## 4 Semantic Interoperability Provision in Heterogeneous Healthcare Service Environments  
### Semantic Mediation Model  
Semantic interoperability is one of the key requirements to support integrated healthcare solutions, whether it would be a patient's remote health monitoring service which collects information through several data sources or an integrated healthcare application to facilitate access to many healthcare services for diverse stakeholders. The semantic mediation model is based on several interoperability provisioning functions. A view of this model is illustrated in Figure 4. It consists of many features which mainly include semantic annotation of healthcare data, semantic alignment of heterogeneous models, the common data model for unified representation of healthcare contents, and a catalog of target ontology models to maintain the repository of semantically aligned ontologies for the integration of multiple healthcare systems. Semantic annotation of healthcare data is achieved by providing enhancement to the contents collected from varied sources, which provides interlinking among the data, as well as making them machine-readable with semantic ontology attachment. Through the semantic annotation process, information is attached to existing contents based on the defined concepts in the subject ontology model. With the semantic annotation, isolated data are transformed into descriptions associated with the ontology that can be further inferred, exchanged, and reused. The semantic mediation model also consists of the ontology alignment mechanism. The semantic alignment and linking function enable the mapping and management of source and target schemas. The mechanism of semantic alignment includes a semantic ontology management process service, which provides the capability to manage the ontology alignment. It is designed as a microservice to instantiate the ontology alignment process by providing the source and target ontology models. It  
Figure 3: Representation model (R-M) of the Virtual Object (VO) to express Real World Object (RWO) and other information. takes both ontologies and performs an alignment. This service returns the alignment results, in terms of the true mapping achieved through the mapping algorithm. The approach to semantic alignment is followed through deep representation learning, as further discussed in Section 4.2.3. Besides, a Common-Data-Model (CDM) for healthcare data integration, sharing, and interoperability provision plays an important role. CDM transforms the heterogeneous types of data collected from diverse sources, having different structure into coherent, unique data formats. The process of transforming the data into the CDM model involves standard vocabularies, core schema, and the common data format. To satisfy the requirements of semantic interoperability for healthcare data, CDM provides a key role. A single source of data cannot provide an overall status, and it is insufficient to be analyzed where applications are dependent on many data sources with different semantics and formats. To comply with semantic interoperability requirements, a common data model has been realized. Semantic interoperability provision in an environment where healthcare applications can utilize the information from several data models which are although designed for different applications but refer to the same type of data can mitigate semantic heterogeneity. In such scenarios; however, it is very difficult to integrate such data automatically. To achieve this, a target ontologies catalog has been designed to provide the semantic repositories and necessary data processing and management mechanism based on the WoO infrastructure. Moreover, base ontology has been designed to contain the generic concepts to support the semantic interoperability for healthcare applications. It also has features and associated metadata.