Event Abstract

XCEDE-DM: A neuroimaging extension to the W3C provenance data model

  • 1 Massachusetts Institute of Technology, United States
  • 2 Integrated Brain Imaging Center, University of Washington, Seattle, WA, United States
  • 3 Brain Imaging and Analysis Center, Duke University, Durham, NC, United States
  • 4 Columbia University, New York, NY, United States
  • 5 Department of Psychiatry and Human Behavior, Department of Computer Science; University of California, Irvine, United States

Sharing, querying, and analyzing neuroimaging data requires a standard description that provides information applicable to data reuse and exchange. Analysis tools and databases that can expose and consume data using a standard model become interoperable and thus more accessible to researchers. To date, data models have focused on a hierarchical syntax that maps well to the relational database world; however, the heterogeneous schemas utilized by neuroimaging databases (e.g., HID, IDA, LORIS, XNAT) have required significant data integration efforts; for example, complex mediators [1] to map schemas, rewrite database specific queries, and retrieve results across systems. The results from such systems conform to a schema, and in the case of mapping between XNAT and HID, query results are returned using XCEDE [2] formatted data. XCEDE serves as a specification for the exchange of scientific data between databases, analysis tools, and web services. It provides a structured metadata hierarchy for storing information relevant to various aspects of an experiment (e.g., project, subject, etc.) along with derived data and provenance. 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 [3], 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. References 1. Ashish et al. (2010) Neuroscience Data Integration through Mediation: An (F) BIRN Case Study. Front. Neuroinform. doi: http://dx.doi.org/10.3389/fninf.2010.00118 2. Gadde et al. (2012) XCEDE: an extensible schema for biomedical data. Neuroinformatics. doi:10.1007/s12021-011-9119-9 3. http://www.w3.org/TR/prov-dm

Keywords: General neuroinformatics

Conference: 5th INCF Congress of Neuroinformatics, Munich, Germany, 10 Sep - 12 Sep, 2012.

Presentation Type: Poster

Topic: Neuroinformatics

Citation: Ghosh S, Nichols N, Gadde S, Steffener J and Keator D (2013). XCEDE-DM: A neuroimaging extension to the W3C provenance data model. Front. Neuroinform. Conference Abstract: 5th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2013.08.00007

Received: 21 Mar 2013; Published Online: 27 Nov 2013.

* Correspondence: Dr. Satrajit Ghosh, Massachusetts Institute of Technology, Cambridge, United States, satra@mit.edu

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