TY - JOUR
T1 - Assessment of the impact of shared brain imaging data on the scientific literature
AU - Milham, Michael P.
AU - Craddock, R. Cameron
AU - Son, Jake J.
AU - Fleischmann, Michael
AU - Clucas, Jon
AU - Xu, Helen
AU - Koo, Bonhwang
AU - Krishnakumar, Anirudh
AU - Biswal, Bharat B.
AU - Castellanos, F. Xavier
AU - Colcombe, Stan
AU - Di Martino, Adriana
AU - Zuo, Xi Nian
AU - Klein, Arno
N1 - Funding Information:
The Child Mind Institute provides primary funding for the INDI team, with additional support provided by the Nathan S. Kline Institute for Psychiatric Research. We would like to thank the many contributors to the 1000 Functional Connectomes Project and INDI; it is their vision and contributions that have made these efforts successful. Thanks also to the many members of the INDI team over the years, especially Maarten Mennes, Quiyang Li, Dan Lurie, and David O’Connor. We thank the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) for hosting support for INDI, as well as Amazon Web Services and the COllaborative Informatics and Neuroimaging Suite (COINS). This work was supported in part by gifts to the Child Mind Institute from Phyllis Green, Randolph Cowen, Joseph P. Healey, and the Stavros Niarchos Foundation. M.P.M. is the Phyllis Green and Randolph Cowen Scholar at the Child Mind Institute. A. D.M. received grant support from the National Institutes of Health (521MH107045); X.-N.Z. received support from the National Basic Research Program (2015CB351702), National Natural Science Foundation of China (81220108014), Beijing Municipal Science & Technology Commission (Z161100002616023 and Z171100000117012), the National R&D Infrastructure and Facility Development Program of China—“Fundamental Science Data Sharing Platform” (DKA2017−12−02−21), and Guangxi Bagui Honor Scholarship Program. A.Kr. received support from the IDEFI IIFR grant (ANR-2012-IDEFI-04). Primary funding for the NKI-RS initiatives is provided by grants from the NIH (R01MH094639, R01MH101555, R01-AG047596, and U01MH099059), as well as support from the New York State Office of Mental Health and Research Foundation for Mental Hygiene, and Child Mind Institute (1FDN2012-1).
Publisher Copyright:
© 2018, The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - 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.
AB - 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.
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U2 - 10.1038/s41467-018-04976-1
DO - 10.1038/s41467-018-04976-1
M3 - Article
C2 - 30026557
AN - SCOPUS:85050635646
VL - 9
JO - Nature Communications
JF - Nature Communications
SN - 2041-1723
IS - 1
M1 - 2818
ER -