A Department of Homeland Security Center of Excellence led by the University of Maryland

New Analytical Methods for the Exploitation of Open-Source Structured Databases to Enhance Situational Awareness for Effective Counter-WMD Strategies


New Analytical Methods for the Exploitation of Open-Source Structured Databases to Enhance Situational Awareness for Effective Counter-WMD Strategies

Other START Researchers: 
Markus Binder

Project Details

Abstract: 

A question that is central to activities to combat weapons of mass destruction (WMD) is to understand which characteristics of terrorist groups are most closely associated with the decision to pursue chemical, biological, radiological, and nuclear (CBRN) weapons --characteristics that can serve as early warning indicators of intent and capability. This project addresses the question by both enhancing and leveraging existing human terrain datasets relevant to violent non-state actors, in order to develop new analytical tools to model human networks engaged in the pursuit of CBRN weapons and related asymmetric activities. The project will optimize open-source structured databases for WMD analysis, and researchers will recalibrate existing models using validated data. The question of how networks (relations among actors at varying scales) and human terrain data (information on human population and societies) available in databases be jointly leveraged is addressed utilizing a tapestry of new analytic methods for expanding the focus of database-oriented research. This will include moving from causal “factors” to an emphasis as well on actors. It will also involve turning the usual statistical models (with their emphasis on relations among variables) “inside out,” thus revealing networks of actors connected to one another by varying degrees of profile similarity, which we will study in reference to conventional social networks such as alliance ties among terrorist groups and in reference to actors’ pursuit of CBRN weapons.

The interest in social networks and CBRN-optimized databases also leads to methods for turning configurational analysis, the study of multiple configurations of variables that lead to an outcome, into a tool for identifying cases most likely to exhibit a dependent variable of interest; in this research, the cases are violent non-state actors, and the dependent variable is CBRN use or pursuit. The project will provide a suite of these new analytical methods for identifying CBRN actors as well as recommendations for interdicting them to national security decision makers based on analyses.

This project is led by Ronald Brieger, with Gary Ackerman, Victor Asal, H. Brinton Milward and R. Karl Rethemeyer.

More information can be found at http://www.u.arizona.edu/~breiger/TANC.html.

Timeframe

Project Period: 
March 2010 to March 2014

Selected Publications

News References