A System for Human-Rendered, Evidentiary Data Discovery and Entity Resolution (SHREDDER)

Counter-insurgency (COIN) and irregular warfare (IW) missions have placed an emphasis on the role of tactical intelligence. Increasingly, tactical personnel such as Company-Level Intel Support Team (CoIST) members are responsible for assessing situations, providing insightful intelligence reports to higher echelons, and providing decision-relevant intelligence to their commander. The understaffing and undertraining of the CoIST results in two primary deficiencies: ineffective data gathering, and subsequent ineffective analysis based on the data sets that are available. To support the CoIST in performing more effective data gathering and analysis, we propose to design and demonstrate a System for Human-Rendered, Evidentiary Data Discovery and Entity Resolution (SHREDDER). Our solution is composed of two main elements. The first component is a Data Discovery Tool that employs collaboration support concepts from social media to enable CoIST personnel to identify the decision-relevant data scattered among databases and the mental models of other personnel. The second component is an Entity and Event Resolution Tool that enables personnel to collaborate visually to associate heterogenous and uncertain collected data in the intelligence analysis process. The structure provided by the Entity and Event Resolution Tool matches the unique needs of the CoIST, wherein a variety of information producers and consumers can each contribute dynamically.