Understanding Information Uncertainty within the Context of a Net-Centric Data Model: A Mine Warfare Example

This paper examines the challenge of assessing operational measures of effectiveness given incomplete and often imperfect information. With the migration of software applications towards a service-oriented architecture and net-centric capability, the ability to capture, quantify, and aggregate uncertainty of information within a semantic framework will be integral to conveying the true operational picture. A potential way to represent the uncertainty of available data is through the incorporation of probabilistic information within a C2-focused semantic data structure. This paper establishes a notional framework for associating probabilities within a content-rich data structure and demonstrates this framework for the Mine Warfare operational measures of effectiveness. The management of multiple variable inputs and the improved bounding of uncertainty over time are developed within a Bayesian context. Finally, the implications of introducing a new method for handling uncertainty within an information-centric data model are explored.