Jason Dalton

Spatial Forecast Methods for Terrorist Events in Urban Environments

Terrorist events such as suicide bombings are rare yet extremely destructive events. Responses to such events are even rarer, because they require forecasting methods for effective prevention and early detection. While many forecasting methods are available, few are designed for conflict scenarios. This paper builds on previous work in forecasting criminal behavior using spatial choice models. Specifically we describe the fusion of two techniques for modeling the spatial choice of suicide bombers into a unified forecast that combines spatial likelihood modeling of environmental characteristics with logistic regression modeling of demographic features. In addition to describing the approach we also provide motivation for the fusion of the methods and contrast the results obtained with those from the more common kernel density estimation methods that do not account for variation in the event space. We give an example of successful use of this combined method and an evaluation of its performance. We conclude that the fusion method shows improvement over other methods and greater scalability for combining larger numbers of spatial forecasting methods than were previously available.

Applying the HL7 reference information model to a clinical data warehouse

Large-scale data integration efforts to support clinical and biological research can be greatly facilitated by the adoption of standards for the representation and exchange of data. As part of a large project to design the necessary architecture for multi-institutional sharing of disparate biomedical data, we explored the potential of the HL7 reference information model (RIM) for representing the data stored in a local academic clinical data warehouse. A necessary first step in information exchange with such a warehouse is the development and utilization of tools for transforming between local data schemes and standards-based conceptual data models. We describe our initial efforts at mapping clinical concepts from a relational data warehouse to the HL7 RIM.

WebCAT: the design and implementation of the Web-based crime analysis toolkit

Last year, a team in the Department of Systems Engineering at the University of Virginia developed a Web-based crime analysis toolkit (WebCAT). This Web-based system allows for information sharing and cross-jurisdictional analysis between the various law enforcement agencies throughout Virginia. However, this system was not deployed. This years capstone team has improved Web-CATs functionality, robustness, and quality of analysis to enable deployment. This work has been done in the context of the whole systems lifecycle: (1) analysis; (2) design; (3) integration; (4) testing; and (5) evaluation. The capstone team has added a number of components to improve data sharing and crime analysis. These new components to WebCAT, among others, have improved the capabilities of crime analysts in terms of (1) quality of analysis; (2) increased speed of performing an analysis; (3) minimal cost necessary to design, implement, use, and maintain the application

WebCAT: the design, analysis and implementation of a Web-based crime analysis toolkit

A team within the System and Information Engineering Department, along with the Virginia Department of Criminal Justice Services, have been developing a Web-based crime analysis toolkit (WebCAT) for the past four years. WebCAT, an online system, facilitates the sharing of statewide crime incident data throughout Virginia law enforcement agencies. It further provides tools for data and spatial analysis. For the past three years, teams worked to develop prototypes of the system. This year focused on the deployment of WebCAT for use by the state of Virginia, through creating enhanced querying functions, more robust analysis tools, and improved interface usability. Further, the team increased security and administrative functions to aid in system oversight and safety. The team used the systems lifecycle through the analysis, design, implementation, testing, and evaluation of WebCAT. The results increased the capacity of data provided to analysts, provides data and spatial analysis tools, and improved system usability.

Facilitating information sharing among law enforcement agencies: improving the geospatial repository for analysis and safety planning

The primary barrier to comprehensive crime analysis in United States is a lack of information sharing between law enforcement agencies. A particularly egregious form of this problem is the failure to share spatial data. This situation prevents geographically and functionally connected agencies from performing cross jurisdictional analysis. The Department of Systems and Information Engineering at the University of Virginia is working in partnership with the National Institute of Justice (NIJ) to create a solution to this problem; the geospatial repository for analysis and safety planning (GRASP). GRASP is a Web application that serves as an online spatial data repository and utilizes geographic information system (GIS) technology to facilitate data sharing among law enforcement agencies. The system provides verified users the ability to view and share spatial data over the Internet in a secure environment. Since its inception, the GRASP system has gone through many changes in design and functionality. This year, the focus was on evolving from a previously centralized system to a distributed design architecture. The team modified the system to be distributable by installation CD-ROM. Furthermore, the capstone team replaced the previous proprietary translation software with an open source software to eliminate any licensing fees associated with adoption of GRASP. In addition, security options for GRASP users were added. The product of this years work is a largely nonproprietary, decentralized GRASP system, modified to be distributed by installation CD to law enforcement agencies around the country.

Facilitating public safety analysis through enhanced information sharing: improving the geospatial repository for analysis and safety planning

The University of Virginia Systems and Information Engineering Department is part of a six-year project commissioned by the National Institute of Justice to develop the geospatial repository for analysis and safety planning, GRASP. GRASP is a Web application that allows for the viewing and sharing of spatial data over the Internet. GRASP is a system that allows verified users to upload spatial data, and in turn are rewarded with full access to all public data stored in the database. For the past three years, student teams have progressively added to the design and development of GRASP. During the summer of 2003, GRASP shifted to an implementation phase that focuses on the active recruitment of new data contributors across the United States. To enable this shift in focus, the GRASP Websites usability and functionality have been improved by implementing new software, upgrading old hardware, and conducting usability tests. These improvements have reduced the time required by the systems administrators. The changes have also enabled an 86% decrease in the time required for data sharing between users of different jurisdictions

Improving GRASP: a geospatial repository for analysis and safety planning

To increase public safety levels in communities, researchers and law enforcement agencies analyze spatial data to reveal crime patterns and relationships. For the past two years, teams of students have worked with the National Institute of Justice (NIJ) to create a centralized data repository for storing this data. This repository, named the Geospatial Repository for Analysis and Safety Planning (GRASP), streamlines the data collecting process. The system has been successful, yet several drawbacks remain. These drawbacks include cost, response time of queries, lack of security features, unintuitive interface, and the inability to conform to federal standards for storing data. To alleviate these problems, our team changed the database backend of the system, added security settings, developed a visual mapping component, and reformatted the metadata to conform to the federal standards. At the conclusion of the project, GRASP was

Design of a radiological response software tool for use by first responders

6000 cheaper, 97 percent faster, and complied with all federal standards.

Mapping from a clinical data warehouse to the HL7 Reference Information Model.

The Capstone team has worked in conjunction with Defense Group Inc. (DGI) to develop a software tool called radiological assessment device (RAD). RAD includes seven tools that perform the following functions: 1) Searches for information regarding sealed sources. 2) Searches for information about historical radiological accidents/incidences. 3) Provides relevant assessment recommendations. 4) Allows for conversion between mass and activity. 5) Provides a mechanism for equivalent radiological unit conversions. 6) Returns critical exposure output based on user inputs relative to the type of scenario encountered. Through the above functionality, the goal is to support first responder decision making during radiological emergency response.