This paper examines the challenge of understanding uncertainty associated with military measures of effectiveness given incomplete and often imperfect information. With the migration towards a network-centric capability, the ability to represent, quantify, and aggregate uncertainty of information within a common framework will be integral to conveying the true operational picture. A potential way to effectively manage uncertainty is through the incorporation of probabilistic information within a semantic construct. This paper utilizes the mine warfare example to examine this concept for uncertainty associated with operational measures of effectiveness. The representation of uncertainty and the inclusion of probabilistic information within a hierarchical data model are developed in a Bayesian context. Finally, the notion of utilizing a structured taxonomic approach to facilitate a reduction in uncertainty is explored.
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