SemanticSpy: Suspect tracking using semantic data in a multimedia environment

Abstract

In this paper we describe SemanticSpy, a tool for tracking suspects and their activities around the globe. Using an RDF data store and a three-dimensional multimedia environment, SemanticSpy is able to bring semantic information to life. SemanticSpy utilizes a blend of semantic information and a media-rich environment that can display images, 3D models, and documents, and can play audio clips to give the user the ability to analyze information using the different types of media. We believe that this will help law enforcement officials gain insight into a suspect's behavior and give them the power to avert the next major crime or terrorist attack. Finally, we describe SemanticSpy's architecture and explain its advantages over other information environments. © Springer-Verlag Berlin Heidelberg 2006.