Brain function is produced by the coordinated activity of multiple neuronal types that are widely distributed across many brain regions. Neuronal signals are acquired using extra- and intracellular recordings, and increasingly optical imaging, during sensory, motor, and cognitive tasks. Neurophysiology research generates large, complex, heterogeneous datasets at terabyte scale. The data size and complexity is expected to continue to grow with the increasing sophistication of experimental apparatus. Lack of standards for neurophysiology data and related metadata is the single greatest impediment to fully extracting return-on- investment from neurophysiology experiments, impeding interchange and reuse of data and reproduction of derived conclusions. This gap motivates the launch of Neurodata Without Borders (NWB:N). The goal of NWB:N is to develop a standardized format and methods for neurophysiology data and metadata. Following a successful pilot, initial efforts have begun on the second phase. Using modern software engineering principles, a beta NWB:2.0 has been developed with a new modular software architecture and APIs that enable users to efficiently interact with the NWB:N data format, format files, and specifications. However, despite the innovations substantial software development remains to fully deliver on the promise of NWB:N. Based on the foundations of NWB:N, the goal of this project is to develop a next generation data format and software ecosystem to enable standardization, sharing, and reuse of neurophysiology data and analyses, enhancing discovery and reproducibility. To achieve this goal we will: 1) develop and maintain an accessible and sustainable open source software ecosystem for NWB:N, 2) design methods for integration of controlled vocabularies, provenance and modeling of data relationships to make data findable, interpretable, and (re)usable, and 3) develop tools for facilitating community adoption, extension, and curation of NWB:N for integration of new use cases.
The single greatest impediment to fully extracting return on investment into neurophysiology data collection is the lack of standards for neurophysiology data and related metadata to enable broad reproduction, interchange, and reuse. The goal of this project is to develop based on the existing Neurodata Without Borders (NWB:N) format a standardized format and methods for neurophysiology data and metadata. To achieve this goal we will: 1) develop and maintain an accessible and sustainable open source software ecosystem for NWB:N, 2) design methods for integration of controlled vocabularies, provenance and modeling of data relationships to make data findable, interpretable, and (re)usable, and 3) develop tools for facilitating community adoption, extension, and curation of NWB:N for integration of new use cases.
