Neurodata Without Borders Project Hosts User/Developer Hackathons
June 3, 2019
A workshop sponsored by the Neurodata Without Borders: Neurophysiology project (NWB:N) brought together the experimental neurophysiology community to further the adoption and development of NWB:N, the NWB:N software libraries, and the scientific workflows that rely on NWB:N. The 6th NWB:N Developer Hackathon and User Days event was held May 13-16 at the HHMI Janelia Research Campus in Ashburn, VA. Attending from Lawrence Berkeley National Laboratory were Oliver Ruebel, Andrew Tritt, and Ryan Ly from the Computational Research Division, Vyassa Baratham with the Neural Systems and Data Science Lab at Berkeley Lab, as well as Ben Dichter who is working as a consultant with Berkeley Lab.
NWB:N is an effort to standardize the description and storage of neurophysiology data and metadata by enabling data sharing and reuse and reducing barriers to applying data analytics within and across research facilities.
During the hackathon, 43 users and developers from 29 different major labs and research institutions attended the event, where they exchanged ideas and best practices for using NWB:N and the libraries, shared NWB:N based tools, discussed common needs, solved bugs, made feature requests, and brainstormed about future funding and collaboration. The event also gave NWB:N developers and users the opportunity to interact and facilitate communication, gather requirements, and train users.
"With the recent release of NWB:N 2.0 in January, the hackathon was central to allow us to engage with new users and developers,” said Reubel, who, along with Dichter, organized the meeting. “The event helped give the community a lot of cohesion and momentum and is an exciting sign for future developments."
The first two days of the meeting focused on user training and use cases, while the second two days focused on core development. For the user days program, the hackathon brought together experts from the neuroscience research community to learn about NWB:N and to work on projects towards adoption of NWB:N for their lab’s data sharing and analysis needs. Users worked on integrating data from 14+ different labs and institutions with NWB:N, involving data from a broad range of data modalities, including electrophysiology (extracellular recordings, intracellular recordings, and electrocorticography), optophysiology (2-photon imaging, fluorescent wide-field images, etc.), behavioral data, processed data (e.g., from spike sorting), neural simulations (using NEURON software), stimulus data, and trial-based data. The user projects also included data from a number of different model species, such as mice, rats, monkeys, and humans.
During the developer days, developers from the neuroinformatics community worked to integrate NWB:N with data analysis, visualization, storage, and management tools as well as to discuss and design new features for NWB:N and build and improve core NWB:N infrastructure. This program focused on open hacking sessions to support interaction between developers and focused development combined with developer breakout sessions. The hackathon projects focused on integrating NWB:N with data analysis, visualization, storage, and management software and development and enhancement of core NWB:N technologies. The developers program saw substantial progress toward integration of NWB:N with important data analysis tools, including Brainstorm, CaImAn, RAVE, NWBWidgets, and the NWBExplorer as part of Open Source Brain. To enable users to more easily discover tools that support NWB:N, an Analysis and Visualization Tools page has been added to the NWB:N website.
"We have been working on NWB:N for over two years,” Tritt said. “It was exciting to see the enthusiasm of the user and developer community to use NWB:N."
Several early adopters — including the Allen Institute for Brain Science, the FrankLab (UCSF), and Buzsaki Lab (NYU) — have already made first sets of NWB:N data files available to the public and several other labs have indicated plans for upcoming data releases in NWB:N 2.0 (see NWB:N Example Data website).
Development of NWB:N at Berkeley Lab is currently being supported via the NIH BRAIN Initiative grant 1R24MH116922-01 led by Ruebel, together with Lydia Ng from the Allen Institute for Brain Science.
About Computing Sciences at Berkeley Lab
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