Within the numerous and heterogeneous web services offered through different sources, automatic web services composition is the most convenient method for building complex business processes that permit invocation of multiple existing atomic services. The current solutions in functional web services composition lack autonomous queries of semantic matches within the parameters of web services, which are necessary in the composition of large-scale related services. In this paper, we propose a graph-based Semantic Web Services composition system consisting of two subsystems: management time and run time. The management-time subsystem is responsible for dependency graph preparation in which a dependency graph of related services is generated automatically according to the proposed semantic matchmaking rules. The run-time subsystem is responsible for discovering the potential web services and nonredundant web services composition of a user's query using a graph-based searching algorithm. The proposed approach was applied to healthcare data integration in different health organizations and was evaluated according to two aspects: execution time measurement and correctness measurement.

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The integration of data from various electronic health record (EHR) systems presents a critical conflict in the sharing and exchanging of patient information across a diverse group of health‐oriented organizations. Patient health records in each system are annotated with ontologies utilizing different health‐care standards, creating ontology conflicts both at the schema and data levels. In this study, we introduce the concept of semantic ontology mapping for the facilitation and interoperability of heterogeneous EHR systems. This approach proposes a means of detecting and resolving the data‐level conflicts that generally exist in the ontology mapping process. We have extended the semantic bridge ontology in support of ontology mapping at the data level and generated the required mapping rules to reconcile data from different ontological sources into a canonical format. As a result, linked‐patient data are generated and made available in a semantic query engine to facilitate user queries of patient data across heterogeneous EHR systems.

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This paper proposes a Semantic Interoperability for Data Integration-SIDI framework to integrate information from heterogeneous databases of difference providers in the same domain. A framework is designed to incorporate with important procedures based on ontology and semantic web services technologies. The semantic web services annotation is imperative to cope with the semantic service discrepancies with the help of ontology. The research also proposes the ontology mapping technique to determine the correspondences between information concepts with semantic bridges description to automatically construct the semantic rule-based inference. As a result, the framework has been applied to the healthcare domain to enable semantic interoperability among independently developed health information system-HIS for integrating healthcare data.