Situation Awareness involves the comprehension of the state of a collection of objects in an evolving environment. This not only includes an understanding of the objects' characteristics but also an awareness of the significant relations that hold among the objects at any point in time. Systems for establishing situation awareness require a knowledge representation for these objects and relations. Traditional ontologies, as defined with a language like DAML/OWL, are commonly used for such purposes. Unfortunately, these languages are insufficient for describing the conditions under which specific relations might hold true, which requires the explicit representation of implications, as is provided by RuleML. This paper describes an approach to knowledge representation for situation awareness employing RuleML-based domain theories constructed over OWL ontologies, presented in the context of its implementation in a Situation Awareness Assistant under development by the authors. Suggestions are also made for additions to the RuleML specification.
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