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 proceedingConference contribution

16 Scopus citations


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 languageEnglish (US)
Title of host publicationCHI'05 Extended Abstracts on Human Factors in Computing Systems, CHI EA'05
Number of pages4
StatePublished - 2005
EventConference on Human Factors in Computing Systems, CHI EA 2005 - Portland, OR, United States
Duration: Apr 2 2005Apr 7 2005

Publication series

NameConference on Human Factors in Computing Systems - Proceedings


OtherConference on Human Factors in Computing Systems, CHI EA 2005
Country/TerritoryUnited States
CityPortland, OR


  • 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


Dive into the research topics of 'Visualization in law enforcement'. Together they form a unique fingerprint.

Cite this