https://doi.org/10.13003/axeer1ee
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.
Looking back over 2024, we wanted to reflect on where we are in meeting our goals, and report on the progress and plans that affect you - our community of 21,000 organisational members as well as the vast number of research initiatives and scientific bodies that rely on Crossref metadata.
In this post, we will give an update on our roadmap, including what is completed, underway, and up next, and a bit about what’s paused and why.
The Crossref2024 annual meeting gathered our community for a packed agenda of updates, demos, and lively discussions on advancing our shared goals. The day was filled with insights and energy, from practical demos of Crossref’s latest API features to community reflections on the Research Nexus initiative and the Board elections.
Our Board elections are always the focal point of the Annual Meeting. We want to start reflecting on the day by congratulating our newly elected board members: Katharina Rieck from Austrian Science Fund (FWF), Lisa Schiff from California Digital Library, Aaron Wood from American Psychological Association, and Amanda Ward from Taylor and Francis, who will officially join (and re-join) in January 2025.
Background The Principles of Open Scholarly Infrastructure (POSI) provides a set of guidelines for operating open infrastructure in service to the scholarly community. It sets out 16 points to ensure that the infrastructure on which the scholarly and research communities rely is openly governed, sustainable, and replicable. Each POSI adopter regularly reviews progress, conducts periodic audits, and self-reports how they’re working towards each of the principles.
In 2020, Crossref’s board voted to adopt the Principles of Open Scholarly Infrastructure, and we completed our first self-audit.
To work out which version you’re on, take a look at the website address that you use to access iThenticate. If you go to ithenticate.com then you are using v1. If you use a bespoke URL, https://crossref-[your member ID].turnitin.com/ then you are using v2.
Within a folder, the Documents tab shows all the submitted documents for that folder.
Each document submitted generates a Similarity Report after the document has been through the Similarity Check. If more documents are present than can be displayed at once, the pages feature will appear beneath the documents - click the page number to display, or click Next to move to the next page of documents.
zip file upload - to submit a zip file containing multiple documents, up to a maximum of 100MB or 1,000 files. Larger files may take longer to upload
cut & paste - to submit text directly into the submission box. Use this to copy and paste a submission from a file format that is not supported. This method supports plain text only (no images or non-text information)
iThenticate currently accepts the following file types for document upload:
Microsoft Word® (.doc and .docx)
Word XML
plain text (.txt)
Adobe PostScript®
Portable Document Format (.pdf)
HTML
Corel WordPerfect® (.wpd)
Rich Text Format (.rtf)
Each file may not exceed 400 pages, and each file size may not exceed 100 MB. Reduce the size of larger files by removing non-text content. You can’t upload or submit to iThenticate files that are password-protected, encrypted, hidden, system files, or read-only.
.pdf documents must contain text - if they contain only images of text, they will be rejected during the upload attempt. To check, copy and paste a section of the .pdf into a plain-text editor such as Microsoft Notepad® or Apple TextEdit®. If no text is copied over, the selection does not contain text.
To convert scanned images of a document, or an image saved as a .pdf, use Optical Character Recognition (OCR) software to convert the image to text. The conversion software can introduce errors, so manually check and correct the converted document.
Some document formats can contain multiple data types, such as text, images, embedded information from another file, and formatting. Non-text information that is not saved directly within the document will not be included in a file upload, for example, references to a Microsoft Excel® spreadsheet included within a Microsoft Office Word® document.
Use a word-processing program to save your file as one of the accepted types listed above, such as .rtf or .txt. Neither file type supports images or non-text data within the file. Plain text format does not support any formatting, and rich text format allows only limited formatting.
When converting a file to a new format, save it with a different name from the original, to avoid accidentally overwriting the original file. This is especially important when converting to plain text or rich text formats, to prevent permanent loss of the original formatting or image content of the file.
Page owner: Kathleen Luschek | Last updated 2020-May-19
