SchizConnect: Mediating neuroimaging databases on schizophrenia and related disorders for large-scale integration

Lei Wang*, Kathryn I. Alpert, Vince D. Calhoun, Derin J. Cobia, David B. Keator, Margaret D. King, Alexandr Kogan, Drew Landis, Marcelo Tallis, Matthew D. Turner, Steven G. Potkin, Jessica A. Turner, Jose Luis Ambite

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

SchizConnect (www.schizconnect.org) is built to address the issues of multiple data repositories in schizophrenia neuroimaging studies. It includes a level of mediation-translating across data sources-so that the user can place one query, e.g. for diffusion images from male individuals with schizophrenia, and find out from across participating data sources how many datasets there are, as well as downloading the imaging and related data. The current version handles the Data Usage Agreements across different studies, as well as interpreting database-specific terminologies into a common framework. New data repositories can also be mediated to bring immediate access to existing datasets. Compared with centralized, upload data sharing models, SchizConnect is a unique, virtual database with a focus on schizophrenia and related disorders that can mediate live data as information is being updated at each data source. It is our hope that SchizConnect can facilitate testing new hypotheses through aggregated datasets, promoting discovery related to the mechanisms underlying schizophrenic dysfunction.

Original languageEnglish (US)
Pages (from-to)1155-1167
Number of pages13
JournalNeuroimage
Volume124
DOIs
StatePublished - Jan 1 2016

Keywords

  • Data mediation and integration
  • Mega analysis
  • Neuroinformatics
  • Schizophrenia databases

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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