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Context-aware process support through automatic discovery and invocation of semantic web services

Dietze, Stefan; Gugliotta, Alessio and Domingue, John (2007). Context-aware process support through automatic discovery and invocation of semantic web services. In: IEEE International Conference on Service-Oriented Computing and Applications (SOCA'07), 19-20 Jun 2007, Newport Beach, California, USA.

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Current technologies aimed at supporting processes – whether it is a business process or a learning process – are usually based on using a dedicated set of metadata to describe a process which refers to some specific data, used in the process. Process metadata is usually specific to a standard specification – like the Business Process Modeling Notation (BPMN) or the IMS Learning Design Standard – while used process data is specific to a specific process context. These facts limit the re-usability of a process model across different standards and contexts. To overcome these issues, this paper describes an innovative semantic web service-oriented architecture aimed at changing this data- and metadata-based paradigm to a highly dynamic service-oriented approach following the idea of a semantic abstraction from process metadata as well as process data. This approach enables a dynamic adaptation to specific actor needs and objectives and supports the development of abstract semantic process models which are re-usable across different contexts and standards. To illustrate the application of our approach, we describe a prototypical
application to the domain of E-Learning.

Item Type: Conference or Workshop Item
Copyright Holders: 2007 IEEE
Extra Information: ISBN: 0-7695-2861-9
Keywords: Business Process Modeling Notation; IMS Learning Design Standard; abstract semantic process model; context-aware process support; dynamic adaptation; dynamic service-oriented approach; e-learning; process description; process metadata; process model reusability; semantic Web services; semantic abstraction; service-oriented architecture
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
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Item ID: 24467
Depositing User: Kay Dave
Date Deposited: 03 Mar 2011 11:02
Last Modified: 15 Jan 2019 06:07
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