The Neurodata Without Borders ecosystem for neurophysiological data science.
Oliver Rübel, Andrew Tritt, Ryan Ly, Benjamin K Dichter, Satrajit Ghosh, Lawrence Niu, Pamela Baker, Ivan Soltesz, Lydia Ng, Karel Svoboda, Loren Frank, Kristofer E Bouchard
Author Information
Oliver Rübel: Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, United States. ORCID
Andrew Tritt: Applied Mathematics and Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, United States.
Ryan Ly: Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, United States. ORCID
Benjamin K Dichter: CatalystNeuro, Benicia, United States.
Satrajit Ghosh: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States. ORCID
Lawrence Niu: MBF Bioscience, Ashburn, United States.
Pamela Baker: Allen Institute for Brain Science, Seattle, United States.
Ivan Soltesz: Department of Neurosurgery, Stanford University, Stanford, United States.
Lydia Ng: Allen Institute for Brain Science, Seattle, United States.
Karel Svoboda: Allen Institute for Brain Science, Seattle, United States.
Loren Frank: Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States.
Kristofer E Bouchard: Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, United States. ORCID
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.
