In the first half of this year we’ve been talking to our community about post-publication changes and Crossmark. When a piece of research is published it isn’t the end of the journey—it is read, reused, and sometimes modified. That’s why we run Crossmark, as a way to provide notifications of important changes to research made after publication. Readers can see if the resesarch they are looking at has updates by clicking the Crossmark logo.
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.
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.
Update 2024-07-01: This post is based on an interview with Euan Adie, founder and director of Overton._
What is Overton? Overton is a big database of government policy documents, also including sources like intergovernmental organizations, think tanks, and big NGOs and in general anyone who’s trying to influence a government policy maker. What we’re interested in is basically, taking all the good parts of the scholarly record and applying some of that to the policy world.
Some of the typical users (outer) and uses (inner) of Crossref metadata
People using Crossref metadata need it for all sorts of reasons including metaresearch (researchers studying research itself such as through bibliometric analyses), publishing trends (such as finding works from an individual author or reviewer), or incorporation into specific databases (such as for discovery and search or in subject-specific repositories), and many more detailed use cases.
All Crossref metadata is open and available for reuse without restriction. Our
159938194 records include information about research objects like articles, grants and awards, preprints, conference papers, book chapters, datasets, and more. The information covers elements like titles, contributors, descriptions, dates, references, connecting identifiers such as Crossref DOIs, ROR IDs and ORCID iDs, together with all sorts of metadata that helps to determine provenance, trust, and reusability—such as funding, clinical trial, and license information.
Anyone can retrieve and use
159938194 records without restriction. So there are no fees to use the metadata but if you really rely on it then you might like to sign up for Metadata Plus which offers greater predictability, higher rate limits, monthly data dumps in XML and JSON, and access to dedicated support from our team.
Options for retrieving metadata
All Crossref metadata is completely open and available to all. Whatever your experience with metadata, there are several tools, techniques, and support guides to help—whether you’re just beginning, exploring occasionally, or need an ongoing reliable integration.
BEGINNING?
You’ve heard Crossref metadata might be useful and want to know where to start.
You rely on Crossref metadata and need to incorporate it into your product at scale.
You might want to jump straight to subscribing to Metadata Plus, which is our premium service for the REST API that comes with monthly data dumps in JSON and XML, higher rate limits, and fast support. But we always recommend that you try out the public version first to make sure it will work for your product. If you’re looking for a single DOI record in multiple formats (e.g. RDF, BibTex, CSL) you can use content negotiation.
Watch the animated introduction to metadata retrieval