Visualizations: from complex analyses to actionable findings

  • Authors:
  • Laura G. Militello;Drew M. Bowers;Thomas R. Boehnlein;Robert B. Olding;Keith Ambrose

  • Affiliations:
  • University of Dayton Research Institute;University of Dayton Research Institute;University of Dayton Research Institute;University of Dayton Research Institute;KLSS

  • Venue:
  • NDM'09 Proceedings of the 9th Bi-annual international conference on Naturalistic Decision Making
  • Year:
  • 2009

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Abstract

Motivation - To provide visualizations that will support high-level decision makers in leveraging findings from analyses conducted using modeling & simulation techniques. Research approach - Cognitive systems engineering methods were used to examine the decision making process as it exists today, as well as identify goals, challenges and information needs at different phases. Research limitations/Implications - This is ongoing work. The strengths and limitations of the design concepts have not yet been assessed experimentally. Originality/Value - The design concepts resulting from this research have the potential to increase the accessibility of findings from complex multivariate analyses. Presenting results from modeling and simulation analyses in the form of actionable findings will likely increase the value of these powerful analytic tools. Take away message - A key challenge to realizing the potential value of sophisticated modeling & simulation techniques is in creating effective visualizations for communicating complex multivariate relationships. Simple, familiar visualizations may be the most effective.