With the increase of terrorist activity around the world, it has become more important than ever to analyze and understand these activities over time. Although the data on terrorist activities are detailed and relevant, the complexity of the data has rendered the understanding and analysis difficult. We present a visual analytical approach to effectively identify related entities such as terrorist groups, events, locations, etc. based on a 2D layout. Our methods are based on sequence comparison from bioinformatics, modified to incorporate the element of time. By allowing the user the freedom to link entities by their activities over time, we provide a new framework for comparison of event sequences. Our scoring mechanism is robust and flexible, giving the user the flexibility to define the extent to which time is considered in aligning entities. Incorporated with high interactivity, the user can efficiently navigate through tens of thousands of records recorded in over a hundred dimensions of data by choosing combinations of categories to examine. Exploration of the terrorist activities in our system reveals relationships between entities that are not easily detectable using traditional methods.

Date Published: 15 April 2008
PDF: 8 pages
Proc. SPIE 6983, Defense and Security 2008: Special Sessions on Food Safety, Visual Analytics, Resource Restricted Embedded and Sensor Networks, and 3D Imaging and Display, 69830G (15 April 2008); doi: 10.1117/12.778084

Published in SPIE Proceedings Vol. 6983:
Defense and Security 2008: Special Sessions on Food Safety, Visual Analytics, Resource Restricted Embedded and Sensor Networks, and 3D Imaging and Display
Moon S. Kim; Kaunglin Chao; William J. Tolone; William Ribarsky; Sergey I. Balandin; Bahram Javidi; Shu-I Tu, Editor(s)