In this paper, we describe the problem of efficiently supplying high-level fusion services (situation and impact assessment) with adequate information using semantic technology and formulate an optimization problem version of it. We begin by discussing situation awareness and the need for computer tools that assist human analysts and decision makers with their sense-making. Such tools are necessary in part because of the vast amount of information that is available for analysis in today's command and control systems: the human operators need help to sort out the relevant parts. This kind of filtering requirement is however not limited to humans: automatic or semi-automatic fusion tools also need to limit the information they use in their processing. Simple such filtering could be done based on geographical location, but as the number of advanced fusion services used in the command and control system increases, more advanced techniques need to be used. We describe the information supply process when dealing with several (possibly heterogeneous) sources of differing quality and describe the concepts of information view and information scope. We describe how semantic queries can be used to achieve such filtering, and in particular describe this implemented for Impactorium, a framework tool for situation and impact assessment developed by FOI. The threat models in Impactorium previously relied solely on simple indicator tags for information supply. This can be done more robustly by adding semantic queries to the threat models. The paper concludes with a summary and some discussion of future work in this area.

Date Published: 19 May 2009
PDF: 8 pages
Proc. SPIE 7352, Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing, 73520N (19 May 2009); doi: 10.1117/12.818544

Published in SPIE Proceedings Vol. 7352:
Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing
Stephen Mott; John F. Buford; Gabriel Jakobson, Editor(s)