A crucial topic of research for military intelligence production over the past several years has been the design and development of systems that facilitate rapid synthesis and manipulation of large volumes of dynamic information streaming from myriad sources and across intelligence domains. The ability to identify, analyze, model, and share enemy activities and relationships in the battlespace is key to boosting human efficiencies while minimizing the need for combat operations and subsequent collateral damage.

Knowledge discovery systems have the potential to assist intelligence analysts in identifying entities and events of interest, visualizing relationships and patterns of activity, sharing information, recognizing gaps in intelligence, and modeling known or suspected courses of action. Such systems find application in other types of intelligence-gathering operations, such as border security and human trafficking, cybersecurity, civilian criminal investigations, and other domains that involve human social networks.

ATRAP, a software suite for data acquisition, mining, and visualization, is just such a knowledge discovery tool: it is able to ingest raw intelligence messages from multiple sources, employ advanced unstructured text processing and correlation capabilities to generate link and pattern analysis, and display that information in a 3-dimensional, geotemporal visualization environment. It has also been imbued with unique algorithms that take into account both activity-based threat models and specific organizational behavior models in order to identify gaps in intelligence and inform collection management priorities. Those features have been delivered within a tightly-integrated application that is intended to augment collaborative analytic missions and provide decision support.

Originating under the auspices of the Asymmetric Threat Response and Analysis Program within the US Army Intelligence Center of Excellence at Ft. Huachuca, the tool was jointly developed by The University of Arizona and ephibian, Inc., as an advanced data fusion and visualization environment that serves as a "cognitive amplifier" for trained intelligence analysts. This interdisciplinary R&D initiative incorporates research from Electrical and Computer Engineering, Linguistics, Political Science, Sociology, Management Information Systems, and Systems Engineering.