The Neurodata Without Borders ecosystem for neurophysiological data science

Author:

Rübel Oliver1ORCID,Tritt Andrew2,Ly Ryan1ORCID,Dichter Benjamin K3,Ghosh Satrajit45ORCID,Niu Lawrence6,Baker Pamela7,Soltesz Ivan8,Ng Lydia7,Svoboda Karel79,Frank Loren91011,Bouchard Kristofer E110121314ORCID

Affiliation:

1. Scientific Data Division, Lawrence Berkeley National Laboratory

2. Applied Mathematics and Computational Research Division, Lawrence Berkeley National Laboratory

3. CatalystNeuro

4. McGovern Institute for Brain Research, Massachusetts Institute of Technology

5. Department of Otolaryngology - Head and Neck Surgery, Harvard Medical School

6. MBF Bioscience

7. Allen Institute for Brain Science

8. Department of Neurosurgery, Stanford University

9. Janelia Research Campus, Howard Hughes Medical Institute

10. Kavli Institute for Fundamental Neuroscience

11. Departments of Physiology and Psychiatry University of California, San Francisco

12. Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory

13. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience, University of California, Berkeley

14. Weill Neurohub

Abstract

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB’s impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.

Funder

Kavli Foundation

National Institute of Mental Health

Howard Hughes Medical Institute

Simmons Family Foundation

National Institute of Neurological Disorders and Stroke

Weill Neurohub

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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