Intelligent Information Integration For The Semantic Web (Lecture Notes in Computer Science)
Intelligent Information Integration For The Semantic Web (Lecture Notes in Computer Science)
Semantics to energize the full services spectrum
Communications of the ACM - Services science
On-line update of situation assessment: A generic approach
International Journal of Knowledge-based and Intelligent Engineering Systems - Selected papers from the KES2004 conference
A software architecture for ontology-driven situation awareness
Proceedings of the 2008 ACM symposium on Applied computing
CONTEXT'07 Proceedings of the 6th international and interdisciplinary conference on Modeling and using context
On relating heterogeneous elements from different ontologies
CONTEXT'07 Proceedings of the 6th international and interdisciplinary conference on Modeling and using context
An application of semantic web technologies to situation awareness
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Formal foundations for situation awareness based on dependent type theory
Information Fusion
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Large-scale control systems, as encountered in the domain of road traffic management, typically deal with highly-dynamic environments providing information about a large number of real-world objects, which stem from multiple heterogeneous sources and are anchored in time and space. Human operators of such systems face information overload which endangers the recognition of critical situations. Situation awareness systems should support operators fulfilling their tasks by leveraging their awareness of the ongoing situations. However, current approaches to SAW miss a common conceptual model necessary for various aspects of SAW. Although the application of ontologies for filling this gap has been proposed in recent years, ontology-driven SAW systems are nevertheless still in their infancy. In this paper, we shape the vision of an ontology-driven SAW system by the analysis of application scenarios facilitating the features of formal ontologies. We illustrate the suggested scenarios with examples from the field of road traffic management and argue that an ontology-driven SAW system does not replace but may actually enhance traditional probabilistic approaches to SAW.