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Int J Med Inform. 2016 Oct;94:21-30. doi: 10.1016/j.ijmedinf.2016.06.009. Epub 2016 Jun 23.

Insight: An ontology-based integrated database and analysis platform for epilepsy self-management research.

Author information

1
Division of Medical Informatics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, United States; Electrical Engineering and Computer Science Department, School of Engineering, Case Western Reserve University, Cleveland, OH 44106, United States. Electronic address: satya.sahoo@case.edu.
2
Electrical Engineering and Computer Science Department, School of Engineering, Case Western Reserve University, Cleveland, OH 44106, United States.
3
Neurological Institute, University Hospitals Case Medical Center, Cleveland, OH 44106, United States.
4
Division of Medical Informatics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, United States.
5
Rollins School of Public Health, Emory University, Atlanta, GA 30322, United States.
6
Center for Managing Chronic Disease, University of Michigan, Ann Arbor, MI 48109, United States.
7
Department of Neurology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, United States.

Abstract

We present Insight as an integrated database and analysis platform for epilepsy self-management research as part of the national Managing Epilepsy Well Network. Insight is the only available informatics platform for accessing and analyzing integrated data from multiple epilepsy self-management research studies with several new data management features and user-friendly functionalities. The features of Insight include, (1) use of Common Data Elements defined by members of the research community and an epilepsy domain ontology for data integration and querying, (2) visualization tools to support real time exploration of data distribution across research studies, and (3) an interactive visual query interface for provenance-enabled research cohort identification. The Insight platform contains data from five completed epilepsy self-management research studies covering various categories of data, including depression, quality of life, seizure frequency, and socioeconomic information. The data represents over 400 participants with 7552 data points. The Insight data exploration and cohort identification query interface has been developed using Ruby on Rails Web technology and open source Web Ontology Language Application Programming Interface to support ontology-based reasoning. We have developed an efficient ontology management module that automatically updates the ontology mappings each time a new version of the Epilepsy and Seizure Ontology is released. The Insight platform features a Role-based Access Control module to authenticate and effectively manage user access to different research studies. User access to Insight is managed by the Managing Epilepsy Well Network database steering committee consisting of representatives of all current collaborating centers of the Managing Epilepsy Well Network. New research studies are being continuously added to the Insight database and the size as well as the unique coverage of the dataset allows investigators to conduct aggregate data analysis that will inform the next generation of epilepsy self-management studies.

PMID:
27573308
PMCID:
PMC5010027
DOI:
10.1016/j.ijmedinf.2016.06.009
[Indexed for MEDLINE]
Free PMC Article

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