Our research data policy framework has been published

24 Feb 2020

Dear Data Policy Standardisation and Implementation Interest Group members,
On behalf of the co-chairs past and present, I am pleased to share that the first major output of this group has been published in a peer-reviewed journal.
Please read, and share with colleagues and the community, the peer-reviewed paper in CODATA Data Science Journal here.
Hrynaszkiewicz, I., Simons, N., Hussain, A., Grant, R. and Goudie, S., 2020. Developing a Research Data Policy Framework for All Journals and Publishers. Data Science Journal, 19(1), p.5. DOI: http://doi.org/10.5334/dsj-2020-005
Thank you to everyone who attended one of our plenary meetings or community calls, read and commented on one of the drafts of the framework, or who has already used the framework to inform policy development or implementation. We are grateful for the broad stakeholder and community engagement that you, this group, and the RDA has brought to this initiative.
Arguably, now the hard work begins, as we work with interested parties to enable adoption of and alignment with the framework by numerous journals and publishers.
We recently sent an invitation to our group's next plenary meeting in Melbourne, where we will be continuing our collaboration with the publishing industry via the STM Association, to encourage adoption of standardised policies. We will also, importantly, be focusing more time on the next priority for our group - collaborations with funding agencies to explore the potential for policy feature harmonisation.
Best wishes,
Iain, Natasha, Simon, Rebecca, Azhar

  • Philipp Conzett's picture

    Author: Philipp Conzett

    Date: 14 Apr, 2020

    Congrats with your published recommendations! I have finally had the chance to read about your research data policy framework, and I found it very useful. I have two comments which may help to improve the recommendations further:

    1. Recommended data repositories

    Your recommendations only mention two types of data repositories: domain-specific repositories and general repositories of the type figshare or Zenodo. There is some common agreement that if there is a trusted domain-specific repository within the field at stake, then this should be recommended rather then a general one. However, there are also institutional repositories, and in my view they are at least as preferable as general repositories of the type figshare or Zenodo. I have just recently got a question from a researcher at our university about data publishing. The journal he was going to submit an article manuscript to, had a list of required repositories (for some types of data), and a list of recommended repositories (for all other types of data). On the latter list, figshare and Zenodo were mentioned, whereas institutional repositories were not mentioned at all. Our institutional data repository provides data curation of all deposited datsets prior to publication. Also, the repository is CoreTrustSeal certified. I cannot really see why a repository like figshare or Zenodo should be preferred over sustainable and trusted institutional repositories. In your recommendation / CODATA article, you write that "lists of recommended data repositories and criteria for assessing data repositories are not in scope" (p. 2). I agree with you that it is unfeasible for your recommendations to include comprehensive lists of recommended data repositories, but perhaps some advice could be given on what kind of repositories that should be recommended, including the advice that sustainable and trusted institutional repositories can easily be found by searching on re3data. I'm afraid that not mentioning institutional efforts to turning FAIR into reality, will potentially contribute to undermine these efforts.

    2. Data access prior to publication

    Your advice for policies 5 and 6 is that "data must be accessible to readers at the publication date, and at minimum have been accessible to editors and peer reviewers before publication" (p. 8). We need guidelines on how access previous to the publication of the data should be handled. On page 11, you give the following advice:

    "The availability of data, such as links to datasets in repositories, must be visible to peer reviewers. Some manuscript submission systems can offer integration with general data repositories that enable confidential access to data during peer review, such as figshare and Dryad, to enable authors and journals to comply efficiently with this policy."

    The feature you mention about confidential access is also available in other repositories, but journal (and repositories!) need more advice on how this should be handled independently of the system(s) that are used. This is particularly important when the publishing venue practices double-blind peer review; in that case, confidential access is not enough, access must also be in a way that does not reveal the identity of the depositor/author of the dataset.

    Best regards,

    Philipp Conzett
    UiT The Arctic University of Norway
    ORCID: https://orcid.org/0000-0002-6754-7911

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