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Assessment of the impact of shared brain imaging data on the scientific literature

Author

Listed:
  • Michael P. Milham

    (Child Mind Institute
    Nathan S. Kline Institute for Psychiatric Research)

  • R. Cameron Craddock

    (Child Mind Institute
    Nathan S. Kline Institute for Psychiatric Research)

  • Jake J. Son

    (Child Mind Institute)

  • Michael Fleischmann

    (Child Mind Institute)

  • Jon Clucas

    (Child Mind Institute)

  • Helen Xu

    (Child Mind Institute)

  • Bonhwang Koo

    (Child Mind Institute)

  • Anirudh Krishnakumar

    (Child Mind Institute
    INSERM U1001, Dpt Frontières du Vivant et de l′Apprendre, University Paris Descartes, Sorbonne Paris Cité)

  • Bharat B. Biswal

    (New Jersey Institute of Technology)

  • F. Xavier Castellanos

    (Nathan S. Kline Institute for Psychiatric Research
    Hassenfeld Childrenʼs Hospital at NYU Langone)

  • Stan Colcombe

    (Nathan S. Kline Institute for Psychiatric Research)

  • Adriana Di Martino

    (Hassenfeld Childrenʼs Hospital at NYU Langone)

  • Xi-Nian Zuo

    (University of Chinese Academy of Sciences (CAS)
    Institute of Psychology
    Institute of Psychology
    Guangxi Teachers Education University)

  • Arno Klein

    (Child Mind Institute)

Abstract

Data sharing is increasingly recommended as a means of accelerating science by facilitating collaboration, transparency, and reproducibility. While few oppose data sharing philosophically, a range of barriers deter most researchers from implementing it in practice. To justify the significant effort required for sharing data, funding agencies, institutions, and investigators need clear evidence of benefit. Here, using the International Neuroimaging Data-sharing Initiative, we present a case study that provides direct evidence of the impact of open sharing on brain imaging data use and resulting peer-reviewed publications. We demonstrate that openly shared data can increase the scale of scientific studies conducted by data contributors, and can recruit scientists from a broader range of disciplines. These findings dispel the myth that scientific findings using shared data cannot be published in high-impact journals, suggest the transformative power of data sharing for accelerating science, and underscore the need for implementing data sharing universally.

Suggested Citation

  • Michael P. Milham & R. Cameron Craddock & Jake J. Son & Michael Fleischmann & Jon Clucas & Helen Xu & Bonhwang Koo & Anirudh Krishnakumar & Bharat B. Biswal & F. Xavier Castellanos & Stan Colcombe & A, 2018. "Assessment of the impact of shared brain imaging data on the scientific literature," Nature Communications, Nature, vol. 9(1), pages 1-7, December.
  • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-04976-1
    DOI: 10.1038/s41467-018-04976-1
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    Cited by:

    1. Giovanni Colavizza & Iain Hrynaszkiewicz & Isla Staden & Kirstie Whitaker & Barbara McGillivray, 2020. "The citation advantage of linking publications to research data," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-18, April.
    2. Joshua Borycz & Robert Olendorf & Alison Specht & Bruce Grant & Kevin Crowston & Carol Tenopir & Suzie Allard & Natalie M. Rice & Rachael Hu & Robert J. Sandusky, 2023. "Perceived benefits of open data are improving but scientists still lack resources, skills, and rewards," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.

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