1 Xiaoyu Wang UNC Charlotte Erin Miller START Center, U. Maryland Kathleen Smarick START Center, U Maryland William Ribarsky UNC Charlotte Remco Chang.

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Presentation transcript:

1 Xiaoyu Wang UNC Charlotte Erin Miller START Center, U. Maryland Kathleen Smarick START Center, U Maryland William Ribarsky UNC Charlotte Remco Chang UNC Charlotte Investigative Visual Analysis of Global Terrorism

2/21  Definition of Terrorism  “The threatened or actual use of illegal force and violence by a non-state actor to attain a political, economic, religious or social goal through fear, coercion or intimidation [1,2].”  Definition of Terrorists  Any non-state actor engaging in terrorism is defined to be a terrorist in the Global Terrorism Database (GTD). 1. LAFREE G., DUGAN L.: Introducing the global terrorism database. Terrorism and Political Violence 19, 2 (2007), 181– NATIONAL CONSORTIUM FOR THE STUDY OF TERRORISM AND RESPONSES TO TERRORISM: Global terrorism database

3/21

4/21  Terrorism activities throughout the world between  Contains over 60,000 incidents  119 dimensions for recording the events (weapons used, number of injuries, etc)  Approximately 2,000 unique entities

5/21  Understanding terrorism is a grand challenge for the Dept of Homeland Security (DHS) and the National Visual Analytics Consortium (NVAC).  Other agencies such as DoD, STRATCOM, and JIPOE are also interested in the area. 1. GUO D., LIAO K., MORGAN M.: Visualizing patterns in a global terrorism incident database. Environment and Planning B: Planning and Design 34, 1 (2007), 767–784.

6/21  Visual Analysis of Terrorism != Social Networks  Social network on terrorism  OntoVis by Shen, Ma, and Eliassi-Rad  Social Action by Adam Perer and Schneiderman  Geospatial approach  Guo, Liao, and Morgan from Penn State  GeoVista by Penn State  Improvise by Chris Weaver  Other Tools  Sandbox and GeoTime by Occulus  Why aren’t there more?

7/21  Big Picture:  Event-based investigative analysis  Visually analyze the activities of entities  Trend comparison using dimensions  Identify trends and patterns of events  Search-by-example of temporal patterns  Look for similar behaviors

8/21 Visual GTD Flow Chart Entity Relationships (Investigative Vis) Dimensional Relationships (ParallelSets) Entity Analysis (Search By Example) C. Ziemkiewicz, X. Wang, A. Godwin, W. Dou, R. Chang, R. Kosara, and W. Ribarsky. Global Terrorism Visualization. Poster Presented at DHS University Network Summit, 2008

9/21 Visual GTD Flow Chart Entity Relationships (Investigative Vis) Dimensional Relationships (ParallelSets) Entity Analysis (Search By Example) C. Ziemkiewicz, X. Wang, A. Godwin, W. Dou, R. Chang, R. Kosara, and W. Ribarsky. Global Terrorism Visualization. Poster Presented at DHS University Network Summit, 2008

10/21  Fundamental investigative concept:  Where : a certain geo-location or region on map.  When : a spot or continues span along time line.  Who : individual entity or a group of entities  What : any physical tool or method.  Why : motivations or reasons.  Highly interactive exploratory tool  Flexible entrance points.  Swift updates in coordinated views.  Details on demand The 5 W’s

11/21 WHERE WHO WHEN Comparison and Shoebox WHAT System Overview

12/21  Designed to be easy and intuitive.  Illustrates the activity patterns of entities.  Multi-group selection helps in comparing activities of different entities. Where

13/21  Use of ThemeRiver to display categorical information.  Understand groups’ temporal patterns and trends over time. When

14/21  Dual Roles:  Selection of entities (“terrorist names” tab)  Displays selected entities (“intermediate results” tab) Who

15/21  Organizes categorical dimensions  Allows for filtering of activities What

16/21  Shoebox provides a container for collecting entities that are under investigation  Comparison view supports temporal comparisons between entities. Shoebox and Comparison

17/21  Scenario One :  Linking Incidents to Reveal Global Strategy ▪ Who -> Where -> When -> What - >  Scenario Two :  Discovering Unexpected Temporal Patterns ▪ What -> Who -> Why Scenarios

18/21 WH Y ? WH Y ? This group’s attacks are not bounded by geo- locations but instead, religious beliefs. Its attack patterns changed with its developments. Scenarios 1: Revealing Global Strategy

19/21 Domestic Group A geographically- bounded entity in the Philippines. The ThemeRiver shows its rise and fall as an entity and its modus operandi. Scenario 2: Discovering Unexpected Temporal Patterns

20/21  Contribution  Created a comprehensive set of tools for visually analyzing global terrorism activities.  Our tool models after one of the principles of investigation, the 5 W’s.  Using coordinated views and high interaction to allow an investigator to explore the data and discover trends and patterns.

21/21 Questions? Thank you!

22/21

23/21  Can operational or investigative processes and methods be modeled into an exploratory visualization?  Example: ▪ Occulus Sandbox models after the use of “post-it” notes ▪ Investigative GTD models the 5 W’s  How can we integrate visual exploration with process modeling? ▪ Bank of America ▪ Department of Transportation

24/21  Support reasoning systems.  Provide online version for mass audience.  Combine knowledge from Social Science perspectives.