Title: CGV: Large: Collaborative Research: Modeling, Display, and Understanding Uncertainty in Simulations for Policy Decision Making

This material is based upon work supported by the National Science Foundation under Grant Numbers:

• 1212806 – University of Utah (PI: R. Whitaker)
• 1212501 – Clemson University (PI: D. House)
• 1212577 – University of California-Santa Barbara (PI: M. Hegarty)
• 1540469 – University of Washington (PI: M. Lindell)

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Abstract: The goal of this collaborative project is to establish the foundations for capturing and conveying the uncertainty associated with predictive simulations, so that future tools for visualizing these predictions will accurately and effectively present information about their uncertainty to a wide range of users. Three demonstration applications are closely integrated into the research plan: one in air quality management, a second in wildfire hazard management, and a third in hurricane evacuation management. This project is the first large-scale effort to consider the visualization of uncertainty in a systematic, end-to-end manner, with the goal of developing a generalizable set of techniques and procedures for accurately and effectively conveying the appropriate level of uncertainties in a wide range of decision-making processes of national importance.

The key impact of this work will be better informed decisions in simulation-assisted problem solving, arising from tools for visualizing data that can accurately and effectively convey the appropriate level of uncertainties to users. Scientific contributions are expected in the areas of simulation and uncertainty quantification, visualization, perception and cognition, and decision making in the presence of uncertainty. Results will be broadly disseminated in a variety of ways across a wide range of academic disciplines and application areas. The multidisciplinary nature of the research and the close integration of the participating research groups will provide a unique educational environment for all involved, while also broadening the participation in computer science beyond traditional boundaries.