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.
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