Acquiring representations of Meta-information to Enhance Battlespace Awareness (AMEBA)

We propose to design, develop, and evaluate a system for Acquiring representations of Meta-information to Enhance Battlespace Awareness (AMEBA). AMEBA aids the warfighter by providing representations of meta-information, or characteristics of information such as uncertainty, staleness, etc. that aid decision-making and are not typically provided. Under Phase I, we demonstrated the feasibility of the proposed approach to developing meta-information visualizations. Specifically, we performed a cognitive task analysis (CTA) of decision-making in intelligence operations using smart sensor networks to identify the types of information and meta-information that are required. We prototyped a software toolkit for mapping incoming data to the identified meta-information types and for creating new information visualization methods and interfaces. Finally, we developed an evaluation methodology and associated metrics. Under Phase II, we propose to expand the system's capabilities by: (1) performing an expanded CTA on enhanced case studies to identify additional decisions and types of meta-information; (2) developing additional strategies for visualizing meta-information; (3) designing interfaces to optimize user interaction with the representations; (4) refining the visualization methods and associated user interfaces by evaluating the representation techniques and user interface mechanisms; and (5) identifying and pursuing Phase III transition and commercialization opportunities.