Journal Production Guidance for Software and Data Citations

Abstract

Software and data citation are emerging best practices in academic and scientific communication that provide excellent support for results validation, reproducibility, credit, sharing and reuse of valuable tools and resources. Data citation has been possible with some rigor since the establishment of DataCite—a Registration Agency of the International DOI Foundation, which issues robust persistent identifiers for datasets and maintains a registry of associated rich metadata—in 2009 1 and was recommended by a comprehensive report of a CODATA-ICSTI task group in 2012 (available at: http://www.nap.edu/catalog.php?record_id=13564 ). CODATA-ICSTI is the international and interdisciplinary Committee on Data for Science and Technology (CODATA) and the International Council for Scientific and Technical Information (ICSTI) jointly-formed Task Group on Data Citation Standards and Practices ( https://codata.org/initiatives/task-groups/previous-tgs/data-citation-standards-and-practices/ ). It has become increasingly adopted since the introduction of the “Joint Declaration of Data Citation Principles” 2 in 2014 and its endorsement by 125 publishers, academic institutions, and funders (see https://force11.org/info/endorse-the-data-citation-principles/ ). The enthusiasm for these principles prompted an effort to provide a clear set of practical guidelines for publishers to begin to implement data citations. In 2018 “A data citation roadmap for scientific publishers” 3 was published, incorporating work from several groups via workshops and including major participation by representatives of Elsevier, Springer-Nature, PLOS, eLIFE, JISC, EMBO Press, CrossRef, and Wiley. However, even when following this guidance, several publishers were finding that machine-actionable software and data citations from their own published articles were not preserved intact when the article was published, and that downstream services and linking were not enabled. Furthermore, it should be noted that software usage and citation, while similar to data citation, has certain key differences that should be reflected in publication workflows 4 , 5 . These are complex and involve authors, reviewers, editors, and other infrastructure services. Here we provide updates on this guidance to enable automated attribution and credit for software and data used in published articles.