IDEAS home Printed from https://ideas.repec.org/a/gam/jpubli/v12y2024i1p6-d1351214.html
   My bibliography  Save this article

FAIRness of Research Data in the European Humanities Landscape

Author

Listed:
  • Ljiljana Poljak Bilić

    (Department of Information Sciences, University of Zadar, 23 000 Zadar, Croatia
    University of Split Library, University of Split, 21 000 Split, Croatia)

  • Kristina Posavec

    (Data Management Department, University of Zagreb University Computing Centre SRCE, 10 000 Zagreb, Croatia)

Abstract

This paper explores the landscape of research data in the humanities in the European context, delving into their diversity and the challenges of defining and sharing them. It investigates three aspects: the types of data in the humanities, their representation in repositories, and their alignment with the FAIR principles (Findable, Accessible, Interoperable, Reusable). By reviewing datasets in repositories, this research determines the dominant data types, their openness, licensing, and compliance with the FAIR principles. This research provides important insight into the heterogeneous nature of humanities data, their representation in the repository, and their alignment with FAIR principles, highlighting the need for improved accessibility and reusability to improve the overall quality and utility of humanities research data.

Suggested Citation

  • Ljiljana Poljak Bilić & Kristina Posavec, 2024. "FAIRness of Research Data in the European Humanities Landscape," Publications, MDPI, vol. 12(1), pages 1-12, March.
  • Handle: RePEc:gam:jpubli:v:12:y:2024:i:1:p:6-:d:1351214
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2304-6775/12/1/6/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2304-6775/12/1/6/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chaim Zins, 2007. "Conceptual approaches for defining data, information, and knowledge," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(4), pages 479-493, February.
    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. Charles Ayoubi & Boris Thurm, 2023. "Knowledge diffusion and morality: Why do we freely share valuable information with Strangers?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 32(1), pages 75-99, January.
    2. Vostrovský, V. & Tyrychtr, J. & Ulman, M., 2015. "Potential of Open Data in the Agricultural eGovernment," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 7(2), pages 1-11, June.
    3. Aven, Terje, 2013. "A conceptual framework for linking risk and the elements of the data–information–knowledge–wisdom (DIKW) hierarchy," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 30-36.
    4. Maymin, Philip Z., 2019. "Wage against the machine: A generalized deep-learning market test of dataset value," International Journal of Forecasting, Elsevier, vol. 35(2), pages 776-782.
    5. Liubertė Irina, 2019. "On Social Knowledge and Its Empirical Investigation in Contemporary Organisations," Management of Organizations: Systematic Research, Sciendo, vol. 81(1), pages 21-37, June.
    6. Darrin Baines & Robert J R Elliott, 2020. "Defining misinformation, disinformation and malinformation: An urgent need for clarity during the COVID-19 infodemic," Discussion Papers 20-06, Department of Economics, University of Birmingham.
    7. Tommaso Luzzati & Ilaria Tucci & Pietro Guarnieri, 2022. "Information overload and environmental degradation: learning from H.A. Simon and W. Wenders," Papers 2209.01039, arXiv.org.
    8. Raphaël Gellert, 2022. "Comparing definitions of data and information in data protection law and machine learning: A useful way forward to meaningfully regulate algorithms?," Regulation & Governance, John Wiley & Sons, vol. 16(1), pages 156-176, January.
    9. Luzzati, Tommaso & Tucci, Ilaria & Guarnieri, Pietro, 2022. "Information overload and environmental degradation: Learning from H.A. Simon and W. Wenders," Ecological Economics, Elsevier, vol. 202(C).
    10. Pop Ioan G. & Talpos Mihai-Florin & Prisac Igor, 2015. "A Transdisciplinary Approach on the Advanced Sustainable Knowledge Integration," Balkan Region Conference on Engineering and Business Education, Sciendo, vol. 1(1), pages 1-11, November.
    11. Darin Freeburg, 2019. "The Knowing Model: Facilitating Behaviour Change in Organisations," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1-22, December.
    12. Yury Nurulin & Inga Skvortsova & Iosif Tukkel & Marko Torkkeli, 2019. "Role of Knowledge in Management of Innovation," Resources, MDPI, vol. 8(2), pages 1-12, May.
    13. Feng Liu & Yong Shi, 2020. "Investigating Laws of Intelligence Based on AI IQ Research," Annals of Data Science, Springer, vol. 7(3), pages 399-416, September.
    14. Alles, Michael & Gray, Glen L., 2016. "Incorporating big data in audits: Identifying inhibitors and a research agenda to address those inhibitors," International Journal of Accounting Information Systems, Elsevier, vol. 22(C), pages 44-59.
    15. Rashid, Mehvish & Clarke, Paul M. & O’Connor, Rory V., 2019. "A systematic examination of knowledge loss in open source software projects," International Journal of Information Management, Elsevier, vol. 46(C), pages 104-123.
    16. Gugissa, Desalegn A. & Ingenbleek, Paul T.M. & van Trijp, Hans C.M., 2021. "Market knowledge as a driver of sustainable use of common-pool resources: A lab-in-the-field study among pastoralists in Ethiopia," Ecological Economics, Elsevier, vol. 185(C).
    17. Ralph Hippe & Roger Fouquet, 2018. "The Knowledge Economy in Historical Perspective," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 19(1), pages 75-108, January.
    18. Ioanna Karamitri & Fotis Kitsios & Michael A. Talias, 2020. "Development and Validation of a Knowledge Management Questionnaire for Hospitals and Other Healthcare Organizations," Sustainability, MDPI, vol. 12(7), pages 1-15, March.
    19. Lu Tan & Jingsong Pei, 2023. "Open Government Data and the Urban–Rural Income Divide in China: An Exploration of Data Inequalities and Their Consequences," Sustainability, MDPI, vol. 15(13), pages 1-18, June.
    20. Paul Beynon‐Davies, 2012. "Enacting Significance: A New Perspective on the Nature of Information within Systems," Systems Research and Behavioral Science, Wiley Blackwell, vol. 29(1), pages 46-65, January.

    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:12:y:2024:i:1:p:6-:d:1351214. See general information about how to correct material in RePEc.

    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. RePEc uses bibliographic data supplied by the respective publishers.