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NWB 2.0 Beta Released

Post Series: nwb-n

A first public beta release of NWB:N 2.0 is available for SfN. The intent of this beta release is to enable early adopters to start exploring the new software and format. In particular, this release includes a first beta release of PyNWB, an advanced new Python data API for NWB:N with support for Python 2.7.x and >3.5. A new Matlab API is also under development and available for early adopters.

While development on NWB:N 2.0 has been progressing rapidly, further changes to the APIs as well as the format are still planed between this beta and the first full release of NWB:N 2.0. A full release of NWB:N 2.0 is planned for Spring/Summer 2018. The NWB:N project includes a number of technical areas with regard to development of the: 1) specification language, 2) format schema, 3) data storage, and 4) data APIs. The SfN poster by Ruebel and Tritt et. al. provides a high-level overview of the new software architecture and different aspects of NWB:N 2.0-beta (see here). Detailed documentation of the various aspects of the NWB:N project is available online at:

The sources of PyNWB, MatNWB, and the format schema are also available online on GitHub via the NWB GitHub organization at https://github.com/NeurodataWithoutBorders .

Development of NWB:N 2.0-beta has been led by Kristofer Bouchard, Oliver Ruebel, and Andrew Tritt (LBNL) as part of the NWB-4-HPC project funded by the Kavli Foundation and in close collaboration with the NWB Executive Board and the broader NWB:N community. The growing NWB:N community has also contributed substantially to the NWB:N 2.0-beta release. For example, the Kitware team (consisting of J.-C. Fillion-Robin, D. Ozturk, C. Kofila, M. Grauer, W. Schroeder) have helped design and establish in collaboration with A. Tritt and O. Ruebel modern, open-source software processes for PyNWB. N. Clack and L. Niu (Vidriotech) with support by K. Svoboda (Janelia Farms HHMI) and in collaboration with A. Tritt and O. Ruebel are developing with MatNWB the new Matlab API for NWB:N. The Allen Institute for Brain Science team (including L. Ng, N. Cain, D. Feng, J. Kiggins) have contributed to the design of NWB:N 2.0, port to Python 2, and legacy read support for the Allen Brain Observatory dataset. The broader community has also contributed to NWB 2.0-beta as part of the NWB Hackathon that was held at HHMI Janelia earlier this year, as well as via GitHub issues, the NWB:N Slack channel, and countless emails and telecons.

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