ezBIDS: Guided standardization of neuroimaging data interoperable with major data archives and platforms
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arXiv
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| Format: | Preprint |
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2023
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| author | Levitas, Daniel Hayashi, Soichi Vinci-Booher, Sophia Heinsfeld, Anibal Bhatia, Dheeraj Lee, Nicholas Galassi, Anthony Niso, Guiomar Pestilli, Franco |
| author_facet | Levitas, Daniel Hayashi, Soichi Vinci-Booher, Sophia Heinsfeld, Anibal Bhatia, Dheeraj Lee, Nicholas Galassi, Anthony Niso, Guiomar Pestilli, Franco |
| contents | Data standardization has become one of the leading methods neuroimaging researchers rely on for data sharing and reproducibility. Data standardization promotes a common framework through which researchers can utilize others' data. Yet, as of today, formatting datasets that adhere to community best practices requires technical expertise involving coding and considerable knowledge of file formats and standards. We describe ezBIDS, a tool for converting neuroimaging data and associated metadata to the Brain Imaging Data Structure (BIDS) standard. ezBIDS provides four unique features: (1) No installation or programming requirements. (2) Handling of both imaging and task events data and metadata. (3) 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 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 and brainlife.io. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_04912 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | ezBIDS: Guided standardization of neuroimaging data interoperable with major data archives and platforms Levitas, Daniel Hayashi, Soichi Vinci-Booher, Sophia Heinsfeld, Anibal Bhatia, Dheeraj Lee, Nicholas Galassi, Anthony Niso, Guiomar Pestilli, Franco Databases Data standardization has become one of the leading methods neuroimaging researchers rely on for data sharing and reproducibility. Data standardization promotes a common framework through which researchers can utilize others' data. Yet, as of today, formatting datasets that adhere to community best practices requires technical expertise involving coding and considerable knowledge of file formats and standards. We describe ezBIDS, a tool for converting neuroimaging data and associated metadata to the Brain Imaging Data Structure (BIDS) standard. ezBIDS provides four unique features: (1) No installation or programming requirements. (2) Handling of both imaging and task events data and metadata. (3) 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 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 and brainlife.io. |
| title | ezBIDS: Guided standardization of neuroimaging data interoperable with major data archives and platforms |
| topic | Databases |
| url | https://arxiv.org/abs/2311.04912 |