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NWB: Neurophysiology

In neuroscience, unlike in the fields such as genetics and cell biology, for example, there is no standardized way to collect and share the wealth of existing data among researchers. The lack of a common format has made comparison across laboratories difficult and replication of specific experiments almost impossible, significantly slowing overall progress in the field.

Launched in mid 2014, Neurodata Without Borders: Neurophysiology is a pilot project to produce a unified data format for cellular-based neurophysiology data. The common data format is based on representative use case studies from four laboratories, and the project includes a vetting phase for assessing whether other data models can also be used in the new common format.

The project will share not only the NWB format, but also high-value data sets that have been translated into the new format, as well as a collection of application programming interfaces (APIs) for reading and writing the data.

Neurodata Without Borders: Neurophysiology is intended to serve the broad neuroscience community and encourage the sharing of data by scientists worldwide.

The NWB Format

The resulting “NWB” format is designed to be flexible enough to incorporate several kinds of data, including electrophysiological and optical physiology data, and to include complex metadata related to stimuli and behavior.

A beta version of the format is now available, please give it a try. Join our mailing list for updates.

Goals & Values of the NWB Format

Improve data presentation and distribution.

To achieve scientific breakthroughs, today’s increasingly complex scientific findings require effortless dissemination of new data and appropriate tools to view and utilize that data (i.e. APIs, software). The presentation, packaging and distribution of large, complex data sets, particularly the high-dimensional datasets coming out of modern neurophysiology experiments, must be less regimented and more nimble. A common data format is a requirement for facilitating this process.

Support cross-validation and reproducibility.

Often key results in the field cannot be reproduced. Reexamination of the original data, facilitated by a common data format, can clear up confusion and minimize uncertainties.

Encourage best practices.

Well-considered procedures for collecting and storing the relevant metadata will be designed and implemented.

Facilitate and expedite discovery.

Experimentalists are often not equipped to extract and interpret all, or even the most important, meanings from the mountains of data being collected. Pooling and sharing the massive and complex data sets being generated today will enable scientists to expedite analyses and produce discoveries more efficiently. facilitated This will be enabled by a common data format.

Share analysis tools.

Many laboratories are developing powerful analysis software. A major impediment to share these tools has been incompatibilities between data models, a problem resolved by a common data format.

Create vital new collaborations with other fields.

A common data format will enable computational researchers and developers of new data mining techniques to seamlessly enter and participate in neuroscience research.