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Modelling perception and resilience factors to data sharing in clinical and basic research: an observational study

Author

Listed:
  • Federica Cugnata

    (University Center for Statistics in the Biomedical Sciences, CUSSB
    Vita-Salute San Raffaele University)

  • Chiara Brombin

    (University Center for Statistics in the Biomedical Sciences, CUSSB
    Vita-Salute San Raffaele University)

  • Chiara Maria Poli

    (Vita-Salute San Raffaele University)

  • Roberto Buccione

    (Vita-Salute San Raffaele University)

  • Clelia Serio

    (University Center for Statistics in the Biomedical Sciences, CUSSB
    Vita-Salute San Raffaele University)

Abstract

Data sharing is a major tenet in the global challenge to improve the reproducibility of scientific findings. Current researcher attitudes toward data sharing and Open Science in general are still far from optimal. The practice of data sharing and how it should be managed remain unclear and inconsistent, with many researchers keen to receive from, but not give back to the community. The lack of a data sharing culture, systemic resistance, misconceptions on data ownership and the unjustified fear of being “scooped”, all concur to create an enormous barrier to the promotion of scientific research based on increased information quality, transparency and openness, and replicability of results. These factors are also compounded by the erroneous perception that the sharing of data compromises competitiveness. Here, we present a rigorous observational study based on 198 researchers in the biomedical areas to evaluate factors affecting perception and natural attitude to data sharing in the biomedical sciences.

Suggested Citation

  • Federica Cugnata & Chiara Brombin & Chiara Maria Poli & Roberto Buccione & Clelia Serio, 2024. "Modelling perception and resilience factors to data sharing in clinical and basic research: an observational study," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3169-3192, June.
  • Handle: RePEc:spr:scient:v:129:y:2024:i:6:d:10.1007_s11192-024-05015-1
    DOI: 10.1007/s11192-024-05015-1
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    References listed on IDEAS

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    1. Max Kozlov, 2022. "NIH issues a seismic mandate: share data publicly," Nature, Nature, vol. 602(7898), pages 558-559, February.
    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. Marko Sarstedt & Christian M. Ringle & Joseph F. Hair, 2022. "Partial Least Squares Structural Equation Modeling," Springer Books, in: Christian Homburg & Martin Klarmann & Arnd Vomberg (ed.), Handbook of Market Research, pages 587-632, Springer.
    4. Thijs Devriendt & Pascal Borry & Mahsa Shabani, 2021. "Factors that influence data sharing through data sharing platforms: A qualitative study on the views and experiences of cohort holders and platform developers," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-14, July.
    5. 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.
    6. Josip Strcic & Antonia Civljak & Terezija Glozinic & Rafael Leite Pacheco & Tonci Brkovic & Livia Puljak, 2022. "Open data and data sharing in articles about COVID-19 published in preprint servers medRxiv and bioRxiv," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2791-2802, May.
    7. Youngseek Kim & Jeffrey M. Stanton, 2016. "Institutional and individual factors affecting scientists' data-sharing behaviors: A multilevel analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 776-799, April.
    8. Kim, Youngseek & Adler, Melissa, 2015. "Social scientists’ data sharing behaviors: Investigating the roles of individual motivations, institutional pressures, and data repositories," International Journal of Information Management, Elsevier, vol. 35(4), pages 408-418.
    9. Rut Lucas-Dominguez & Adolfo Alonso-Arroyo & Antonio Vidal-Infer & Rafael Aleixandre-Benavent, 2021. "The sharing of research data facing the COVID-19 pandemic," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4975-4990, June.
    10. Thijs Devriendt & Mahsa Shabani & Karim Lekadir & Pascal Borry, 2022. "Data sharing platforms: instruments to inform and shape science policy on data sharing?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3007-3019, June.
    11. Harper, Lindsey M. & Kim, Youngseek, 2018. "Attitudinal, normative, and resource factors affecting psychologists’ intentions to adopt an open data badge: An empirical analysis," International Journal of Information Management, Elsevier, vol. 41(C), pages 23-32.
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