Meta-Information Visualization and Processing for C2

We propose to design, develop, and evaluate methods for Meta-Information Visualization and Processing (MVP) for BMD C2. These methods will assist BMD operators in reasoning about large amounts of complex information – a task made more challenging due to meta-information (i.e., qualifiers of information) such as recency, reliability, and pedigree. Under Phase I, we demonstrated the feasibility of our approach to developing meta-information visualization and processing methods. Specifically, we performed a work domain analysis (WDA) of BMD C2 decision-making to identify the types of information and meta-information required. We prototyped methods for the computation and presentation of meta-information, and created user interfaces for the management of meta-information. Finally, we developed an evaluation methodology. Under Phase II, we propose to develop and evaluate these meta-information visualization and processing methods by: (1) performing an expanded WDA on enhanced vignettes to identify additional decisions and associated meta-information; (2) extending the Phase I techniques for computing, visualizing, and interacting with meta-information; (3) implementing a stand-alone software demonstration of these techniques; (4) integrating these techniques as software components in a MDA demonstration testbed while developing tools for human-in-the-loop evaluation; (5) refining the techniques through evaluation; and (6) identifying and pursuing Phase III transition and commercialization opportunities.