Data sharing efforts increasingly contribute to the acceleration of
scientific discovery. Neuroimaging data is accumulating in distributed
domain-specific databases and there is currently no integrated access mechanism
nor an accepted format for the critically important meta-data that is necessary
for making use of the combined, available neuroimaging data. In this
manuscript, we present work from the Derived Data Working Group, an open-access
group sponsored by the Biomedical Informatics Research Network (BIRN) and the
International Neuroimaging Coordinating Facility (INCF) focused on practical
tools for distributed access to neuroimaging data. The working group develops
models and tools facilitating the structured interchange of neuroimaging
meta-data and is making progress towards a unified set of tools for such data
and meta-data exchange. We report on the key components required for integrated
access to raw and derived neuroimaging data as well as associated meta-data and
provenance across neuroimaging resources. The components include (1) a
structured terminology that provides semantic context to data, (2) a formal
data model for neuroimaging with robust tracking of data provenance, (3) a web
service-based application programming interface (API) that provides a
consistent mechanism to access and query the data model, and (4) a provenance
library that can be used for the extraction of provenance data by image
analysts and imaging software developers. We believe that the framework and set
of tools outlined in this manuscript have great potential for solving many of
the issues the neuroimaging community faces when sharing raw and derived
neuroimaging data across the various existing database systems for the purpose
of accelerating scientific discovery
