A Cognitive Systems Approach to Supporting Air Force Intelligence Analysis

ABSTRACT: The insertion of WAAS into the Air Force GEOINT analyst's arsenal of resources represents an evolutionary advance in potential real-time and forensic analysis capabilities. With the broad coverage areas that WAAS provides, analysts will be able to monitor individuals, groups, and vehicles across space and time, allowing them to more accurately and effectively develop patterns of life, identify insurgent networks and cells, and provide critical, time-sensitive information to customers on the ground. But with these new capabilities come challenges. WAAS datasets will be enormous, and the potential for data overload is significant. Decision aids and user interfaces are needed that will support analysts in optimally exploiting WAAS datasets, and these supports must be based on the actual cognitive demands of the analysts. In this effort, we will directly address this requirement by performing an extensive cognitive analysis of the WAAS data analysis task. Our team will develop multiple WAAS datasets, customized to the unique cognitive tasks that WAAS analysts will face. These datasets will be integrated into realistic, mission-relevant simulations, which will be administered with operational analysts. Aids and interfaces will be developed and the most promising and immediately usable will be formally evaluated, again utilizing the mission-relevant WAAS datasets. BENEFIT: The Air Force GEOINT analysis community will have a direct and immediate need for supports to WAAS analysis. As Gorgon Stare is deployed, analysts will be faced with massive amounts of data to exploit, and our cogntively-based supports will promote effective and efficient data exploitation. Outside DoD, our contacts at the Department of Homeland Security, Customs and Border Patrol, and the Federal Emergency Management Agency will all need similar, analyst-centered WAAS decision aids and interface supports.