Acquire Representations of Meta-Information for Enhancing Battlespace Awareness (AMEBA)
The Situation
Current military visualization environments typically lack means of representing informational qualifiers such as recency, reliability, and pedigree. Too often, the term “uncertainty” is used to encompass multiple qualifiers. As a result, users will typically not perceive, attend, aggregate, understand, or act on these qualifiers (e.g., in Figure 1, the user may have restricted situational awareness if the health of the sensor field that identified incoming entities is not represented). In the past, there has been little research to determine which techniques are most appropriate for conveying certain qualifiers.
The Charles River Analytics Solution
In our project to Acquire Representations of Meta-Information for Enhancing Battlespace Awareness (AMEBA), we performed a cognitive task analysis (CTA) of decision-making in intelligence operations to understand the informational needs of the user across a selected series of tasks. From that analysis, we have developed the concept of meta-information, providing a richer structure for the qualifiers of information that are used in decision-making. We have developed a software toolkit that supports the rapid prototyping and human-in-the-loop evaluation of meta-information representations (e.g., in Figure 2, the health of the sensor that detected an entity is encoded through transparency of the entity icon). We have used the toolkit to perform a series of user experiments with our partners at the University at Buffalo to determine the most effective means of representing different types of meta-information.
The Benefit
The results of the AMEBA experiments and evaluations have yielded insight about the way users perceive and reason about meta-information. This knowledge can be used in the design of visualization techniques to ensure that decision-makers have full situation awareness under any task. Charles River is currently exploring partnerships with lead system integrators (LSIs) to incorporate the empirically validated visualization techniques into larger Government systems, such as the Air Force Integrated Collaborative Environment (AF-ICE), and the Distributed Common Ground System (DCGS). We are also able to provide services to these large-scale efforts by leveraging our visualization design, development and evaluation tools across application domains.
Related Papers
Bisantz, A., Pfautz, J., Stone, R., Roth, E., Thomas-Meyers, G., & Fouse, A. (2006). "Assessment of Color Variables for Displaying Meta-Information on Maps," in Proc. of the Human Factors & Ergonomics Society 50th Annual Meeting, October 16-20, San Francisco, California.
Pfautz, J., Roth, E., Bisantz, A., Thomas-Meyers, G., Llinas, J., & Fouse, A. (2006). "The Role of Meta-Information in C2 Decision-Support Systems," in Proc. of the Command and Control Research and Technology Symposium, June 20-22, 2006, San Diego, California.
Pfautz, J., Bisantz, A., Roth, E., Fouse, A., & Nunes, A. (2006). "Beyond Uncertainty: Examining Meta-Information Visualization Techniques," in Proc. of SIGGRAPH '06, July 30 - August 3, 2006, Boston, Massachusetts.
Pfautz, J., Fouse, A., Farry, M., Bisantz, A., & Roth, E. (2007). "Representing Meta-Information to Support C2 Decision Making," in Proc. of the International Command and Control Research and Technology Symposium (ICCRTS '07), June 19-21, 2007, Newport, Rhode Island.
