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Achieving human and machine accessibility of cited data in scholarly publications

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 IDMETA team, led by Joan Starr, of the 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.


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