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During persistent surveillance of a given population in a conflict situation, data management can quickly become unwieldy due to the inundation of low-level information from many, disparate sources. Computational population models can easily fuse and aggregate information input, but there is still the challenge of providing effective data visualization which minimizes information overload and introduces misinterpretation by simplified visualization based on aggregations. Visualizations of the actionable knowledge to the analyst based on the population effects as evidenced by their stratagemical behaviors are needed. Five model classes that study the beliefs of groups and how their beliefs change as a result of events were evaluated for their potential for visualization based on an analyst's cognitive model of the conflict situation.A visualization approach was developed that can be used for all of the classes of models based on frames of reference for time and physical location within the environment.

A Visualization Approach for Group Behaviors, Beliefs and Intentions to Support Critical Decisions