Table 1 Semantic Interoperability in E-Health for Improved Healthcare Table 1. HL7 Service Specifications.
Related Figures (12)
Semantics in Action — Applications and Scenarios flows in HL7 is important for achieving the goal of semantic process interoperability WSMO entities (ontologies, services, goals and mediators) modeling are the next step t« be performed. For HL7 processes we would require to model Interaction ontology anc Message Ontology. The interaction ontology would contain all the process artifact (application roles, trigger events, message types and interactions) while the Messags Ontology would contain information related to HL7 V3 message like transmissior wrapper, control act wrapper and message payload. The WSMO entities should b« modeled using WSMT tool for the semantics to completely take effect. The Adapte component implementation is also an important step as conversion from XML to WSMI and WSML to XML is required for overcoming heterogeneity problem and bringin; interoperability. To completely utilize the WSMO entities an execution environmen WSMX should be implemented. Semantic web services will bring automatic service discovery which will make the timely information transfer of patient resulting in quicl access to patient care. Fig. 3. Architecture for SaaS based SEMR system. Semantics in Action — Applications and Scenarios The Semantic Gateway service will then discover, select and invoke Patient Administration Business Process service through HL7 message parsing. The Patient Administration service will call the Patient data service for data management. The Patient data service will call the Authorization service to authorize the patient for viewing his medical data. This service will assign user name and password to the patient. Then the Patient data service will store the registered patient in the patient database. Semantic Interoperability in E-Health for Improved Healthcare Fig. 6. Semantic Framework. utilizes semantic-based publish-subscribe model in conjunction with UDDI. In the Service discovery process we analyzed that there are less updates and frequent searches hence push model is the right approach to use. Through our web based Semantic Registry in Figure 6 users can publish and request service descriptions from Service Publish Interface and Service Discovery Interface. The service descriptions stored in OWL-S Profile Repository as OWL-S service profile. The matching algorithm semantically enhances ontology mappings for providing services descriptions to requesters. It assigns scores to individual concepts of the advertised service by concept matching with that of the requested one and then assigns overall ranking to advertisement on the basis of individual scores. The results have shown a significant increase in precision and recall of service discovery as compared to UDDI approach. The users of the UDDI registry can also switch between traditional syntax-based and proposed semantic-based searching. Normal users can access OWL-S profiles and WSDL advertisements through inquiry API provided by UDDI registry. Semantic Matchmaker used in this work (Capability Matching Module) performs Inputs, Outputs, Preconditions and Effects and Service Category Matching. Capabilities of OWL-S web services; Preconditions and Effects represent a “state” before and after the execution of a service respectively. In this paper we enhance the OWL-S semantic web services capability matching to Inputs, Outputs, Preconditions and Effects. In this way this work will cover data as well as functional semantics modeling aspects. The Physician and patients can now query the Semantic Registry by providing service inputs, output, preconditions or effects. As service discovery will use OWL-S service profile and service process model, the service requester have to provide the required service criteria on the basis of service inputs, output, preconditions or effects. Figure 9 explains the working of the demand oriented information provision. advertisement have direct parent-child relationship. (3) Enclosure match is applicable when request and advertisement is not direct parent-child but still match in the ontology hierarchy. (4) Unknown matches or Fail when there is no concept in the ontology. Table 2 shows the ranking and degree of matches for the requested service with the advertised services. Similarly the same results achieved for other capabilities of services such as service outputs, preconditions and effects. Fig. 10. Performance Analysis of Publishing OWL-S Profile. The performance analysis of the system is represented in form of time taken for ontology to be loaded into the memory. Analysis also contains the results of the system in terms of number of relevant results produced by our system comparing with the results of the syntax based systems without ontologies. The current book is a combination of number of great ideas, applications, case studies, and practical systerr in the domain of Semantics. The book has been divided into two volumes. The current one is the second volume which highlights the state-of-the-art application areas in the domain of Semantics. This volume has been divided into four sections and ten chapters. The sections include: 1) Software Engineering, 2) Applications: Semantic Cache, E-Health, Sport Video Browsing, and Power Grids, 3) Visualization, and 4) Natural Language Disambiguation. Authors across the World have contributed to debate on state-of-the-art systems, theories, models, applications areas, case studies in the domain of Semantics. Furthermore, autho have proposed new approaches to solve real life problems ranging from e-Health to power grids, video browsing to program semantics, semantic cache systems to natural language disambiguation, and public debate to software engineering.
