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Data Repository Selection: Criteria that matter

Researchers | Data sharing
Data Repository Selection: Criteria that matter

FAIRsharing and DataCite are proposing a set of criteria that journals and publishers believe are important for the identification and selection of data repositories.

The following blog post is a joint announcement of an initiative by several publishers, including Hindawi, in collaboration with Fairsharing and DataCite, to help authors select appropriate data repositories. This continues our commitment to furthering Open Science by working with others in the scholarly community to align policies and ensure that the data underlying the findings of the papers we publish can be made available for reuse – as open as possible and as closed as necessary. Please help us in this community effort by providing feedback on this initiative, as outlined below.

Publishers and journals are developing data policies to ensure that datasets, as well as other digital products associated with articles, are deposited and made accessible via appropriate repositories, also in line with the FAIR Principles (ref1).  With thousands of options available, however, the lists of deposition repositories recommended by publishers are often different (ref1ref2)  and consequently the guidance provided to authors may vary from journal to journal. This is due to a lack of common criteria used to select the data repositories, but also to the fact that there is still no consensus of what constitutes a good data repository. 

To tackle this, FAIRsharing (ref3) and DataCite (ref4) have joined forces with a group of publisher representatives listed below, including Hindawi, who are actively implementing data policies and recommending data repositories to researchers. The result of our work is a set of proposed criteria that journals and publishers believe are important for the identification and selection of data repositories, which can be recommended to researchers when they are preparing to publish the data underlying their findings. 

Our work intends to 

  • reduce complexity for researchers when preparing their submissions to journals, 
  • increase efficiency for data repositories that currently have to work with all individual publishers, and
  • simplify the process of recommending data repositories for publishers.  

Our work will make the implementation of research data policies more efficient and consistent, which may help to improve approaches to data sharing by promoting the use of reliable data repositories. 

Although we recognize that researchers and other stakeholders play a role in the research data life cycle, in this first instance the target audience for our work are other journals and publishers, repository developers and maintainers, certification and other evaluation initiatives, and other policy makers.  

This proposed criteria are intended to:

  • guide journals and publishers in providing authors with consistent recommendations and guidance on data deposition, and improve authors’ data sharing practices;
  • reduce potential for confusion of researchers and support staff, and reduce duplication of effort by different publishers and data repositories
  • inform data repository developers and managers of the features believed to be important by journals and publishers;
  • apprise certification and other evaluation initiatives, serving as a reference and perspective from journals and publishers;
  • drive the curation of the description of the data repository in FAIRsharing, which will enable display, filter and search based on these criteria.

We invite you to read the pre-print article (ref5) that describes the work, its motivation, relations to other initiatives, and provide us with feedback via this form (ref6). 


  1. https://www.nature.com/articles/sdata201618
  2. https://fairsharing.org/recommendations/
  3. https://fairsharing.org/
  4. https://datacite.org/
  5. https://osf.io/m2bce/
  6. https://docs.google.com/forms/d/e/1FAIpQLSfFCYtsDqN5-QjtpdT9MM4OWbodPa1CmRSmVdr2mLkDznYQng/viewform

This blog post was co-written by  Susanna-Assunta Sansone1 (0000-0001-5306-5690), Peter McQuilton1 (0000-0003-2687-1982), Helena Cousijn2 (0000-0001-6660-6214), Matthew Cannon3 (0000-0002-1496-8392), Wei Mun Chan4 (0000-0002-9971-813X), Ilaria Carnevale5 (0000-0001-8509-0495), Imogen Cranston6 (0000-0002-7134-499X), Scott Edmunds7 (0000-0001-6444-1436), Nicholas Everitt3 (0000-0001-8343-8910), Emma Ganley8 (0000-0002-2557-6204), Chris Graf9 (0000-0002-4699-4333), Iain Hrynaszkiewicz8 (0000-0002-9673-5559), Varsha K. Khodiyar10 (0000-0002-2743-6918), Thomas Lemberger11 (0000-0002-2499-4025), Catriona J. MacCallum (0000-0001-9623-2225)12, Kiera McNeice13 (0000-0003-2839-4067), Hollydawn Murray6 (0000-0002-8243-2493), Philippe Rocca-Serra1 (0000-0001-9853-5668), Kathryn Sharples9 (0000-0003-2809-6828), Marina Soares E Silva5 (0000-0001-9530-627X), Jonathan Threlfall6 (0000-0001-8599-4320).

It is distributed under the Creative Commons Attribution License (CC-BY). The illustration is by Hindawi Ltd and is also CC-BY.

1FAIRsharing, University of Oxford, Oxford, OX1 3QG, UK; 2DataCite, Welfengarten 1b, 30167 Hannover, Germany; 3Taylor & Francis, Park Square, Milton Park, Abingdon, OX14 4RN, UK; 4eLife Sciences Publications, Ltd, Westbrook Centre, Milton Road, Cambridge, CB4 1YG, UK; 5Elsevier, Radarweg 29, 1043NX, Amsterdam, The Netherlands; 6F1000, Middlesex House, 34-42 Cleveland St, Fitzrovia, London W1T 4LB, UK; 7GigaScience, BGI Hong Kong Tech Ltd., 26F A Kings Wing Plaza, 1 On Kwan St, Shek Mun, N.T., Hong Kong, China; 8PLOS (Public Library of Science), Carlyle House, Carlyle Road, Cambridge CB4 3DN, UK; 9Wiley, 9600 Garsington Road, Oxford, OX4 2DQ, UK; 10Springer Nature, 4 Crinan Street, London, N1 9XW, UK; 11EMBO Press, Meyerhofstrasse 1, 69117 Heidelberg, Germany; 12Hindawi Ltd, 1 Fitzroy Square, London, W1T 5HF, UK; 13Cambridge University Press, Shaftesbury Rd, Cambridge, CB2 8BS, UK.