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Situation-driven processes for semantic web services

Dietze, Stefan; Gugliotta, Alessio and Domingue, John (2008). Situation-driven processes for semantic web services. In: 5th International Conference on Service Systems and Service Management (ICSSSM'08), 30 Jun - 2 Jul 2008, Melbourne, Australia.

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Process models to support user objectives are used across several domains, such as eLearning or Business Process Management. Usually, specific metadata schemas, such as the XML bindings of the Business Process Modelling Notation (BPMN) or IMS Learning Design (IMS LD), are used to enable interoperability. Since Web services which are used throughout a process at runtime, are allocated statically within the process model at design-time, their dynamic adaptability to distinct situations is highly restricted. Whereas the aforementioned process models define a process from a user perspective, Semantic Web Services (SWS) technologies, such as WSMO or OWL-S, define processes from a system perspective by enabling the semantic description of services and data to support their automatic discovery and invocation to achieve specific user tasks at runtime. However, until now, a common link is missing to bridge between a processpsila user perspective and its system perspective. In this paper we propose a metamodel for Situation-Driven Processes (SDP) which enables the description of a process in terms of specific process situations which each is linked to a specific user Goal (user perspective) as well as a set of Brokered Goals (system perspective). Since Brokered Goals are gradually derived from SWS Goals, a process is accomplished dynamically at runtime in terms of SWS Goal achievements. As a result, following an approach of situation-driven process generation at runtime, we support the dynamic composition of a process appropriate for a given situation and its automatic transformation into distinct process metadata standards.

Item Type: Conference or Workshop Item
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: 23033
Depositing User: Kay Dave
Date Deposited: 20 Sep 2010 13:52
Last Modified: 14 Jan 2019 11:44
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