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.
Hello, readers! My name is Luis, and I’ve recently started a new role as the Technical Community Manager at Crossref, where I aim to bridge the gap between some of our services and our community awareness to enhance the Research Nexus. I’m excited to share my thoughts with you.
My journey from research to science communications infrastructure has been a gradual transition. As a Masters student in Biological Sciences, I often felt curious about the behind-the-scenes after a paper is submitted and published.
In May, we updated you on the latest changes and improvements to the new version of iThenticate and let you know that a new similarity report and AI writing detection tool were on the horizon.
On Wednesday 1 November 2023, Turnitin (who produce iThenticate) will be releasing a brand new similarity report and a free preview to their AI writing detection tool in iThenticate v2. The AI writing detection tool will be enabled by default and account administrators will be able to switch it off/on.
Following up on his earlier post (which was also blogged to CrossTech here), Leigh Dodds is now [Following up on his earlier post (which was also blogged to CrossTech here), Leigh Dodds is now]3 the possibility of using machine-readable auto-discovery type links for DOIs of the form
These LINK tags are placed in the document HEAD section and could be used by crawlers and agents to recognize the work represented by the current document. This sounds like a great idea and we’d like to hear feedback on it.
Concurrently at Nature we have also been considering how best to mark up in a machine-readable way DOIs appearing within a document page BODY. Current thinking is to do something along the following lines:
which allows the DOI to be presented in the preferred Crossref citation format (doi:10.1038/nprot.2007.43), to be hyperlinked to the handle proxy server (<a href="http://dx.doi.org/10.1038/nprot.2007.43">http://dx.doi.org/10.1038/nprot.2007.43</a>), and to refer to a validly registered URI form for the DOI (info:doi/10.1038/nprot.2007.43). Again, we would be real interested to hear any opinions on this proposal for inline DOI markup as well as on Leigh’s proposal for document-level DOI markup.
(Oh, and btw many congrats to Leigh on his recent promotion to CTO, Ingenta.)