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SchizConnect: Virtual Data Integration in Neuroimaging

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Data Integration in the Life Sciences (DILS 2015)


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

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SchizConnect is supported by a grant from the National Institutes of Health (NIH/NIMH), 5U01MH097435 to L. Wang, JL. Ambite, S.G. Potkin and J.A.Turner. The work on COINS is also supported by 5P20GM103472 (NIGMS) to V.D. Calhoun.

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Correspondence to Jose Luis Ambite .

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Ambite, J.L. et al. (2015). SchizConnect: Virtual Data Integration in Neuroimaging. In: Ashish, N., Ambite, JL. (eds) Data Integration in the Life Sciences. DILS 2015. Lecture Notes in Computer Science(), vol 9162. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21842-7

  • Online ISBN: 978-3-319-21843-4

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