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Data sharing in neuroimaging research.

Poline, J-B; Breeze, JL; Ghosh, S; Gorgolewski, K; Halchenko, YO; Hanke, M; Haselgrove, C; ... Kennedy, DN; + view all (2012) Data sharing in neuroimaging research. Frontiers Neuroinformatics , 9 (1) pp. 9-13. 10.3389/fninf.2012.00009. Gold open access

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Abstract

Significant resources around the world have been invested in neuroimaging studies of brain function and disease. Easier access to this large body of work should have profound impact on research in cognitive neuroscience and psychiatry, leading to advances in the diagnosis and treatment of psychiatric and neurological disease. A trend toward increased sharing of neuroimaging data has emerged in recent years. Nevertheless, a number of barriers continue to impede momentum. Many researchers and institutions remain uncertain about how to share data or lack the tools and expertise to participate in data sharing. The use of electronic data capture (EDC) methods for neuroimaging greatly simplifies the task of data collection and has the potential to help standardize many aspects of data sharing. We review here the motivations for sharing neuroimaging data, the current data sharing landscape, and the sociological or technical barriers that still need to be addressed. The INCF Task Force on Neuroimaging Datasharing, in conjunction with several collaborative groups around the world, has started work on several tools to ease and eventually automate the practice of data sharing. It is hoped that such tools will allow researchers to easily share raw, processed, and derived neuroimaging data, with appropriate metadata and provenance records, and will improve the reproducibility of neuroimaging studies. By providing seamless integration of data sharing and analysis tools within a commodity research environment, the Task Force seeks to identify and minimize barriers to data sharing in the field of neuroimaging.

Type: Article
Title: Data sharing in neuroimaging research.
Location: Switzerland
Open access status: An open access publication
DOI: 10.3389/fninf.2012.00009
Publisher version: http://dx.doi.org/ 10.3389/fninf.2012.00009
Language: English
Additional information: Copyright: © 2012 Poline, Breeze, Ghosh, Gorgolewski, Halchenko, Hanke, Haselgrove, Helmer, Keator, Marcus, Poldrack, Schwartz, Ashburner and Kennedy. This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License (https://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.
Keywords: EEG-MEG, brain imaging, data sharing, fMRI, magnetic resonance imaging, standards
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/1344634
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