The effective sharing of data requires the development and broad adoption of standards for the organization of data and metadata. Within the field of neuroimaging, there is an emerging standard for data/metadata organization, the Brain Imaging Data Structure (BIDS), which is currently implemented for MRI and is under development for PET and MEG. This standard provides the basis for organization and sharing of raw data for a broad subset of projects funded by the BRAIN Initiative. In the present project we propose to extend and expand the BIDS framework to the description and organization of data/metadata that are derived from these raw data, which we refer to generally as derivatives. This will provide the ability for researchers to share processed data, statistical models and results, and computational modeling results in a way that ensures their usability.
Data sharing is essential for transparent and reproducible research, but shared data are only useful if they are described in a way that every user can easily understand. We propose to extend the Brain Imaging Data Structure (BIDS), which provides a framework for organizing and describing raw neuroimaging data, to encompass other forms of processed data and the statistical/computational models that are applied to those data. This framework will greatly increase the usefulness of data generated as part of the BRAIN Initiative.
