iSemServ: a framework for engineering intelligent semantic services

The need for modern enterprises and Web users to simply and rapidly develop and deliver platform-independent services to be accessed over the Web by the global community is growing. This is self-evident, when one considers the omnipresence of electronic services (e-services) on the Web. Accordingly...

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Bibliographic Details
Main Author: Mtsweni, Jabu Saul
Other Authors: Biermann, Elmarie
Format: Others
Language:en
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10500/9380
id ndltd-netd.ac.za-oai-union.ndltd.org-unisa-oai-umkn-dsp01.int.unisa.ac.za-10500-9380
record_format oai_dc
collection NDLTD
language en
format Others
sources NDLTD
topic Intelligent semantic services
Web services
Ontologies
Intelligent agents
Service engineering
Model-driven techniques
iSemServ framework
006.78
Web services
Semantic web
Intelligent agents (Computer software)
spellingShingle Intelligent semantic services
Web services
Ontologies
Intelligent agents
Service engineering
Model-driven techniques
iSemServ framework
006.78
Web services
Semantic web
Intelligent agents (Computer software)
Mtsweni, Jabu Saul
iSemServ: a framework for engineering intelligent semantic services
description The need for modern enterprises and Web users to simply and rapidly develop and deliver platform-independent services to be accessed over the Web by the global community is growing. This is self-evident, when one considers the omnipresence of electronic services (e-services) on the Web. Accordingly, the Service-Oriented Architecture (SOA) is commonly considered as one of the de facto standards for the provisioning of heterogeneous business functionalities on the Web. As the basis for SOA, Web Services (WS) are commonly preferred, particularly because of their ability to facilitate the integration of heterogeneous systems. However, WS only focus on syntactic descriptions when describing the functional and behavioural aspects of services. This makes it a challenge for services to be automatically discovered, selected, composed, invoked, and executed – without any human intervention. Consequently, Semantic Web Services (SWS) are emerging to deal with such a challenge. SWS represent the convergence of Semantic Web (SW) and WS concepts, in order to enable Web services that can be automatically processed and understood by machines operating with limited or no user intervention. At present, research efforts within the SWS domain are mainly concentrated on semantic services automation aspects, such as discovery, matching, selection, composition, invocation, and execution. Moreover, extensive research has been conducted on the conceptual models and formal languages used in constructing semantic services. However, in terms of the engineering of semantic services, a number of challenges are still prevalent, as demonstrated by the lack of development and use of semantic services in real-world settings. The lack of development and use could be attributed to a number of challenges, such as complex semantic services enabling technologies, leading to a steep learning curve for service developers; lack of unified service platforms for guiding and supporting simple and rapid engineering of semantic services, and the limited integration of semantic technologies with mature service-oriented technologies. vi In addition, a combination of isolated software tools is normally used to engineer semantic services. This could, however, lead to undesirable consequences, such as prolonged service development times, high service development costs, lack of services re-use, and the lack of semantics interoperability, reliability, and re-usability. Furthermore, available software platforms do not support the creation of semantic services that are intelligent beyond the application of semantic descriptions, as envisaged for the next generation of services, where the connection of knowledge is of core importance. In addressing some of the challenges highlighted, this research study adopted a qualitative research approach with the main focus on conceptual modelling. The main contribution of this study is thus a framework called iSemServ to simplify and accelerate the process of engineering intelligent semantic services. The framework has been modelled and developed, based on the principles of simplicity, rapidity, and intelligence. The key contributions of the proposed framework are: (1) An end-to-end and unified approach of engineering intelligent semantic services, thereby enabling service engineers to use one platform to realize all the modules comprising such services; (2) proposal of a model-driven approach that enables the average and expert service engineers to focus on developing intelligent semantic services in a structured, extensible, and platform-independent manner. Thereby increasing developers’ productivity and minimizing development and maintenance costs; (3) complexity hiding through the exploitation of template and rule-based automatic code generators, supporting different service architectural styles and semantic models; and (4) intelligence wrapping of services at message and knowledge levels, for the purposes of automatically processing semantic service requests, responses and reasoning over domain ontologies and semantic descriptions by keeping user intervention at a minimum. The framework was designed by following a model-driven approach and implemented using the Eclipse platform. It was evaluated using practical use case scenarios, comparative analysis, and performance and scalability experiments. In conclusion, the iSemServ framework is considered appropriate for dealing with the complexities and restrictions involved in engineering intelligent semantic services, especially because the amount of time required to generate intelligent semantic vii services using the proposed framework is smaller compared with the time that the service engineer would need to manually generate all the different artefacts comprising an intelligent semantic service. Keywords: Intelligent semantic services, Web services, Ontologies, Intelligent agents, Service engineering, Model-driven techniques, iSemServ framework. === Computing === D. Phil. (Computer science)
author2 Biermann, Elmarie
author_facet Biermann, Elmarie
