NIQuery: Neuroimaging Informatics Query Framework for Data Sharing, Discovery, and Analysis
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1
Integrated Brain Imaging Center, University of Washington, Seattle, WA, United States
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2
Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA, United States
Scientific discovery about the human brain will be accelerated by neuroinformatics services on the programmable web. Just as bioinformatics databases provide services for molecular data, a scalable service-oriented framework is needed to take advantage of the large number of human neuroimaging data sets now available online. We have developed a specification, NIQuery, for remote access to observation-level data in distributed and heterogeneous image-specialized databases. NIQuery integrates emerging open source standards for metadata description, access & query, and provides investigators with computational access to voxel-level data. The protocol supporting this functionality consists of: 1) a persistent Session object that wraps databases (e.g. XNAT[1], NIMS[2], Allen Institute[3]), exposes the NIQuery application programming interface, and serves objects and requests; 2) a Query object that provides a mechanism to interrogate databases with user defined and/or predefined web-accessible queries; 3) a Data object conforming to a supported 'image' data model (e.g., DICOM, NIfTI, etc.) that provides a mechanism to return pixel data to an application; and 4) a Workflow object through which a server provides a computational service on a Data object. A registry service (www.niquery.org) provides an index of available NIQuery servers, as well as the query, data, and workflow objects available on each server. NIQuery enables client applications to discover shared neuroimaging data using metadata-level distributed queries and then execute image processing workflows on discovered data at their source, on a cached copy in the cloud, or locally. A sample implementation of this framework involves exporting a snapshot of XNAT and NIMS databases into XCEDE XML files, indexing the snapshots with the NIQuery registry service, and remotely calculating quality control metrics on resting-state fMRI data. These informatics tools will support agile exploration and reuse of open access neuroimaging data. References 1. Marcus DS, Olsen TR, Ramaratnam M, Buckner RL. The Extensible Neuroimaging Archive Toolkit: an informatics platform for managing, exploring, and sharing neuroimaging data. Neuroinformatics. 2. Neurobiological Image Management System. http://github.com/cni/nims 3. Zeng H, et. al. 2012. Large-Scale Cellular-Resolution Gene Profiling in Human Neocortex Reveals Species-Specific Molecular Signatures. Cell.
Keywords:
General neuroinformatics
Conference:
5th INCF Congress of Neuroinformatics, Munich, Germany, 10 Sep - 12 Sep, 2012.
Presentation Type:
Poster
Topic:
Neuroinformatics
Citation:
Nichols
B,
Dougherty
R,
Detwiler
L,
Schaefer
G,
Frank
R,
Brinkley
J,
Wandell
B and
Grabowski
T
(2014). NIQuery: Neuroimaging Informatics Query Framework for Data Sharing, Discovery, and Analysis.
Front. Neuroinform.
Conference Abstract:
5th INCF Congress of Neuroinformatics.
doi: 10.3389/conf.fninf.2014.08.00124
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Received:
21 Mar 2013;
Published Online:
27 Feb 2014.
*
Correspondence:
Dr. B. Nolan Nichols, Integrated Brain Imaging Center, University of Washington, Seattle, WA, Seattle, United States, nolan.nichols@gmail.com