IDEAS home Printed from https://ideas.repec.org/a/gam/jpubli/v8y2020i2p21-d344422.html
   My bibliography  Save this article

FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units

Author

Listed:
  • Koenraad De Smedt

    (Department of Linguistic, Literary and Aesthetic Studies, University of Bergen, P.O Box 7800, 5020 Bergen, Norway)

  • Dimitris Koureas

    (International Biodiversity Infrastructures, Naturalis Biodiversity Center, P.O. Box 9517, 2300 RA Leiden, The Netherlands)

  • Peter Wittenburg

    (Max Planck Computing and Data Facility, Max-Planck-Gesellschaft, Gießenbachstraße 2, 85748 Garching, Germany)

Abstract

Data science is facing the following major challenges: (1) developing scalable cross-disciplinary capabilities, (2) dealing with the increasing data volumes and their inherent complexity, (3) building tools that help to build trust, (4) creating mechanisms to efficiently operate in the domain of scientific assertions, (5) turning data into actionable knowledge units and (6) promoting data interoperability. As a way to overcome these challenges, we further develop the proposals by early Internet pioneers for Digital Objects as encapsulations of data and metadata made accessible by persistent identifiers. In the past decade, this concept was revisited by various groups within the Research Data Alliance and put in the context of the FAIR Guiding Principles for findable, accessible, interoperable and reusable data. The basic components of a FAIR Digital Object (FDO) as a self-contained, typed, machine-actionable data package are explained. A survey of use cases has indicated the growing interest of research communities in FDO solutions. We conclude that the FDO concept has the potential to act as the interoperable federative core of a hyperinfrastructure initiative such as the European Open Science Cloud (EOSC).

Suggested Citation

  • Koenraad De Smedt & Dimitris Koureas & Peter Wittenburg, 2020. "FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units," Publications, MDPI, vol. 8(2), pages 1-17, April.
  • Handle: RePEc:gam:jpubli:v:8:y:2020:i:2:p:21-:d:344422
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2304-6775/8/2/21/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2304-6775/8/2/21/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christine L. Borgman, 2012. "The conundrum of sharing research data," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(6), pages 1059-1078, June.
    2. Christine L. Borgman, 2012. "The conundrum of sharing research data," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(6), pages 1059-1078, June.
    3. Lindell Bromham & Russell Dinnage & Xia Hua, 2016. "Interdisciplinary research has consistently lower funding success," Nature, Nature, vol. 534(7609), pages 684-687, June.
    4. Lutz Bornmann & Rüdiger Mutz, 2015. "Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(11), pages 2215-2222, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vikas Jaiman & Leonard Pernice & Visara Urovi, 2022. "User incentives for blockchain-based data sharing platforms," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-22, April.
    2. Benedikt Fecher & Sascha Friesike & Marcel Hebing, 2014. "What Drives Academic Data Sharing?," SOEPpapers on Multidisciplinary Panel Data Research 655, DIW Berlin, The German Socio-Economic Panel (SOEP).
    3. Mike Thelwall, 2020. "Data in Brief: Can a mega-journal for data be useful?," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 697-709, July.
    4. Carol Tenopir & Elizabeth D Dalton & Suzie Allard & Mike Frame & Ivanka Pjesivac & Ben Birch & Danielle Pollock & Kristina Dorsett, 2015. "Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-24, August.
    5. Andrea K. Thomer, 2022. "Integrative data reuse at scientifically significant sites: Case studies at Yellowstone National Park and the La Brea Tar Pits," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(8), pages 1155-1170, August.
    6. Plantin, Jean-Christophe, 2021. "The data archive as factory: alienation and resistance of data processors," LSE Research Online Documents on Economics 109692, London School of Economics and Political Science, LSE Library.
    7. Keren Weinshall & Lee Epstein, 2020. "Developing High‐Quality Data Infrastructure for Legal Analytics: Introducing the Israeli Supreme Court Database," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 17(2), pages 416-434, June.
    8. Guillaume Cabanac & Thomas Preuss, 2013. "Capitalizing on order effects in the bids of peer-reviewed conferences to secure reviews by expert referees," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(2), pages 405-415, February.
    9. Liwei Zhang & Liang Ma, 2021. "Does open data boost journal impact: evidence from Chinese economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3393-3419, April.
    10. Shibayama, Sotaro & Lawson, Cornelia, 2021. "The use of rewards in the sharing of research resources," Research Policy, Elsevier, vol. 50(7).
    11. Koutroumpis, Pantelis & Leiponen, Aija & Thomas, Llewellyn D W, 2017. "The (Unfulfilled) Potential of Data Marketplaces," ETLA Working Papers 53, The Research Institute of the Finnish Economy.
    12. Gary A. Hoover & Christian Hopp, 2017. "What Crisis? Taking Stock of Management Researchers' Experiences with and Views of Scholarly Misconduct," CESifo Working Paper Series 6611, CESifo.
    13. Ryan P Womack, 2015. "Research Data in Core Journals in Biology, Chemistry, Mathematics, and Physics," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-22, December.
    14. Keiko Kurata & Mamiko Matsubayashi & Shinji Mine, 2017. "Identifying the Complex Position of Research Data and Data Sharing Among Researchers in Natural Science," SAGE Open, , vol. 7(3), pages 21582440177, July.
    15. Brian Rappert & Louise Bezuidenhout, 2016. "Data sharing in low-resourced research environments," Prometheus, Taylor & Francis Journals, vol. 34(3-4), pages 207-224, October.
    16. Stefan Reichmann & Thomas Klebel & Ilire Hasani‐Mavriqi & Tony Ross‐Hellauer, 2021. "Between administration and research: Understanding data management practices in an institutional context," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(11), pages 1415-1431, November.
    17. Benedikt Fecher & Sascha Friesike & Marcel Hebing, 2015. "What Drives Academic Data Sharing?," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-25, February.
    18. Isabella Peters & Peter Kraker & Elisabeth Lex & Christian Gumpenberger & Juan Gorraiz, 2016. "Research data explored: an extended analysis of citations and altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 723-744, May.
    19. Jingfeng Xia, 2013. "Mandates and the Contributions of Open Genomic Data," Publications, MDPI, vol. 1(3), pages 1-14, October.
    20. Benedikt Fecher & Sascha Friesike & Marcel Hebing, 2014. "What Drives Academic Data Sharing?," RatSWD Working Papers 236, German Data Forum (RatSWD).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jpubli:v:8:y:2020:i:2:p:21-:d:344422. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://www.mdpi.com .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.