Abstract

Data standardization promotes a common framework through which researchers can utilize others’ data and is one of the leading methods neuroimaging researchers use to share and replicate findings. As of today, standardizing datasets requires technical expertise such as coding and knowledge of file formats. We present ezBIDS, a tool for converting neuroimaging data and associated metadata to the Brain Imaging Data Structure (BIDS) standard. ezBIDS contains four major features: (1) No installation or programming requirements. (2) Handling of both imaging and task events data and metadata. (3) Semi-automated inference and guidance for adherence to BIDS. (4) Multiple data management options: download BIDS data to local system, or transfer to OpenNeuro.org or to brainlife.io. In sum, ezBIDS requires neither coding proficiency nor knowledge of BIDS, and is the first BIDS tool to offer guided standardization, support for task events conversion, and interoperability with OpenNeuro.org and brainlife.io.

Details

Title
ezBIDS: Guided standardization of neuroimaging data interoperable with major data archives and platforms
Author
Levitas, Daniel 1   VIAFID ORCID Logo  ; Hayashi, Soichi 1 ; Vinci-Booher, Sophia 2   VIAFID ORCID Logo  ; Heinsfeld, Anibal 1   VIAFID ORCID Logo  ; Bhatia, Dheeraj 1 ; Lee, Nicholas 1   VIAFID ORCID Logo  ; Galassi, Anthony 3 ; Niso, Guiomar 4   VIAFID ORCID Logo  ; Pestilli, Franco 1   VIAFID ORCID Logo 

1  University of Texas, Department of Psychology, Department of Neuroscience, Center for Perceptual Systems, Center for Learning and Memory, Center for Aging Population Sciences, Austin, USA (GRID:grid.55460.32) (ISNI:0000000121548364) 
2  Vanderbilt University, Department of Psychology and Human Development, Peabody College, Nashville, USA (GRID:grid.152326.1) (ISNI:0000 0001 2264 7217) 
3  National Institute of Mental Health, Center for Multimodal Neuroimaging, Bethesda, USA (GRID:grid.416868.5) (ISNI:0000 0004 0464 0574) 
4  Instituto Cajal, CSIC, Madrid, Spain (GRID:grid.419043.b) (ISNI:0000 0001 2177 5516) 
Pages
179
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41597-024-02959-0
ProQuest document ID
2923579978
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.