Event Abstract

Neuroimaging Data Access and Query through a Common Application Programming Interface

  • 1 Integrated Brain Imaging Center, University of Washington, Seattle, WA, USA
  • 2 University of Massachusetts Medical School, Worcester, MA, United States
  • 3 Neurospin-I2BM-CEA, Gif sur Yvette, France
  • 4 McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States

A large number of databases are developed to store and manage human neuroimaging data. While individual neuroscience databases provide mechanisms to query and download information within a given framework (e.g., Allen Institute, COINS, HID, IDA, LORIS, NIMS, XNAT), there is no standardized way to programmatically access related information stored in these heterogeneous systems. Creating a data exchange layer with a common interface to access and query shared brain imaging data will enable the development of interoperable client applications capable of consuming resources available across disparate brain imaging data management systems.

We present a preliminary application programming interface (API) for providing uniform access to neuroimaging databases. Conceptually, the API is a service for accessing common entities (e.g., project, subject) and their relationships (e.g., subject wasAssociatedWith project) specified by the XCEDE data model [1] and defined in a lexicon [2]. Neuroimaging databases conforming to the API implement a mapping of their local resources to XCEDE entities and provide a mechanism to request resources. The API is not tied to a specific language or technology, but for web-accessible databases, REST is a natural fit. For example, a REST implementation of the API would respond to an HTTP request for a Subject URI (e.g., www.example.com/xcede_query/subject?uri={uri}) by listing the relationship and URI of related entiies (e.g, {wasAssociatedWith: projectURI} ). The response to an API request can return XCEDE XML or another format (e.g., JSON, RDF) conforming to the XCEDE data model [1].

Discussions with the developers of many neuroimaging databases are helping to refine this specification, and existing tools will speed the first implementation of the API [3]. Our goal is that in the near future, existing databases and those under development will implement this protocol and expose existing and newly acquired datasets in a common data access framework. This work was conducted with the Neuroimaging Task Force of the INCF Program on Standards for Datasharing. References [1] Gadde et al. 2012. XCEDE: an extensible schema for biomedical data. Neuroinformatics.doi:10.1007/s12021-011-9119-9 [2] Bug et al. 2008. The NIFSTD and BIRNLex Vocabularies: Building Comprehensive Ontologies for Neuroscience. Neuroinformatics.doi:10.1007/s12021-008-9032-z [3] Schwartz et al. 2012. PyXNAT: xnat in python. Front. Neuroinform.doi:10.3389/fninf.2012.00012

Keywords: Infrastructural and portal services, Neuroimaging, data storage, Neuroscience, standardization

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

Presentation Type: Poster

Topic: Neuroinformatics

Citation: Nichols B, Haselgrove C, Poline J and Ghosh S (2014). Neuroimaging Data Access and Query through a Common Application Programming Interface. Front. Neuroinform. Conference Abstract: 5th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2014.08.00100

Received: 21 Mar 2013; Published Online: 27 Feb 2014.

* Correspondence: Dr. B. Nolan Nichols, Integrated Brain Imaging Center, University of Washington, Seattle, WA, Seattle, USA, nolan.nichols@gmail.com

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