The OpenNeuro resource for sharing of neuroscience data
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Evaluation Summary:
This manuscript describes the OpenNeuro data sharing platform, which is built upon the Brain Imaging Data Structure (BIDS). More than 500 data sets are stored in BIDS, following the FAIR principles, and integrated with data analysis tools. This is a highly important resource for the neuroimaging community, and the shared data sets have already been used in basic neuroscience and for methods development.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1, Reviewer #2 and Reviewer #3 agreed to share their names with the authors.)
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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.
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Author Response:
Reviewer #3 (Public Review):
This is a well-written paper describing the OpenNeuro data archive. OpenNeuro covers diverse mesoscale brain imaging data (fMRI, PET, etc) from many projects and including multiple experimental paradigms. The focus is on human imaging, but primate and rodent data are also represented. The project rests on a standardized and relatively mature Data format (BIDS) for imaging data. This is key to implementing FAIR principles and automated checking for compliance. OpenNeuro is already producing discoveries that could not have been made without meta-analysis across diverse data sets. OpenNeuro is also used to improve data analysis pipelines. By its nature, this kind of paper always reads a bit like an advertisement.
The paper makes a compelling case for domain-specific repositories supported …
Author Response:
Reviewer #3 (Public Review):
This is a well-written paper describing the OpenNeuro data archive. OpenNeuro covers diverse mesoscale brain imaging data (fMRI, PET, etc) from many projects and including multiple experimental paradigms. The focus is on human imaging, but primate and rodent data are also represented. The project rests on a standardized and relatively mature Data format (BIDS) for imaging data. This is key to implementing FAIR principles and automated checking for compliance. OpenNeuro is already producing discoveries that could not have been made without meta-analysis across diverse data sets. OpenNeuro is also used to improve data analysis pipelines. By its nature, this kind of paper always reads a bit like an advertisement.
The paper makes a compelling case for domain-specific repositories supported by a modern cloud architecture and sound computer science. I appreciate the discussion of the challenges that have been overcome (e.g. versioning of data sets; privacy and consent) and others that are looming (e.g. long-term maintenance in the absence of obvious commercial drivers).
I would like to see a bit more comparison to other archives, including some mature projects in other fields (e.g. astronomy, IVOA; structural molecular biology; CCDC), as well and more nascent efforts in brain research (e.g. DANDI; BIL).
Rather than focus on direct comparisons to other archives, we have focused on the FAIR principles for data management. We also feel that, in an article highlighting OpenNeuro, it could be seen as bad form to compare critically to other databases, rather than letting the merits of OpenNeuro stand on their own.
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Evaluation Summary:
This manuscript describes the OpenNeuro data sharing platform, which is built upon the Brain Imaging Data Structure (BIDS). More than 500 data sets are stored in BIDS, following the FAIR principles, and integrated with data analysis tools. This is a highly important resource for the neuroimaging community, and the shared data sets have already been used in basic neuroscience and for methods development.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1, Reviewer #2 and Reviewer #3 agreed to share their names with the authors.)
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Reviewer #1 (Public Review):
Markiewicz et al. describe the principles, history and technological building blocks of the OpenNeuro neuroimaging data sharing platform. In addition, Markiewicz et al., provide data on OpenNeuro growth in terms of data uploaded, data downloaded and publications re-using OpenNeuro data, all of which are extremely impressive. They convincingly argue for the importance of minimizing data sharing restrictions, while rigorously maintaining data safety. They describe the origins of the BIDS standard and provide arguments for its critical importance to data sharing. They conclude with discussing OpenNeuro's limitations, the funding challenges faced in maintaining it and future directions. The article makes it clear that OpenNeuro and the accompanying BIDS standard are critically important for the success of …
Reviewer #1 (Public Review):
Markiewicz et al. describe the principles, history and technological building blocks of the OpenNeuro neuroimaging data sharing platform. In addition, Markiewicz et al., provide data on OpenNeuro growth in terms of data uploaded, data downloaded and publications re-using OpenNeuro data, all of which are extremely impressive. They convincingly argue for the importance of minimizing data sharing restrictions, while rigorously maintaining data safety. They describe the origins of the BIDS standard and provide arguments for its critical importance to data sharing. They conclude with discussing OpenNeuro's limitations, the funding challenges faced in maintaining it and future directions. The article makes it clear that OpenNeuro and the accompanying BIDS standard are critically important for the success of neuroimaging research and that without it, neuroimaging will not, cannot progress. In summary, this article describing OpenNeuro and BIDS provides fuel for the belief that neuroimaging research will emerge from its reproducibility crisis, strengthened, modernized and more open.
