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BeAware! - Situation awareness, the ontology-driven way

BeAware! - Situation awareness, the ontology-driven way,10.1016/j.datak.2010.07.008,Data & Knowledge Engineering,Norbert Baumgartner,Wolfgang Gotteshe

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BeAware! - Situation awareness, the ontology-driven way   (Citations: 1)
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Information overload is a severe problem for human operators of large-scale control systems as, for example, encountered in the domain of road traffic management. Operators of such systems are at risk to lack situation awareness, because existing systems focus on the mere presentation of the available information on graphical user interfaces—thus endangering the timely and correct identification, resolution, and prevention of critical situations. In recent years, ontology-based approaches to situation awareness featuring a semantically richer knowledge model have emerged. However, current approaches are either highly domain-specific or have, in case they are domain-independent, shortcomings regarding their reusability.In this paper, we present our experience gained from the development of BeAware!, a framework for ontology-driven information systems aiming at increasing an operator's situation awareness. In contrast to existing domain-independent approaches, BeAware!'s ontology introduces the concept of spatio-temporal primitive relations between observed real-world objects thereby improving the reusability of the framework. To show its applicability, a prototype of BeAware! has been implemented in the domain of road traffic management. An overview of this prototype and lessons learned for the development of ontology-driven information systems complete our contribution.
Journal: Data & Knowledge Engineering - DKE , vol. 69, no. 11, pp. 1181-1193, 2010
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    • ...We are currently developing a framework for realizing ontology-driven situation awareness techniques [2], including duplicate detection techniques [3], in the sample domain of road traffic management...
    • ...Qualitative relations between objects can be automatically derived from their quantitative attributes using rule-based relation interpretations [2] (e. g., two traffic jams are PartiallyOverlapping if their spatial regions overlap)...
    • ...To correlate quantitative values with their qualitative representations, we introduced rule-based relation interpretations that derive relations from object attribute values [2]...
    • ...Currently, relation calculi relevant to the generation of spatio-temporal data are supported (RCC, spatial distance and size calculi [2], and Allen’s Temporal Intervals)...

    Wolfgang Gottesheim, et al. SemGen - Towards a Semantic Data Generator for Benchmarking Duplicate ...

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