News & Updates
Search Research Content
Resource Finder at Kennedy Krieger Institute
A free resource that provides access to information and support for individuals and families living with developmental disabilities.
Towards structured sharing of raw and derived neuroimaging data across existing resources.
|Title||Towards structured sharing of raw and derived neuroimaging data across existing resources.|
|Publication Type||Journal Article|
|Year of Publication||2013|
|Authors||Keator DB, Helmer K, Steffener J, Turner JA, Van Erp TGM, Gadde S, Ashish N, Burns GA, Nichols BN|
|Date Published||2013 Nov 15|
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.