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. 2018 Jul 19;9(1):2818.
doi: 10.1038/s41467-018-04976-1.

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

Affiliations

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

Michael P Milham et al. Nat Commun. .

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.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Publications that used INDI shared data. Publications sorted (a) by INDI data set and year, for the period of 2010–2016 (2017 is not included since that year was in progress at the time this study was conducted), (b) by publication type, and (c) by journal discipline (limited to peer-reviewed publications and based on Web of Science classifications)
Fig. 2
Fig. 2
Estimation of publication impact. a Fifteen highest-impact journals with articles using INDI data sets (based on CiteScore, with the number of publications in each journal). b Cumulative density function (CDF) for CiteScores of publications that used INDI data (select journals are marked to provide reference points to help interpret CiteScores). c CDF comparison for MRI-based publications focused on autism that used ABIDE data versus closed data (one non-ABIDE publication of CiteScore 23.17 was not included in the figure for axis consistency). d CDF comparison for MRI-based publications focused on ADHD that used ADHD-200 data versus closed data. e CDF comparison of publications that used INDI data versus the HCP and the larger MRI brain imaging literature, as indexed by Web of Science (WoS)
Fig. 3
Fig. 3
Data use by authors. Breakdown of publications by contributor status, for the period from 2010–2016 (2017 is not included since this study was conducted during that year)

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