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 …

Date

September 21, 2025

Authors

Jose Luis Ambite, Marcelo Tallis, Kathryn Alpert, David B Keator, Margaret King, Drew Landis, George Konstantinidis, Vince D Calhoun, Steven G Potkin, Jessica A Turner, Lei Wang

Conference

Data Integration in the Life Sciences: 11th International Conference, DILS 2015, Los Angeles, CA, USA, July 9-10, 2015, Proceedings 11

Pages

37-51

Publisher

Springer International Publishing