Keywords: Data Archive, Neuroimaging, Database, Open Data, MRI, PET, MEG, EEG, iEEG
Resource ID: SCR_005031
A free and open platform for validating and sharing BIDS-compliant MRI, PET, MEG, EEG, and iEEG data
OpenNeuro is a 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. Uploaded datasets are made available with minimal restrictions to the public at large, in order to permit maximal reuse. OpenNeuro accepts datasets formatted according to the Brain Imaging Data Structure (BIDS) standard, a community-developed standard that aims to achieve broad coverage of neuroimaging data types while unifying metadata.
* OpenNeuro is designed to make sharing raw imaging datasets as easy as possible, to maximize the potential for reuse and re-analysis.
* Leveraging the BIDS standard for data validation and metadata extraction, OpenNeuro provides a rich view of each dataset, as well as viewing files within the browser.
* Data are versioned using modern research data management (RDM) tools, and persistent digital object identifiers (DOIs) are generated for every version of the dataset.
* Data are made accessible through multiple open protocols, ensuring high availability and resiliency.
* Datasets may be embargoed for 36 months. Multiple collaborators can be given write access, and anonymous review links can provide read-only access to peer reviewers.
* Dataset authors may upload datasets of any size, for example as consortia contributing to a data commons or lab PIs desiring transparency.
* Users may search for datasets according to criteria such as name, participant demographics, imaging modality or task, and retrieve all or parts of the datasets programmatically.
* Reviewers may comment on datasets, requesting clarification or suggesting improvements in metadata, to ensure datasets are correctly interpreted.
* Third-party metadata indexers may combine OpenNeuro metadata with other repositories to provide novel search and query infrastructure.
* Upload your dataset to OpenNeuro, and generate a citable DOI to include in a manuscript. While the dataset remains private, provide a reviewer link along with your journal submission. Mark the dataset as public at the same time as the final journal article.
* During peer review, request that the authors make their data and code available for validation. Using an anonymous reviewer link on OpenNeuro, identify issues with the data quality or metadata accuracy. Suggest changes to the authors, who can create a new version with a new DOI.
* Collect multiple OpenNeuro datasets matching a cohort and task of interest. Pre-process using a common pipeline to minimize variation and perform an mega-analysis.
* Open licensing (CC0) of datasets ensures maximum reusability.
* Reliance on the BIDS validator ensures higher metadata consistency across datasets.
* Automated validation using the BIDS validator enables researchers to test their dataset prior to upload.
* Datasets that cannot be shared openly are not currently supported.
* Uploaded datasets must be formatted according to the Brain Imaging Data Structure (BIDS; https://bids.neuroimaging.io) standard and released under a CC0 public domain license.
CJ Markiewicz, 2021, “The OpenNeuro resource for sharing of neuroscience data,” eLife, DOI: https://doi.org/10.7554/eLife.71774
Russell Poldrack, Professor
Stanford University, Stanford, CA, USA
TEAM / COLLABORATOR(S)
Adam Thomas, Team Director, National Institute of Mental Health
Anthony Galassi, Software Engineer, National Institute of Mental Health
Christopher Markiewicz, Software Developer, Stanford University
Melanie Ganz-Benjaminsen, Associate Professor, University of Copenhagen
Nell Hardcastle, Software Developer, Stanford University
Robert Innis, Principal Investigator, National Institute of Mental Health
Ross Blair, Software Developer, Stanford University
* NIMH 5R24MH117179