Mtsweni, Jabu Saul
author Mtsweni, Jabu Saul
author_sort Mtsweni, Jabu Saul
title iSemServ: a framework for engineering intelligent semantic services
title_short iSemServ: a framework for engineering intelligent semantic services
title_full iSemServ: a framework for engineering intelligent semantic services
title_fullStr iSemServ: a framework for engineering intelligent semantic services
title_full_unstemmed iSemServ: a framework for engineering intelligent semantic services
title_sort isemserv: a framework for engineering intelligent semantic services
publishDate 2013
url http://hdl.handle.net/10500/9380
work_keys_str_mv AT mtswenijabusaul isemservaframeworkforengineeringintelligentsemanticservices
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spelling ndltd-netd.ac.za-oai-union.ndltd.org-unisa-oai-umkn-dsp01.int.unisa.ac.za-10500-93802016-04-16T04:08:19Z iSemServ: a framework for engineering intelligent semantic services Mtsweni, Jabu Saul Biermann, Elmarie Pretorius, L. Intelligent semantic services Web services Ontologies Intelligent agents Service engineering Model-driven techniques iSemServ framework 006.78 Web services Semantic web Intelligent agents (Computer software) The need for modern enterprises and Web users to simply and rapidly develop and deliver platform-independent services to be accessed over the Web by the global community is growing. This is self-evident, when one considers the omnipresence of electronic services (e-services) on the Web. Accordingly, the Service-Oriented Architecture (SOA) is commonly considered as one of the de facto standards for the provisioning of heterogeneous business functionalities on the Web. As the basis for SOA, Web Services (WS) are commonly preferred, particularly because of their ability to facilitate the integration of heterogeneous systems. However, WS only focus on syntactic descriptions when describing the functional and behavioural aspects of services. This makes it a challenge for services to be automatically discovered, selected, composed, invoked, and executed – without any human intervention. Consequently, Semantic Web Services (SWS) are emerging to deal with such a challenge. SWS represent the convergence of Semantic Web (SW) and WS concepts, in order to enable Web services that can be automatically processed and understood by machines operating with limited or no user intervention. At present, research efforts within the SWS domain are mainly concentrated on semantic services automation aspects, such as discovery, matching, selection, composition, invocation, and execution. Moreover, extensive research has been conducted on the conceptual models and formal languages used in constructing semantic services. However, in terms of the engineering of semantic services, a number of challenges are still prevalent, as demonstrated by the lack of development and use of semantic services in real-world settings. The lack of development and use could be attributed to a number of challenges, such as complex semantic services enabling technologies, leading to a steep learning curve for service developers; lack of unified service platforms for guiding and supporting simple and rapid engineering of semantic services, and the limited integration of semantic technologies with mature service-oriented technologies. vi In addition, a combination of isolated software tools is normally used to engineer semantic services. This could, however, lead to undesirable consequences, such as prolonged service development times, high service development costs, lack of services re-use, and the lack of semantics interoperability, reliability, and re-usability. Furthermore, available software platforms do not support the creation of semantic services that are intelligent beyond the application of semantic descriptions, as envisaged for the next generation of services, where the connection of knowledge is of core importance. In addressing some of the challenges highlighted, this research study adopted a qualitative research approach with the main focus on conceptual modelling. The main contribution of this study is thus a framework called iSemServ to simplify and accelerate the process of engineering intelligent semantic services. The framework has been modelled and developed, based on the principles of simplicity, rapidity, and intelligence. The key contributions of the proposed framework are: (1) An end-to-end and unified approach of engineering intelligent semantic services, thereby enabling service engineers to use one platform to realize all the modules comprising such services; (2) proposal of a model-driven approach that enables the average and expert service engineers to focus on developing intelligent semantic services in a structured, extensible, and platform-independent manner. Thereby increasing developers’ productivity and minimizing development and maintenance costs; (3) complexity hiding through the exploitation of template and rule-based automatic code generators, supporting different service architectural styles and semantic models; and (4) intelligence wrapping of services at message and knowledge levels, for the purposes of automatically processing semantic service requests, responses and reasoning over domain ontologies and semantic descriptions by keeping user intervention at a minimum. The framework was designed by following a model-driven approach and implemented using the Eclipse platform. It was evaluated using practical use case scenarios, comparative analysis, and performance and scalability experiments. In conclusion, the iSemServ framework is considered appropriate for dealing with the complexities and restrictions involved in engineering intelligent semantic services, especially because the amount of time required to generate intelligent semantic vii services using the proposed framework is smaller compared with the time that the service engineer would need to manually generate all the different artefacts comprising an intelligent semantic service. Keywords: Intelligent semantic services, Web services, Ontologies, Intelligent agents, Service engineering, Model-driven techniques, iSemServ framework. Computing D. Phil. (Computer science) 2013-05-09T11:59:05Z 2013-05-09T11:59:05Z 2013-05-09 2013-01 Thesis http://hdl.handle.net/10500/9380 en University of South Africa 1 online resource (xix, 236 leaves : ill)