A Framework for Multi-source Semantic Information Extraction & Fusion for Collaborative Threat Assessment (SIFT)

This paper describes the motivations, methods, and automation architecture of a framework for multisource Semantic Information extraction & Fusion for collaborative Threat assessment (SIFT). First, the technical and pragmatic challenges that motivate the research ideas are summarized. Next, a characterization of the activities for generating decision enabling information from multi-source data is provided. This characterization, called the ‘SIFT Method,’ specifies the SIFT automation support requirements. The SIFT architecture is described next. Finally, the paper summarizes the significance and benefits of the SIFT solution and outlines key areas that would benefit from additional research and development. The application of SIFT is expected to significantly reduce ‘data-to-decision’ time through the use of semantic and collaborative visual analytics techniques.