In the scholarly communications environment, the evolution of a journal article can be traced by the relationships it has with its preprints. Those preprint–journal article relationships are an important component of the research nexus. Some of those relationships are provided by Crossref members (including publishers, universities, research groups, funders, etc.) when they deposit metadata with Crossref, but we know that a significant number of them are missing. To fill this gap, we developed a new automated strategy for discovering relationships between preprints and journal articles and applied it to all the preprints in the Crossref database. We made the resulting dataset, containing both publisher-asserted and automatically discovered relationships, publicly available for anyone to analyse.
The second half of 2023 brought with itself a couple of big life changes for me: not only did I move to the Netherlands from India, I also started a new and exciting job at Crossref as the newest Community Engagement Manager. In this role, I am a part of the Community Engagement and Communications team, and my key responsibility is to engage with the global community of scholarly editors, publishers, and editorial organisations to develop sustained programs that help editors to leverage rich metadata.
STM, DataCite, and Crossref are pleased to announce an updated joint statement on research data.
In 2012, DataCite and STM drafted an initial joint statement on the linkability and citability of research data. With nearly 10 million data citations tracked, thousands of repositories adopting data citation best practices, thousands of journals adopting data policies, data availability statements and establishing persistent links between articles and datasets, and the introduction of data policies by an increasing number of funders, there has been significant progress since.
Have you attended any of our annual meeting sessions this year? Ah, yes – there were many in this conference-style event. I, as many of my colleagues, attended them all because it is so great to connect with our global community, and hear your thoughts on the developments at Crossref, and the stories you share.
Let me offer some highlights from the event and a reflection on some emergent themes of the day.
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)
plain text (.txt)
Portable Document Format (.pdf)
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