Characterizing the intelligence analysis process through a longitudinal field study: Implications for visual analytics

Youn Ah Kang, John Stasko

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


While intelligence analysis has been a primary target domain for visual analytics system development, relatively little user and task analysis has been conducted within this area. Our research community's understanding of the work processes and practices of intelligence analysts is not deep enough to adequately address their needs. Without a better understanding of the analysts and their problems, we cannot build visual analytics systems that integrate well with their work processes and truly provide benefit to them. In order to close this knowledge gap, we conducted a longitudinal, observational field study of intelligence analysts in training within the intelligence program at Mercyhurst College. We observed three teams of analysts, each working on an intelligence problem for a 10-week period. Based on the findings of the study, we describe and characterize processes and methods of intelligence analysis that we observed, make clarifications regarding the processes and practices, and suggest design implications for visual analytics systems for intelligence analysis.

Original languageEnglish
Pages (from-to)134-158
Number of pages25
JournalInformation Visualization
Issue number2
Publication statusPublished - 2014 Apr

Bibliographical note

Funding Information:
This work was supported by the National Science Foundation under award IIS-0915788 and the VACCINE Center, a Department of Homeland Security’s Center of Excellence in Command, Control and Interoperability.

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition


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