Frame Logic‐based specification and discovery of semantic web services with application to medical appointments

Abstract

Matching web services and client requirements in the form of goals is a significant challenge in the discovery of semantic web services. The most common but unsatisfactory approach to matching is set‐based, where both the client and web services declare what objects they require and what objects they can provide. Matching then becomes the simple task of comparing sets of objects. This approach is inadequate because it says nothing about the functionality required by the client or the functionality provided by the web service. As an alternative, we use the Frame Logic as implemented in Flora‐2 to specify web service capabilities and client requirements, including their preconditions, postconditions, and ontologies, implement a logic‐based discovery agent using Flora‐2, demonstrate its usefulness in a medical appointment making scenario, and show its efficiency both theoretically and by benchmarking. The result is an expressive yet concise representation scheme for semantic web services, and a practical, efficient, powerful, and fully implemented matching engine based purely on logical inference for web service discovery, with direct applicability to Web Service Modeling Ontology and Web Service Modeling Language, because both are based on Frame Logic.

Semantic Web in Healthcare: A Systematic Literature Review of Application, Research Gap, and Future Research Avenues

“…In the e-healthcare service-based theme (see Table 6 ), the authors in [ 51 ] established a set of setups to test the matcher's efficiency for scalability in terms of the number of Semantic Web services for medical appointments and their complexity. They consider the logical complexity of Flora-2 expressions used in pre and post-conditions, which can handle various web service and goal descriptions, including ontology consistency check.…”

“…Concerning this, it could be very helpful if there is a system that can match patient requirements with the services. Such a matchmaking system has been developed to match the web services with the patient's requirements for medical appointments [ 51 ]. To provide hospital-based services, a Semantic Web-based dynamic healthcare system was developed using ontologies [ 17 ].…”

“…Besides, Kiourtis et al [ 68 ] developed a technique for converting healthcare data into its equivalent HL7 FHIR structure, which principally corresponds to the most used data structures for describing healthcare information. Furthermore, a sublanguage of F-logic named Frame Logic for Semantic Web Services (FLOG4SWS) and web services along with some features of Flora-2 was used to represent the ontology [ 51 ]. The authors of some papers used RDF and OWL for data representation of different ontologies [ 50 , 52 , 54 , 66 ].…”