the dump above some of the DC terms are interpreted by the XMP toolkit to have structured formats, i.e. are recognized as array members, and have language and ordering attributes. This seems to be an artefact of the toolkit as the RDF did not specify these structurings. Note also that the PRISM values were not similarly interpreted as the PRISM schema is not registered with the toolkit. <code></code>Obviously, there’s much more to be learned yet. I’ll post an update to this later, but meantime it would be very interesting to get feedback from others on experiences they may have with XMP or any opinions they may want to share. I think it all looks very promising although tools are somewhat restricted. </li> </ul> </article> <article> <h1>IBM Article on PRISM</h1> Tony Hammond — Tue, 10 Jul 2007 00:00:00 +0000 Nice entry article on PRISM <a href="http://www.ibm.com/developerworks/xml/library/x-think13.html" target="_blank">here</a> by Uche Ogbuji, Fourthought Inc. on IBM’s DeveloperWorks. </article> <article> <h1>RSC’s Project Prospect v1.1</h1> rkidd — Thu, 31 May 2007 00:00:00 +0000 We updated our <a href="https://web.archive.org/web/20070401173200/http://www.rsc.org/Publishing/Journals/ProjectProspect/index.asp" target="_blank">Project Prospect</a> articles today to release v1.1, with a pile of look & feel improvements to the HTML views and links. The most interesting technical addition is the launch of our enhanced RSS feeds, where we have updated our <a href="https://pubs.rsc.org/en/EAlerts/RssFeed" target="_blank">existing feeds</a> for enhanced articles. These now include ontology terms and primary compounds both visually (as text terms and 2D images) and within the RDF - using the OBO in OWL representation and the info:inchi specification mentioned here by Tony only a few weeks ago. The enhanced entries will soon become more common as we concentrate our enhancements on our Advance Articles, but the current example below from our <a href="https://pubs.rsc.org/en/ealerts/rssfeed" target="_blank">Photochemical and Photobiological Sciences feed</a> is lovely. RDF code after the jump - just as beautiful to the parents… So the RDF code for the OBO terms and InChIs looks like this: <pre tabindex="0"><code><tt> <rdf:li> <content:item rdf:about="info:inchi/InChI=1/C20H28O/c1-16(8-6-9-17(2)13-15-21)11-12-19-18(3)10-7-14-20(19,4)5/h6,8-9,11-13,15H,7,10,14H2,1-5H3/b9-6-,12-11+,16-8+,17-13+"/> </rdf:li> <rdf:li><content:item rdf:about="http://purl.org/obo/owl/CL#CL:0000210"/> </rdf:li> </tt> </code></pre>We now have over five hundred 2007 articles enhanced, so we’ve brought the majority back into controlled access. There are always <a href="https://web.archive.org/web/20081004073354/http://www.rsc.org/Publishing/Journals/ProjectProspect/Examples.asp" target="_blank">examples</a> from each journal freely available. </article> <article> <h1>XMP Capabilities Extended</h1> Tony Hammond — Thu, 22 Mar 2007 00:00:00 +0000 This <a href="https://web.archive.org/web/20070908031425/http://blogs.adobe.com/creativesolutionspr/2007/03/adobe_extends_xmp_capabilities.html" target="_blank">post</a> on Adobe’s Creative Solutions PR blog may be worth a gander: <blockquote> _“This new update, the Adobe XMP 4.1, provides new libraries for developers to read, write and update XMP in popular image, document and video file formats including: JPEG, PSD, TIFF, AVI, WAV, MPEG, MP3, MOV, INDD, PS, EPS and PNG. In addition, the rewritten XMP 4.1 libraries have been optimized into two major components, the XMP Core and the XMP Files. </blockquote> <blockquote> The XMP Core enables the parsing, manipulating and serializing of XMP data, and the XMP Files enables the reading, rewriting, and injecting serialized XMP into the multiple file formats. The XMP Files can be thought of as a “file I/O” component for reading and writing the metadata that is manipulated by the XMP Core component. </blockquote> <blockquote> Supported development environments for Adobe’s XMP 4.1 are: XCode 2.3 for Macintosh universal binaries, Visual Studio 2005 (VC8) for Windows, and Eclipse 3.x on any available platform. The XMP Core is available as C++ and Java sources with project files for the Macintosh, Windows and Linux platform. A Java version of XMP Files is under consideration for a future update.”_ </blockquote> And now I just read that last sentence again: “A Java version of XMP Files is under consideration for a future update.” So, how hard do they really want to make uptake of XMP be? Am surprised they’re even still considering offering full Java support, and not offering also anything in the way of support for glue languages such as Perl, Python, or Ruby. Which leads to the question: Is anybody here using XMP and had any success to relate or lessons for the rest of us? </article> <article> <h1>Use of PRISM in RSS</h1> Tony Hammond — Tue, 23 Jan 2007 00:00:00 +0000 Was rooting around for some information and stumbled across this page which may be of interest: <a href="http://googlereader.blogspot.com/2006/08/namespaced-extensions-in-feeds.html" target="_blank">http://googlereader.blogspot.com/2006/08/namespaced-extensions-in-feeds.html</a> Namespaced Extensions in Feeds Thursday, August 03, 2006 posted by Mihai Parparita “I wrote a small MapReduce program to go over our BigTable and get the top 50 namespaces based on the number of feeds that use them.”<table border=0 cellpadding="5"> </table> Seems quite an impressive percentage for PRISM. </article> <article> <h1>AdsML</h1> Tony Hammond — Tue, 03 Oct 2006 00:00:00 +0000 A new version of the AdsML Framework 2.0, Release 8 from the <a href="https://web.archive.org/web/20061004090802/http://195.52.248.218/WebSite/adsml.nsf/HTML/Index.html" target="_blank">AdsML Consortium</a> is now available for download from <a href="http://www.adsml.org/2006/announcements/adsml-framework-2-0-release-8-issued/" target="_blank">http://www.adsml.org/2006/announcements/adsml-framework-2-0-release-8-issued/</a>. Below is an extract from the “Vision” document which outlines the broad goals of AdsML. _“2 The Vision of AdsML According to its Charter document, the mission of the AdsML Consortium is 3- fold: • to create an internationally-adopted set of specifications and associated business processes for the electronic exchange of business information and content for advertising • to simplify and accelerate business interactions • to facilitate use across multiple media in both current and future environments. This dry, somewhat technical statement masks the simplicity and power of what the AdsML Consortium aims to do. Stated informally, AdsML’s vision is to tie together all of the parties involved in producing, booking, distributing and publishing an ad as if they all used the same software system – but without actually requiring everyone to switch to a different software system or vendor.”_ </article> </main></body></html>

