期刊
NEUROIMAGE
卷 82, 期 -, 页码 647-661出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2013.05.094
关键词
XCEDE; Provenance; Data model; Neuroimaging; Database; Web services
资金
- Function Biomedical Informatics Research Network [NIH 1 U24 U24 RR021992]
- BIRN Coordinating Center [NIH 1 U24 RR025736-01]
- International Neuroinformatics Coordinating Facility
- National Academies Keck Futures Initiative
- [RC4 NS073008-01]
- Division Of Integrative Organismal Systems
- Direct For Biological Sciences [1120912] Funding Source: National Science Foundation
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. Published by Elsevier Inc.
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