Ontology-Based Context Representation and Reasoning Using OWL and SWRL

Abstract

Recently, quite a few researches upon context-awareness, ubiquitous computing and automatic surveillance have emerged. Their objectives are to appropriately react to current context situation over the web, rather than in a single machine. This requires exchanging the context of extremely dynamic web environment, as well as reasoning about the context to achieve goal. Thus, context representation and context reasoning play significant roles. This paper presents an ontology-based approach to: 1) employing web ontology language (OWL) to describe context knowledge, and 2) using semantic web rule language (SWRL) to represent rule-based inference rules for context reasoning. OWL describes context knowledge in details by defining relationships among knowledge. As an XML-based language, OWL enjoys good interoperability for knowledge sharing and reuse over the web. Further, SWRL represents rule-based first-order logic (FOL) inference rules, which are expressed in terms of predefined OWL taxonomic context knowledge. By doing so, SWRL rules perfectly integrate with OWL, making it easy to develop and maintain application systems. Besides, as SWRL is also XML-based, it is not so dependent upon inference engine. That is, inference engine can be changed without rewriting the rules for engine-specific syntax. This enhances system maintainability.