Toward Community-Driven Big Open Brain Science: Open Big Data and Tools for Structure, Function, and Genetics
Charles AS, Falk B, Turner N, Pereira TD, Tward D, Pedigo BD, Chung J, Burns R, Ghosh SS, Kebschull JM, Silversmith W, Vogelstein JT
Identifiers and access
- DOI
- 10.1146/annurev-neuro-100119-110036
- PubMed
- 32283996
- PMC
- PMC9119703
- Cited by
- 19
Key findings
This perspective argues that fully exploiting growing big-brain-science data requires explicit, concerted investment in community-driven analysis tools that span modalities, scales, and previously siloed communities — democratising brain science across structure, function, and genetics.
Abstract
Source: pubmed
As acquiring bigger data becomes easier in experimental brain science, computational and statistical brain science must achieve similar advances to fully capitalize on these data. Tackling these problems will benefit from a more explicit and concerted effort to work together. Specifically, brain science can be further democratized by harnessing the power of community-driven tools, which both are built by and benefit from many different people with different backgrounds and expertise. This perspective can be applied across modalities and scales and enables collaborations across previously siloed communities.
Topics
- open-data-standards
- reproducibility-tooling
Lab authors
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