Abstract

http://ssrn.com/abstract=904676
 
 

Footnotes (8)



 


 



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


Nazli Choucri


Massachusetts Institute of Technology (MIT) - Department of Political Science

Stuart Madnick


Massachusetts Institute of Technology (MIT) - Sloan School of Management

Michael Siegel


Massachusetts Institute of Technology (MIT) - Sloan School of Management

April 2006

MIT Sloan Research Paper No. 4600-06
CISL Working Paper No. 2006-03

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.

Number of Pages in PDF File: 26

Keywords: Homeland Security, Context Knowledge Representation, Reasoning Technologies

working papers series





Download This Paper

Date posted: May 26, 2006  

Suggested Citation

Choucri, Nazli and Madnick, Stuart and Siegel, Michael, Improving National and Homeland Security through Context Knowledge Representation & Reasoning Technologies (April 2006). MIT Sloan Research Paper No. 4600-06; CISL Working Paper No. 2006-03. Available at SSRN: http://ssrn.com/abstract=904676 or http://dx.doi.org/10.2139/ssrn.904676

Contact Information

Nazli Choucri (Contact Author)
Massachusetts Institute of Technology (MIT) - Department of Political Science ( email )
77 Massachusetts Avenue
Cambridge, MA 02139
United States

Stuart E. Madnick
Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )
E53-321
Cambridge, MA 02142
United States
617-253-6671 (Phone)
617-253-3321 (Fax)
Michael Siegel
Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )
E53-323
Cambridge, MA 02142
United States
617-253-2937 (Phone)
617-258-7579 (Fax)
Feedback to SSRN


Paper statistics
Abstract Views: 743
Downloads: 119
Download Rank: 140,949
Footnotes:  8

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo3 in 1.328 seconds