Abstract
Semantic Web technologies offer a promising framework for integration of disparate biomedical data. In this paper we present the semantic information integration platform under development at the Center for Clinical and Translational Sciences (CCTS) at the University of Texas Health Science Center at Houston (UTHSC-H) as part of our Clinical and Translational Science Award (CTSA) program. We utilize the Semantic Web technologies not only for integrating, repurposing and classification of multi-source clinical data, but also to construct a distributed environment for information sharing, and collaboration online. Service Oriented Architecture (SOA) is used to modularize and distribute reusable services in a dynamic and distributed environment. Components of the semantic solution and its overall architecture are described.
Highlights
Understanding, diagnosing, treating, and preventing human disease requires the integration of information and knowledge from all levels of biology including molecules, tissues, organ systems, individuals and populations
We developed a semantic application called the Survey On Demand System (SODS) that uses this model, domain ontologies, and Knowledge organization systems (KOS) that are available to the system to facilitate construction of an ontology driven structured data entry (SDE) tool for questionnaire and survey design
The system described in this paper is conceptualized to use formal information and knowledge representation frameworks (i.e., Semantic Web) to construct an ontology-driven information system
Summary
Understanding, diagnosing, treating, and preventing human disease requires the integration of information and knowledge from all levels of biology including molecules, tissues, organ systems, individuals and populations. Integrating heterogeneous data from multiple sources, and sharing information in a distributed and collaborative environment are challenging informatics problems. Heterogeneous information from semantically and schematically disparate sources must be normalized, integrated and mapped to medical vocabulary systems. Integrated data need to be repurposed to support research and practical applications across different principals, and among different communities, without losing or distorting the semantics and the context of the original data. All these operations need to take place in an environment that is distributed in time and space. They must comply with policies and regulations relating to the proper conduct of research (consent management, accountability, confidentiality, etc)
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