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Reviewer #2 (Public Review):
• This work sets the standard for data sharing and management resources in neuroimaging and could become the dominant standard resource in the field. Challenges to this aspiration are the high degree of decentralization and poor present organization, large size of these datasets. The authors have profited from Amazon's program of freely sharing not for profit public data sets, but this will scale as OpenNeuro becomes for widely used is less clear.
• Comparing with other major imaging databases such as ADNI this resource is clearly the direction the field should go. The authors and developers have taken a truly open science approach.
• The BIDS standard is important and as part of the backbone of OpenNeuro perhaps somewhat more description of how it is used in OpenNeuro would be important and interesting to …Reviewer #2 (Public Review):
• This work sets the standard for data sharing and management resources in neuroimaging and could become the dominant standard resource in the field. Challenges to this aspiration are the high degree of decentralization and poor present organization, large size of these datasets. The authors have profited from Amazon's program of freely sharing not for profit public data sets, but this will scale as OpenNeuro becomes for widely used is less clear.
• Comparing with other major imaging databases such as ADNI this resource is clearly the direction the field should go. The authors and developers have taken a truly open science approach.
• The BIDS standard is important and as part of the backbone of OpenNeuro perhaps somewhat more description of how it is used in OpenNeuro would be important and interesting to readers, particularly that thousands of datasets even outside of this resource use it.
• The description and implementation FAIR principles is well described and clear, and important part of paper. -
Reviewer #3 (Public Review):
This is a well-written paper describing the OpenNeuro data archive. OpenNeuro covers diverse mesoscale brain imaging data (fMRI, PET, etc) from many projects and including multiple experimental paradigms. The focus is on human imaging, but primate and rodent data are also represented. The project rests on a standardized and relatively mature Data format (BIDS) for imaging data. This is key to implementing FAIR principles and automated checking for compliance. OpenNeuro is already producing discoveries that could not have been made without meta-analysis across diverse data sets. OpenNeuro is also used to improve data analysis pipelines. By its nature, this kind of paper always reads a bit like an advertisement.
The paper makes a compelling case for domain-specific repositories supported by a modern cloud …
Reviewer #3 (Public Review):
This is a well-written paper describing the OpenNeuro data archive. OpenNeuro covers diverse mesoscale brain imaging data (fMRI, PET, etc) from many projects and including multiple experimental paradigms. The focus is on human imaging, but primate and rodent data are also represented. The project rests on a standardized and relatively mature Data format (BIDS) for imaging data. This is key to implementing FAIR principles and automated checking for compliance. OpenNeuro is already producing discoveries that could not have been made without meta-analysis across diverse data sets. OpenNeuro is also used to improve data analysis pipelines. By its nature, this kind of paper always reads a bit like an advertisement.
The paper makes a compelling case for domain-specific repositories supported by a modern cloud architecture and sound computer science. I appreciate the discussion of the challenges that have been overcome (e.g. versioning of data sets; privacy and consent) and others that are looming (e.g. long-term maintenance in the absence of obvious commercial drivers).
I would like to see a bit more comparison to other archives, including some mature projects in other fields (e.g. astronomy, IVOA; structural molecular biology; CCDC), as well and more nascent efforts in brain research (e.g. DANDI; BIL).
Although OpenNeuro is a best-in-class archive with huge potential impact, similar archives operating with similar principles have operated for a while in other fields (e.g. astronomy; genomics etc). I thus wonder if the paper is of 'general interest'; i.e. of interest outside of the worlds of neuroimaging and those interested in data archives & data sharing in general. OpenNeuro is a pioneer in brain research and can function as a model for other subfields in neuroscience.
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