SCIENCE@home

Developing a Research Data Policy Framework for All Journals and Publishers

I. Hrynaszkiewicz,Natasha Simons,A. Hussain,R. Grant,S. Goudie

Published 2020 in Data Science Journal

ABSTRACT

An output of the Data policy standardisation and implementation Interest Group (IG) of the Research Data Alliance (RDA) More journals and publishers – and funding agencies and institutions – are introducing research data policies. But as the prevalence of policies increases, there is potential to confuse researchers and support staff with numerous or conflicting policy requirements. We define and describe 14 features of journal research data policies and arrange these into a set of six standard policy types or tiers, which can be adopted by journals and publishers to promote data sharing in a way that encourages good practice and is appropriate for their audience’s perceived needs. Policy features include coverage of topics such as data citation, data repositories, data availability statements, data standards and formats, and peer review of research data. These policy features and types have been created by reviewing the policies of multiple scholarly publishers, which collectively publish more than 10,000 journals, and through discussions and consensus building with multiple stakeholders in research data policy via the Data Policy Standardisation and Implementation Interest Group of the Research Data Alliance. Implementation guidelines for the standard research data policies for journals and publishers are also provided, along with template policy texts which can be implemented by journals in their Information for Authors and publishing workflows. We conclude with a call for collaboration across the scholarly publishing and wider research community to drive further implementation and adoption of consistent research data policies. Publisher's Note: a correction article relating to this publication has been published and can be found at  http://doi.org/10.5334/dsj-2020-017

PUBLICATION RECORD

  • Publication year

    2020

  • Venue

    Data Science Journal

  • Publication date

    2020-02-21

  • Fields of study

    Political Science, Computer Science, Education

  • Identifiers
    DOI 10.5334/dsj-2020-005
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-29 of 29 references · Page 1 of 1

CITED BY

Showing 1-54 of 54 citing papers · Page 1 of 1