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.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵* equal contributors;
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The authors have updated the manuscript to: 1) provide more technical details and clarifying the conceptual and technical innovations relative to previous technologies and how these innovations enable researchers to share data in compliance with FAIR principles with the community and foster collaboration, 2) provide more details on examples demonstrating the utility of NWB to harmoniously store diverse neurophysiology data types 3) discuss more clearly the short-term advantages for individual researchers, especially those generating data, of adopting NWB towards broader adoption 4) clarify text and language where appropriate
