Ontology-Based Medical Data Integration for Regional Healthcare Application
The regional information sharing provides the ability to transfer up-to-date patient health information quickly and easily across hospitals and institutes. However, the fact that most systems are developed proprietarily hinders data integration. Most developers solve this problem by employing specific data model standards, leading to system inflexibility and inextensibility. In this paper, we present an ontology-based integration method to cope with data heterogeneity in the regional health information network. To carry out interoperability at runtime and in a non-intrusive manner, we design three-layer system architecture. The semantic layer is used to perform coordination among heterogeneous systems, which can connect seamlessly without changing original data structure. We adopt the hybrid ontology approach that extracts information from heterogeneous databases to establish local ontologies and uses an upper-level ontology to make these ontologies compatible. This paper demonstrates a means of accessing to heterogeneous databases for better regional information sharing.
KeywordsData integration Hybrid ontology OWL Regional healthcare
This work was supported by the National Natural Science Foundation (Grant No. 61173127) and Zhejiang University Top Disciplinary Partnership Program (Grant No. 188170*193251101).
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