Tim Clark's blog

Just Published - Basic Guidelines for Accesssible Data Citations

We are excited that our paper, Achieving Human and Machine Accessibility of Cited Data in Scholarly Publications, has just been published and we are honored that it is ARTICLE #1 in the newly-launched open-access journal PeerJ Computer Science. 


This article was the joint work of the multi-institution IDMETA team, led by Joan Starr (California Digital Library) as part of the Force11 Data Citation Implementation Group.  It outlines a detailed set of guidelines for implementing data citations that are accessible both to humans via Web browsers, and to computers and software via Web services.

It contains specific technical recommendations on how to implement the Joint Declaration of Data Citation Principles, including how archived data should be cited, archived, and  identified; how identifiers should resolve; which identifier schemes are recommended; which kinds of web services provide best accessibility; and how landing pages should be organized to provide maximal human and machine accessibility of the cited data.

Together with the new NISO JATS revisions to support direct data citation - a complementary effort led by Jo McEntyre (European Bioinformatics Institute) - this article provides robust working technical guidelines that publishers and archivists can follow to implement the JDDCP.  As we note in the article:

"The recommendations outlined here were developed as part of a community process by participants representing a wide variety of scholarly organizations, hosted by the FORCE11 Data Citation Implementation Group (DCIG) (https://www.force11.org/datacitationimplementation). This work was conducted over a period of approximately one year beginning in early 2014 as a follow-on activity to the completed JDDCP.

I would like to specifically mention what a great experience working with the PeerJ CS reviewers and production team was.  Total time from submission to first review was two weeks. Harry Hocheiser the Academic Editor for this article, and Jackie Thai, Head of Publishing Operations, were outstanding to work with.

We hope that this article along with the new NISO JATS revision will help accelerate the wide adoption of data citation in  scholarly literature, to better enable open transparency for validation, reuse and extension of results. 

Transparency, validation, reuse & extension imply robustness of results.  Robust findings are reproducible.

Tim Clark

Harvard Medical School & Massachusetts General Hospital

Tim Clark

FORCE11 Member since October 26, 2011
  • Organization/Institution: University of Virginia
  • ORCID ID: 0000-0003-4060-7360
  • Skype: skypetimc


Tim Clark, Ph.D., is a researcher in biomedical informatics and computer science.  He is Associate Professor of Public Health Sciences and of Neurology at the University of Virginia School of Medicine, and Associate Research Director for Neuroinformatics at the UVA Data Science Institute.  Dr. Clark is an Editorial Board member of the journals Briefings in Bioinformatics,  Data Science, and Frontiers in Research Metrics and Analytics; and an Advisory Board member for F1000 Research. 

Before coming to UVA, Tim spent 14 years at the Massachusetts General Hospital and Harvard Medical School, where he was Assistant Professor of Neurology and co-led the Data and Statistics Core at the Massachusetts Alzheimer Disease Research Center. Before that Tim was Vice President of Informatics at Millennium Pharmaceuticals, where his team built one of the first integrated bio- and chemi-informatics software platforms in the pharmaceutical industry. He began his career in life science informatics at the NCBI/NIH, where he led the database development team for NCBI GenBank. Dr. Clark’s academic training is in Computer Science.  He earned his M.S. at Johns Hopkins University; and his Ph.D. at the University of Manchester (UK) where his dissertation was supervised by Professor Carole Goble.