SchizConnect: virtual data integration in neuroimaging
SchizConnect: virtual data integration in neuroimaging
In many scientific domains, including neuroimaging studies, there is a need to obtain increasingly larger cohorts to achieve the desired statistical power for discovery. However, the economics of imaging studies make it unlikely that any single study or consortia can achieve the desired sample sizes. What is needed is an architecture that can easily incorporate additional studies as they become available. We present such architecture based on a virtual data integration approach, where data remains at the original sources, and is retrieved and harmonized in response to user queries. This is in contrast to approaches that move the data to a central warehouse. We implemented our approach in the SchizConnect system that integrates data from three neuroimaging consortia on Schizophrenia: FBIRN’s Human Imaging Database (HID), MRN’s Collaborative Imaging and Neuroinformatics System (COINS), and the NUSDAST project at XNAT Central. A portal providing harmonized access to these sources is publicly deployed at schizconnect.org.
37-51
Ambite, Jose Luis
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Tallis, Marcelo
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Alpert, Kathryn
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Keator, David
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King, Margaret
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Landis, Drew
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Konstantinidis, George
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Calhoun, Vince D.
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Potkin, Steven
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Turner, Jessica
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Wang, Lei
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8 July 2015
Ambite, Jose Luis
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Tallis, Marcelo
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Alpert, Kathryn
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Keator, David
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King, Margaret
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Landis, Drew
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Konstantinidis, George
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Calhoun, Vince D.
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Potkin, Steven
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Turner, Jessica
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Wang, Lei
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Ambite, Jose Luis, Tallis, Marcelo, Alpert, Kathryn, Keator, David, King, Margaret, Landis, Drew, Konstantinidis, George, Calhoun, Vince D., Potkin, Steven, Turner, Jessica and Wang, Lei
(2015)
SchizConnect: virtual data integration in neuroimaging.
11th International Conference on Data Integration in the Life Sciences, , Los Angeles, United States.
09 - 10 Jul 2015.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
In many scientific domains, including neuroimaging studies, there is a need to obtain increasingly larger cohorts to achieve the desired statistical power for discovery. However, the economics of imaging studies make it unlikely that any single study or consortia can achieve the desired sample sizes. What is needed is an architecture that can easily incorporate additional studies as they become available. We present such architecture based on a virtual data integration approach, where data remains at the original sources, and is retrieved and harmonized in response to user queries. This is in contrast to approaches that move the data to a central warehouse. We implemented our approach in the SchizConnect system that integrates data from three neuroimaging consortia on Schizophrenia: FBIRN’s Human Imaging Database (HID), MRN’s Collaborative Imaging and Neuroinformatics System (COINS), and the NUSDAST project at XNAT Central. A portal providing harmonized access to these sources is publicly deployed at schizconnect.org.
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Published date: 8 July 2015
Venue - Dates:
11th International Conference on Data Integration in the Life Sciences, , Los Angeles, United States, 2015-07-09 - 2015-07-10
Identifiers
Local EPrints ID: 504285
URI: http://eprints.soton.ac.uk/id/eprint/504285
PURE UUID: 644959de-f46c-4f4d-8054-92eb612f6843
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Date deposited: 02 Sep 2025 17:09
Last modified: 02 Sep 2025 17:09
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Contributors
Author:
Jose Luis Ambite
Author:
Marcelo Tallis
Author:
Kathryn Alpert
Author:
David Keator
Author:
Margaret King
Author:
Drew Landis
Author:
George Konstantinidis
Author:
Vince D. Calhoun
Author:
Steven Potkin
Author:
Jessica Turner
Author:
Lei Wang
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