A model‐driven approach for semantic web service modeling using web service modeling languages. Issue 7 (13th June 2021)

• Record Type: Journal Article
• Authors: Mohseni, Mohsen; Sohrabi, Mohammad Karim; Dorrigiv, Morteza
• Is Part Of: Journal of software. Volume 33:Issue 7(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-06-13
• Subjects: model‐driven approach -- semantic web services -- UML profile -- web service modeling language; Software engineering -- Periodicals; Computer software -- Development -- Periodicals; Software maintenance -- Periodicals; 005.1
• DOI: 10.1002/smr.2364
• Languages: English
• ISSNs: 2047-7473

Abstract

Abstract: The service‐oriented software engineering approach has been increasingly utilized to design and develop complex distributed systems. Exploiting semantic web technologies to increase utilization of the web services at the semantic level leads to create semantic web services (SWSs). This paper proposes a model‐driven architecture (MDA) to model the SWS and to transform it from a high‐level modeling language, such as the Unified Modeling Language (UML), to a low‐level semantic description, such as the Web Service Modeling Language (WSML). To annotate all aspects of the SWS, a UML profile is provided by extending the UML metamodel. Some stereotypes and tagged values are also defined to support WSML. Therefore, the structure aspects of the SWS are modeled with a class diagram based on stereotypes that are defined in the UML profile. The logical and behavioral aspects of the SWS are modeled and expressed using activity diagrams, sequence diagrams, and Object Constraint Language (OCL). Experimental results show that the proposed approach not only increases the level of independence, accuracy, expressiveness, understandability, and machine processability but also significantly reduces the complexity and heterogeneity. Moreover, the proposed method is also evaluated in comparison with the previous methods of the literature, and the results will show that the proposed method outperforms the other methods in terms of expressiveness, understandability, scalability, level of independence, and accuracy.