Rigor in Information Analysis

Although all types of analytic processes, from those in scientific research to those used in legal analysis, purport to encourage high degrees of rigor, little legitimate research has been done to explore what the attributes of rigor might be or what processes are most likely to produce high quality analysis. CSEL’s rigor research was the first to do just that.

Related Publications

Rayo, M. F., & Murphy, T. B. (2016). Visual Analytics: Computational AND Representational Data Processing to Support Analytic Rigor.

Zelik, D. J., Patterson, E. S., & Woods, D. D. (2010). Measuring attributes of rigor in information analysis. Macrocognition metrics and scenarios: Design and evaluation for real-world teams, 65-83.

Trent, S. A., Smith, M. W., Zelik, D., Grossman, J., & Woods, D. D. (2009). Reading Intent and Other Cognitive Challenges in Intelligence Analysis. Advanced Decision Architectures for the Warfigher: Foundations and Technology, 307-321.

Zelik, D. J., Patterson, E. S., & Woods, D. D. (2007). Supporting the assessment of rigor: Representing analysis to create process insight. In 2nd Annual Workshop on Meta-Information Portrayal, Washington, DC.

Zelik, D. J., Patterson, E. S., & Woods, D. D. (2007). Judging Sufficiency: How Professional Intelligence Analysts Assess Analytical Rigor. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 51(4), 318–322. https://doi.org/10.1177/154193120705100436


CSEL Researchers