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

CGV：大型：协作研究：建模、显示和理解政策决策模拟中的不确定性

• 批准号: 1212790
• 负责人: Michael Lindell
• 金额: $ 31.91万
• 依托单位: Texas A&M University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1212790&HistoricalAwards=false
• 关键词: CGV; Large; Collaborative; Research; Modeling

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.

该合作项目的目标（1212806，Ross T. Whitaker，犹他大学；1212501，Donald H. House，克莱姆森大学；1212577，Mary Hegarty，加州大学圣巴巴拉分校；1212790，Michael K. Lindell，德克萨斯农工大学Main Campus）的目的是建立计算和认知基础，以捕获和传达与预测模拟相关的不确定性，因此用于可视化这些预测的软件工具可以准确有效地向广大用户呈现这些信息。该研究计划紧密结合了三个示范应用：一是空气质量管理，二是野火灾害管理，三是飓风疏散管理。该项目是第一个以系统、端到端的方式考虑不确定性可视化的大规模努力，其目标是开发一套通用原则以及一套工具，以准确有效地传达适当的信息。这项工作的主要影响将是传达预测模拟结果及其相关不确定性的方法和工具，从而在依赖于以下因素的情况下做出更明智的公共政策决策：这样的预测。 预计在模拟和不确定性量化、可视化、感知和认知以及存在不确定性的情况下做出决策等领域做出科学贡献。结果将以多种方式在广泛的学科和应用领域广泛传播，并将在项目网站 (http://visunc.sci.utah.edu) 上提供。 该研究的多学科性质以及参与研究小组的紧密结合将为研究生和其他学员提供独特的教育环境，同时也将计算机科学的参与范围扩大到传统界限之外。