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Neurodata Without Borders Wins 2019 R&D100 Award

Efficient, standardized mechanisms for storing, analyzing, and sharing data enable brain research worldwide, accelerating the pace of scientific discovery.

October 29, 2019 — The Neurodata Without Borders: Neurophysiology (NWB:N) project has been selected for a 2019 R&D100 Award by R&D World magazine. The R&D 100 Awards have served as one of the most prestigious innovation awards programs for the past 56 years, honoring great R&D pioneers and revolutionary ideas in science and technology. 

Originally launched in 2014, NWB:N is a data standard for neurophysiology research that provides neuroscientists with a software ecosystem that enables scientists to share, archive, use, and build tools for analyzing data, ensuring the success of brain research worldwide and accelerating the pace of scientific discovery.

Understanding how the brain works and gives rise to thoughts, memories, perception, and consciousness remains one of the greatest challenges in science. To tackle this challenge, neurophysiologists run experiments that measure neuronal activity from different parts of the brain and relate that activity to sensation and behavior. These experiments generate large, complex, and diverse datasets at terabyte scale, and the size and complexity of these datasets are expected to grow significantly under recent global investments in neuroscience research, such as the BRAIN Initiative and the E.U. Human Brain Project.

With this massive growth of data comes the need for efficient, standardized mechanisms for storing, analyzing, and sharing data. Unlike other fields, such as genetics and astronomy, neurophysiology has not had a standard data format. This has made collaboration across laboratories inefficient, direct comparison of findings difficult, and re-use of rich data almost impossible, significantly slowing overall progress in the field.

To address this challenge, researchers from Lawrence Berkeley National Laboratory (LBNL), the Allen Institute, Vidrio Technologies, UC Berkeley, UC San Francisco, Howard Hughes Medical Institute (HHMI), and the broader research community developed NWB:N, which enables the re-use of data, facilitates collaboration across laboratories, and makes high performance computing easily accessible to neuroscientific research. 

“NWB fills a critical gap in the neuroscience research community by providing not only a data standard but a rich software ecosystem surrounding the standard,” said Oliver Rübel, a staff scientist at LBNL and NWB principal investigator. “Unlike other data formats, NWB is open-source, free to use, supports the full scope of neurophysiology experiments, and is optimized for storing and analyzing the increasingly large datasets being generated today,” said Andrew Tritt, chief software architect of the PyNWB Python API for NWB. 

“The lack of a standard format makes it tedious for neuroscientists to share data with collaborators and re-use data across studies, such that most do not even try. As neuroscientists adopt NWB, we expect the pace of scientific discovery to accelerate,” says Ryan Ly, a core developer of NWB. “A main focus of NWB has always been the users. In particular since the release of NWB:N 2.0 in January 2019, a main focus of our efforts has been to work with neuroscience labs and tool developers to help them adopt and integrate NWB,” said Benjamin Dichter, who is being supported via a subcontract with LBNL funded by the Kavli Foundation as a community liaison for NWB. 

We would like to thank the whole NWB 2.0 development team at LBNL, the Allen Institute for Brain Science, and Vidrio Technologies, the executive board, and our sponsors from The Kavli Foundation, the Simons Foundation, HHMI, and the National Institutes of Health. We would also like to thank all of the members of the NWB 1.0 pilot project (see here for a brief overview and history of NWB). And finally, we want to give a special thanks to all of our users! Without our great community, this would have not been possible. Learn more about NWB at!

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