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. 2021 Oct 18:10:e71774.
doi: 10.7554/eLife.71774.

The OpenNeuro resource for sharing of neuroscience data

Christopher J Markiewicz  1 , Krzysztof J Gorgolewski  1 , Franklin Feingold  1 , Ross Blair  1 , Yaroslav O Halchenko  2 , Eric Miller  3 , Nell Hardcastle  3 , Joe Wexler  1 , Oscar Esteban  1   4 , Mathias Goncavles  1 , Anita Jwa  1 , Russell Poldrack  1
Affiliations

The OpenNeuro resource for sharing of neuroscience data

Christopher J Markiewicz et al. Elife. .

Abstract

The sharing of research data is essential to ensure reproducibility and maximize the impact of public investments in scientific research. Here, we describe OpenNeuro, a BRAIN Initiative data archive that provides the ability to openly share data from a broad range of brain imaging data types following the FAIR principles for data sharing. We highlight the importance of the Brain Imaging Data Structure standard for enabling effective curation, sharing, and reuse of data. The archive presently shares more than 600 datasets including data from more than 20,000 participants, comprising multiple species and measurement modalities and a broad range of phenotypes. The impact of the shared data is evident in a growing number of published reuses, currently totalling more than 150 publications. We conclude by describing plans for future development and integration with other ongoing open science efforts.

Keywords: EEG; MEG; MRI; data sharing; human; mouse; neuroimaging; neuroscience; open science; rat.

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Conflict of interest statement

CM, KG, FF, RB, YH, JW, OE, MG, AJ, RP No competing interests declared, EM is owner of Squishymedia which is funded to perform software development work on OpenNeuro. NH is an employee of Squishymedia which is funded to perform software development work on OpenNeuro.

Figures

Figure 1.
Figure 1.. A schematic overview of the data upload process.
Figure 1—figure supplement 1.
Figure 1—figure supplement 1.. Word clouds based on Cognitive Atlas terms for psychological concepts (top) and tasks (bottom) identified from titles and README files associated with OpenNeuro datasets.
Figure 1—figure supplement 2.
Figure 1—figure supplement 2.. Word clouds based on Cognitive Atlas terms for psychological concepts (top) and tasks (bottom) identified from titles and README files associated with OpenNeuro datasets.
Figure 2.
Figure 2.. The volume of data available on OpenNeuro has shown a steady growth since its opening started operations in 2017.
Shown are figures from July 2018, when all data were migrated to a new DataLad storage backend, through the present date. The green line illustrates the cumulative growth in total number of datasets, and the red line shows the aggregate of subjects (in thousands).
Figure 3.
Figure 3.. OpenNeuro datasets vary substantially in number of participants (X axis), number of sessions per participant (Y axis), and number of tasks per participant (size/color of datapoints); axes are log-scaled for easier visualization.
Results are based on metadata derived directly from the 502 OpenNeuro datasets available via DataLad as of 10/9/2021.
Figure 4.
Figure 4.. Published reuses of OpenNeuro datasets, split by the type of reuse.
Note that the final bar includes only reuses identified through June 2021.
See this image and copyright information in PMC

Comment in

  • A FAIR platform for data-sharing.
    Wiseman S. Wiseman S. Nat Neurosci. 2021 Dec;24(12):1640. doi: 10.1038/s41593-021-00976-5. Nat Neurosci. 2021. PMID: 34848877 No abstract available.

References

    1. Aquino KM, Fulcher BD, Parkes L, Sabaroedin K, Fornito A. Identifying and removing widespread signal deflections from fMRI data: Rethinking the global signal regression problem. NeuroImage. 2020;212:116614. doi: 10.1016/j.neuroimage.2020.116614. - DOI - PubMed
    1. Bannier E, Barker G, Borghesani V, Broeckx N, Clement P, Emblem KE, Ghosh S, Glerean E, Gorgolewski KJ, Havu M, Halchenko YO, Herholz P, Hespel A, Heunis S, Hu Y, Hu C-P, Huijser D, de la Iglesia Vayá M, Jancalek R, Katsaros VK, Kieseler M-L, Maumet C, Moreau CA, Mutsaerts H-J, Oostenveld R, Ozturk-Isik E, Pascual Leone Espinosa N, Pellman J, Pernet CR, Pizzini FB, Trbalić AŠ, Toussaint P-J, Visconti di Oleggio Castello M, Wang F, Wang C, Zhu H. The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data. Human Brain Mapping. 2021;42:1945–1951. doi: 10.1002/hbm.25351. - DOI - PMC - PubMed
    1. Bansal S, Kori A, Zulfikar W, Wexler J, Markiewicz C, Feingold F, Poldrack R. High-Sensitivity Detection of Facial Features on MRI Brain Scans with a Convolutional Network. bioRxiv. 2020 doi: 10.1101/2021.04.25.441373. - DOI
    1. Bischoff-Grethe A, Ozyurt IB, Busa E, Quinn BT, Fennema-Notestine C, Clark CP, Morris S, Bondi MW, Jernigan TL, Dale AM, Brown GG, Fischl B. A technique for the deidentification of structural brain MR images. Human Brain Mapping. 2007;28:892–903. doi: 10.1002/hbm.20312. - DOI - PMC - PubMed
    1. Biswal BB, Mennes M, Zuo XN, Gohel S, Kelly C, Smith SM, Beckmann CF, Adelstein JS, Buckner RL, Colcombe S, Dogonowski AM, Ernst M, Fair D, Hampson M, Hoptman MJ, Hyde JS, Kiviniemi VJ, Kötter R, Li SJ, Lin CP, Lowe MJ, Mackay C, Madden DJ, Madsen KH, Margulies DS, Mayberg HS, McMahon K, Monk CS, Mostofsky SH, Nagel BJ, Pekar JJ, Peltier SJ, Petersen SE, Riedl V, Rombouts S, Rypma B, Schlaggar BL, Schmidt S, Seidler RD, Siegle GJ, Sorg C, Teng GJ, Veijola J, Villringer A, Walter M, Wang L, Weng XC, Whitfield-Gabrieli S, Williamson P, Windischberger C, Zang YF, Zhang HY, Castellanos FX, Milham MP. Toward discovery science of human brain function. PNAS. 2010;107:4734–4739. doi: 10.1073/pnas.0911855107. - DOI - PMC - PubMed

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