Metadata on Crossref

Schema 5.5 now available: adding CRediT, new record types for blogs and posters, and more

Why this update is kind of a big deal

What else is included in Schema 5.5?

1. Updates to report series metadata

2. Posted content improvements: now including blogs and posters

3. Expanded archive support

4. Clinical trial metadata across more record types

Schema adoption

New Crossref Service Providers program ready for applications

Scope and goals of the program

Participants of the Service Providers program will commit to:

Service Providers program tiers

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Building better connections: the story of Crossref's metadata development

What We’ve Accomplished

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Two billion citation links in Crossref help research travel further

Why metadata matters for research integrity: a new joint guide from Crossref and DataCite

Strengthening community connections in São Paulo

Português version

Metadata for research integrity: a joint guide from Crossref and DataCite

Why metadata matters for research integrity and jow to contribute

Strategists

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What this guide covers

Read the full guide

Voices from Crossref Metadata Sprint in São Paulo

Projects summary

Voices from the Sprint

Participants

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Metadata available through Crossref

Metadata enrichment layers

Layer 1: Member updates

Layer 2: Community feedback loop

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Layer 4: Third-party datasets

Layer 5: Unstructured content scraping

Summary

2026 public data file now available

Why do we do this?

What’s different this year?

Insights from a roundtable on author affiliation metadata

Insights from presenters

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Inherent data complexity

Author-related issues

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Adopt collective approaches

Engage authors and institutions

Improve the tech

Encourage publisher best practices

Moving forward

References

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The best way of acknowledging research funding in the metadata: Crossref Grant ID

Highlights of a very busy year: our 2025 annual report

Strategic theme 1: Contribute to an environment where the community identifies and co-creates solutions for broad benefit

Enhanced tools and services

Deprecations and modernisation

Eating our own DOI dogfood

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Strategic theme 2: A sustainable source of complete, open, and global scholarly metadata and relationships

Schema developments

Public data file

Inaugural Metadata Awards

Metadata Matching project

Data infrastructure and Research Nexus participation dashboard

Retraction Watch integration

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Strategic theme 3: Manage Crossref openly and sustainably, modernising and making transparent all operations so that we are accountable to the communities that govern us

Infrastructure modernisation

Se pudesse alterar algo no GLS ou na forma como os metadados dos subsídios que regista são utilizados, o que seria?