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

这个合作项目(1212806，罗斯·T·惠特克，犹他大学；1212501，唐纳德·H·豪斯，克莱姆森大学；1212577，玛丽·赫加蒂，加州大学圣巴巴拉分校；1212790，迈克尔·K·林德尔，德克萨斯农工大学主校区)的目标是建立计算和认知基础，以捕捉和传达与预测模拟相关的不确定性，以便可视化这些预测的软件工具可以准确和有效地将关于这些信息的信息呈现给广泛的用户。三个示范应用被紧密整合到研究计划中：一个是空气质量管理，第二个是野火危险管理，第三个是飓风疏散管理。该项目是以系统的、端到端的方式审议不确定性可视化的第一次大规模努力，目的是制定一套一般原则和一套工具，以便准确和有效地为一系列具有国家重要性的决策进程传达适当程度的不确定性。这项工作的主要影响将是传达预测模拟的结果及其相关不确定性的方法和工具，从而在依赖这种预测的情况下更好地作出公共政策决策。预计在模拟和不确定性量化、可视化、感知和认知以及在存在不确定性的情况下进行决策方面会有科学贡献。结果将以各种方式在广泛的学术学科和应用领域广泛传播，并将在项目网站(http://visunc.sci.utah.edu).)上公布研究的多学科性质和参与研究小组的密切结合将为研究生和其他受训人员提供独特的教育环境，同时也扩大了对计算机科学的参与，使其超越传统的界限。

The goal of this collaborative project (1212806, Ross T. Whitaker, University of Utah; 1212501, Donald H. House, Clemson University; 1212577, Mary Hegarty, University of California-Santa Barbara; 1212790, Michael K. Lindell, Texas A&M University Main Campus) is to establish the computational and cognitive foundations for capturing and conveying the uncertainty associated with predictive simulations, so that software tools for visualizing these forecasts can accurately and effectively present this information about 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 general set of principles as well as a set of tools for accurately and effectively conveying the appropriate level of uncertainties for a range of decision-making processes of national importance.The primary impact of this work will be methods and tools for conveying the results of predictive simulations and their associated uncertainties, resulting in better informed public policy decisions in situations that rely on such forecasts. 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, and will be available at the project Web site (http://visunc.sci.utah.edu). The multidisciplinary nature of the research and the close integration of the participating research groups will provide a unique educational environment for graduate students and other trainees, while also broadening the participation in computer science beyond traditional boundaries.