Leveraging visualization to improve sensemaking within a computational RPD model: a military perspective

Motivation - To explore the concept that knowledge visualization would improve sensemaking within the scope of a NDM model; specifically the agent-based R-CAST system derived from Klein's Recognition-Primed Decision (RPD) Model. Research approach - In order to evaluate the effectiveness of the visual sensemaking extension to gain better situation awareness and team performance, we are taking an experimental approach. Research limitations/Implications - This is an ongoing effort with results of planned experiment expected in early 2009. Originality/Value - The knowledge visualization concept offered in this effort is based on a hybrid dimensionality reduction technique and the aggregated similarity measures of an RPD experience space. The results of the knowledge visualization will likely improve the perception, comprehension and projection associated with an RPD experience space. Take away message - Processes that support a decision maker's sensemaking and situational awareness to solve problems are inadequate. Extending RPD with knowledge visualization may significantly improve the decision making process.