Improving National and Homeland Security through Context Knowledge Representation & Reasoning Technologies

Abstract

In the aftermath of the 9/11 tragedy it has became clear that the lack of effective information exchange among government agencies hindered the capability of identifying potential threats and preventing terrorism actions. It has been noted by the National Research Council that Although there are many private and public databases that contain information potentially relevant to counterterrorism programs, they lack the necessary context definitions (i.e., metadata) and access tools to enable interoperation with other databases and the extraction of meaningful and timely information1. This report clearly recognized the important problem that the semantic data integration research community has been studying. In this chapter, we describe the Laboratory for Information Globalization and Harmonization Technologies (LIGHT) developed at MIT. LIGHT arises from previous research, most notably the COntext INterchange (COIN) context mediation technology and the Global System for Sustainable Development (GSSD). Context Mediation technology addresses the above problem and deals directly with the integration of heterogeneous contexts (i.e. data meaning) in a flexible, scalable and extensible environment. This approach makes it easier and more transparent for receivers (e.g., applications, sensors, users) to exploit distributed sources (e.g., databases, web, information repositories, sensors). In this paper we define context as the assumptions of the source and receiver that affect correct interpretation of the meaning of the information. Receivers are able to specify their desired context so that there will be no uncertainty in the interpretation of the information coming from heterogeneous sources. The COIN context knowledge representation approach and associated reasoning tools significantly reduce the overhead involved in the integration of multiple sources and simplifies maintenance in an environment of changing source and receiver context. This technology is essential in the counter-terrorism environment in a number of areas including: (1) allowing for receivers (i.e., applications, analysts) to have multiple views of the same data (e.g., different semantic assumptions - two analysts may have a different meaning for Soviet Union depending on the application), (2) allowing for the collection of information into a single data warehouse, and (3) use in a dynamic federated environment where applications may have changing contexts and sources are added and removed from the grid. This approach is essential to the agile integration of information to support counter terrorism.