Purpose-aware reasoning about interoperability of heterogeneous training systems

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Abstract

We describe a novel approach by which software can assess the ability of a confederation of heterogeneous systems to interoperate to achieve a given purpose. The approach uses ontologies and knowledge bases (KBs) to capture the salient characteristics of systems, on the one hand, and of tasks for which these systems will be employed, on the other. Rules are used to represent the conditions under which the capabilities provided by systems can fulfill the capabilities needed to support the roles and interactions that make up each task. An Analyzer component employs these KBs and rules to determine if a given confederation will be adequate, to generate suitable confederations from a collection of available systems, to pre-diagnose potential interoperability problems that might arise, and to suggest system configuration options that will help to make interoperability possible. We have demonstrated the feasibility of this approach using a prototype Analyzer and KBs. © 2008 Springer-Verlag Berlin Heidelberg.

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APA

Elenius, D., Ford, R., Denker, G., Martin, D., & Johnson, M. (2007). Purpose-aware reasoning about interoperability of heterogeneous training systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4825 LNCS, pp. 750–763). https://doi.org/10.1007/978-3-540-76298-0_54

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