XCEDE-DM: A neuroimaging extension to the W3C provenance data model
Satrajit Ghosh (Massachusetts Institute of Technology), Nolan Nichols (Integrated Brain Imaging Center, University of Washington, Seattle, WA), Syam Gadde (Brain Imaging and Analysis Center, Duke University, Durham, NC), Jason Steffener (Columbia University, New York, NY), David Keator (Department of Psychiatry and Human Behavior, Department of Computer Science; University of California, Irvine)
XCEDE-DM abstracts the implicit hierarchical data model described by the XCEDE schema into a technology agnostic syntax, which can then be serialized (e.g., into XML, JSON, RDF, etc.). Further, explicit data modeling facilitates broader use of web service specifications and database mediation services by defining a reusable representation of objects and their relationships, rather than re-creating new models for every data sharing activity. XCEDE-DM is derived from the W3C PROV model , captures provenance not as an afterthought but as explicitly modeled relationships between entities, activities and agents, and is related to other INCF efforts defining a common query api and lexicon for neuroimaging. XCEDE-DM can capture complete details of a neuroimaging process including people and their roles, acquisition and analyses. Although we focus on neuroimaging, the model is applicable to the entire domain of neuroinformatics.
This work was conducted with the Neuroimaging Task Force of the INCF Program on Standards for Datasharing.
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