Visualization in law enforcement

Hsinchun Chen; Homa Atabakhsh; Chunju Tseng; Byron Marshall; Siddharth Kaza; Shauna Eggers; Hemanth Gowda; Ankit Shah; Tim Petersen; Chuck Violette

doi:10.1145/1056808.1056893

Visualization in law enforcement

Hsinchun Chen, Homa Atabakhsh, Chunju Tseng, Byron Marshall, Siddharth Kaza, Shauna Eggers, Hemanth Gowda, Ankit Shah, Tim Petersen, Chuck Violette

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

17 Scopus citations

Abstract

Visualization techniques have proven to be critical in helping crime analysis. By interviewing and observing Criminal Intelligence Officers (CIO) and civilian crime analysts at the Tucson Police Department (TPD), we found that two types of tasks are important for crime analysis: crime pattern recognition and criminal association discovery. We developed two separate systems that provide automatic visual assistance on these tasks. To help identify crime patterns, a Spatial Temporal Visualization (STV) system was designed to integrate a synchronized view of three types of visualization techniques: a GIS view, a timeline view and a periodic pattern view. The Criminal Activities Network (CAN) system extracts, visualizes and analyzes criminal relationships using spring-embedded and blockmodeling algorithms. This paper discusses the design and functionality of these two systems and the lessons learned from the development process and interaction with law enforcement officers.

Original language	English (US)
Title of host publication	CHI'05 Extended Abstracts on Human Factors in Computing Systems, CHI EA'05
Pages	1268-1271
Number of pages	4
DOIs	https://doi.org/10.1145/1056808.1056893
State	Published - 2005
Event	Conference on Human Factors in Computing Systems, CHI EA 2005 - Portland, OR, United States Duration: Apr 2 2005 → Apr 7 2005

Publication series

Name	Conference on Human Factors in Computing Systems - Proceedings

Other

Other	Conference on Human Factors in Computing Systems, CHI EA 2005
Country/Territory	United States
City	Portland, OR
Period	4/2/05 → 4/7/05

Keywords

Association network
Crime analysis
Crime network
Lawenforcement
Social network analysis
Spatial and temporal visualization

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Graphics and Computer-Aided Design

Access to Document

10.1145/1056808.1056893

Cite this

Chen, H, Atabakhsh, H, Tseng, C, Marshall, B, Kaza, S, Eggers, S, Gowda, H, Shah, A, Petersen, T & Violette, C 2005, Visualization in law enforcement. in CHI'05 Extended Abstracts on Human Factors in Computing Systems, CHI EA'05. Conference on Human Factors in Computing Systems - Proceedings, pp. 1268-1271, Conference on Human Factors in Computing Systems, CHI EA 2005, Portland, OR, United States, 4/2/05. https://doi.org/10.1145/1056808.1056893

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title = "Visualization in law enforcement",

abstract = "Visualization techniques have proven to be critical in helping crime analysis. By interviewing and observing Criminal Intelligence Officers (CIO) and civilian crime analysts at the Tucson Police Department (TPD), we found that two types of tasks are important for crime analysis: crime pattern recognition and criminal association discovery. We developed two separate systems that provide automatic visual assistance on these tasks. To help identify crime patterns, a Spatial Temporal Visualization (STV) system was designed to integrate a synchronized view of three types of visualization techniques: a GIS view, a timeline view and a periodic pattern view. The Criminal Activities Network (CAN) system extracts, visualizes and analyzes criminal relationships using spring-embedded and blockmodeling algorithms. This paper discusses the design and functionality of these two systems and the lessons learned from the development process and interaction with law enforcement officers.",

keywords = "Association network, Crime analysis, Crime network, Lawenforcement, Social network analysis, Spatial and temporal visualization",

author = "Hsinchun Chen and Homa Atabakhsh and Chunju Tseng and Byron Marshall and Siddharth Kaza and Shauna Eggers and Hemanth Gowda and Ankit Shah and Tim Petersen and Chuck Violette",

year = "2005",

doi = "10.1145/1056808.1056893",

language = "English (US)",

isbn = "1595930027",

series = "Conference on Human Factors in Computing Systems - Proceedings",

pages = "1268--1271",

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note = "Conference on Human Factors in Computing Systems, CHI EA 2005 ; Conference date: 02-04-2005 Through 07-04-2005",

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T1 - Visualization in law enforcement

AU - Chen, Hsinchun

AU - Atabakhsh, Homa

AU - Tseng, Chunju

AU - Marshall, Byron

AU - Kaza, Siddharth

AU - Eggers, Shauna

AU - Gowda, Hemanth

AU - Shah, Ankit

AU - Petersen, Tim

AU - Violette, Chuck

PY - 2005

Y1 - 2005

N2 - Visualization techniques have proven to be critical in helping crime analysis. By interviewing and observing Criminal Intelligence Officers (CIO) and civilian crime analysts at the Tucson Police Department (TPD), we found that two types of tasks are important for crime analysis: crime pattern recognition and criminal association discovery. We developed two separate systems that provide automatic visual assistance on these tasks. To help identify crime patterns, a Spatial Temporal Visualization (STV) system was designed to integrate a synchronized view of three types of visualization techniques: a GIS view, a timeline view and a periodic pattern view. The Criminal Activities Network (CAN) system extracts, visualizes and analyzes criminal relationships using spring-embedded and blockmodeling algorithms. This paper discusses the design and functionality of these two systems and the lessons learned from the development process and interaction with law enforcement officers.

AB - Visualization techniques have proven to be critical in helping crime analysis. By interviewing and observing Criminal Intelligence Officers (CIO) and civilian crime analysts at the Tucson Police Department (TPD), we found that two types of tasks are important for crime analysis: crime pattern recognition and criminal association discovery. We developed two separate systems that provide automatic visual assistance on these tasks. To help identify crime patterns, a Spatial Temporal Visualization (STV) system was designed to integrate a synchronized view of three types of visualization techniques: a GIS view, a timeline view and a periodic pattern view. The Criminal Activities Network (CAN) system extracts, visualizes and analyzes criminal relationships using spring-embedded and blockmodeling algorithms. This paper discusses the design and functionality of these two systems and the lessons learned from the development process and interaction with law enforcement officers.

KW - Association network

KW - Crime analysis

KW - Crime network

KW - Lawenforcement

KW - Social network analysis

KW - Spatial and temporal visualization

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T3 - Conference on Human Factors in Computing Systems - Proceedings

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BT - CHI'05 Extended Abstracts on Human Factors in Computing Systems, CHI EA'05

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Y2 - 2 April 2005 through 7 April 2005

ER -

Visualization in law enforcement

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Keywords

ASJC Scopus subject areas

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