Efficient, standardized mechanisms for storing, analyzing, and sharing data enable brain research worldwide, accelerating the…
We are excited to announce the full release of Neurodata Without Borders: Neurophysiology version 2.0 (NWB:N 2.0). NWB:N is a data standard for neurophysiology, providing neuroscientists with a common standard to share, archive, use, and build common analysis tools for neurophysiology data. With NWB:N 2.0 we have made significant advances towards creating a usable standard, software ecosystem, and vibrant community for standardizing neurophysiology data. With PyNWB and MatNWB this release also includes advanced NWB:N-compliant data APIs for both Python and Matlab.
What is new in NWB:N 2.0? NWB:N 2.0 is more than just a file format; it defines an ecosystem of standards, tools, and methods for managing, storing, sharing, and analyzing complex neurophysiology data. As part of the NWB:N 2.0 project we have developed a modern, open software strategy and APIs for NWB:N, identified and implemented critical changes to the NWB:N data standard, and identified, created, and separated the core components of the NWB:N ecosystem (i.e., the specification language, standard schema, data storage, and data APIs). To provide an overview of the advances in the NWB:N 2.0 data schema, we have also published with this release a preprint of a first paper on NWB:N 2.0 .
What does this release mean for me? With this release the NWB:N 2.0 data schema is now considered final and stable. If you have been waiting with adopting NWB:N, now is the time to join the journey.
Where can I find NWB:N resources online? All resources around the NWB:N data standard are available via neurodatawithoutborders.github.io . This is your central technical resource for all documentation, software repositories, events and everything else NWB:N. NWB:N is open source; all our software is available via the NWB Github organization and we have open Slack and GoogleGroup channels. Please see our contributing guidelines for details on how to contribute to NWB:N. Finally, for a broader overview of the NeurodataWithoutBorders organization see also nwb.org .
Which upcoming events should I know about? On May 13-16, 2019 we are having a joint NWB:N developer hackathon and user meeting at the HHMI Janelia Research Campus in Ashburn, VA. The first two days (May 13-14) of the event will be devoted to the NWB:N User Days focused on user training and use cases. The second half of the meeting (May 15-16) will then be devoted to the NWB:N Developer Hackathon focused on core development. We are still in the early planning stages for the event. For now, reserve the date if you are planning to attend and stay tuned for future announcements. Space at the event will be limited. If you would like an invitation, then please let us know by completing the invitation request form by Feb 8, 2019. Further details regarding the event will be announced on the event website. We’ll also be at the upcoming 5th annual BRAIN Initiative investigators meeting in April.
How is development of NWB:N being supported? Development on NWB:N is currently funded via several projects by the Kavli foundation and NIH. The NWB:N Executive and Technical Advisory Boards together with our sponsors and project teams, play a central role in creating the vision for and enabling NWB:N to grow to become a widely accepted standard in neurophysiology.
Core development of the NWB:N standard and PyNWB is currently supported by the National Institute Of Mental Health of the National Institutes of Health under Award Number R24MH116922 to Oliver Rübel (LBNL) and L. Ng (Allen Institute for Brain Science). Development of data query and analysis tools and core NWB:N development is also being supported by the Simons Foundation for the Global Brain grant 521921 to L. Frank. Core development of NWB:N 2.0 has been supported by the Kavli foundation as part of the NWB4HPC project to K. Bouchard (LBNL).
Also, engagement with industry partners is central to our software strategy and to facilitate the creation of an advanced data science ecosystem for neurophysiology. Development of visualization tools and software processes is supported by NIH SBIR 5R44MH115731-02 to W. Schroeder (Kitware) and L. Ng (Allen Institute for Brain Science). Development of MatNWB is being led by Vidrio with supported by the Simons Foundation and HHMI. Also, Vathes is developing interfaces between DataJoint and NWB.
Who is using NWB:N? A central goal of NWB:N 2.0 is to work with the neuroscience community towards better science solutions. User, developer and application engagement are central to this mission. In April 2018, 65+ scientists from 20 major institutions attended the 4th NWB:N Hackathon at the Allen Institute for Brain Science and the 5th Hackathon and User Days at Lawrence Berkeley National Lab. We hope to repeat the great success of these events in our upcoming 6th NWB:N Hackathon and User Days at HHMI Janelia in May.
Many groups are already adopting NWB:N, including laboratories at UCSF, UCB, Caltech, LBNL, HHMI Janelia, and the Allen Institute for Brain Science, among others. The NWB:N teams are also actively engaging with NIH BRAIN Initiative projects and several U19 projects are in the process of adopting (e.g., U19-NS104590 to I. Soltesz) or are investigating adoption of NWB:N. To coordinate NWB:N efforts across the U19 projects the NWB:N Data Standards Subgroup has been created as part of the NIH BRAIN Initiative U19 Data Science Consortium . The Kavli foundation has also funded several seed grants to help select labs evaluate and adopt NWB:N and is sponsoring the creation of a NWB:N community liaison position.
Future development: With the release of NWB:N 2.0, we are looking forward to the next main phase of the NWB:N project. One main goal is to promote adoption of NWB:N 2.0 and to help neuroscience laboratories, projects, and data archives transition into using the standard. Another main goal is to develop new software tools that build upon NWB:N 2.0 including advanced query, analysis and visualization tools for NWB:N, integration of NWB:N with lab data management and data provenance, integration of controlled vocabularies and ontologies with NWB:N, and creation of standard mechanisms and tools for creating and sharing NWB:N extensions.
NWB:N would not be possible without the great support by our users and developers. We would like to thank the amazing NWB:N community and everyone that has contributed to NWB:N 2.0!
References: O. Ruebel, A. Tritt, B. Dichter, T. Braun, N. Cain, N. Clack, T. J. Davidson, M. Dougherty, J.-C. Fillion-Robin, N. Graddis, M. Grauer, J. T. Kiggins, L. Niu, D. Ozturk, W. Schroeder, I. Soltesz, F. T. Sommer, K. Svoboda, L. Ng, L. M. Frank, K. Bouchard, “NWB:N 2.0: An Accessible Data Standard for Neurophysiology,” January, 18, 2019, doi: https://doi.org/10.1101/523035 (Online Preprint)(PDF)