TLS - Applied Visual Analytics for Economic Decision-Making

TLS - 用于经济决策的应用可视化分析

• 批准号: 0915605
• 负责人: David Ebert
• 金额: $ 37.7万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0915605&HistoricalAwards=false
• 关键词: TLS; Applied; Visual; Analytics; Economic

Scientists have discovered that individuals are often unable to make optimal decisions when problems are complex due to limitations on cognitive abilities. This interdisciplinary project employs visual analytics as a transformational analytical tool in economics. The investigators use visual analytics to improve decision making and identify key motivations in knowledge creation in various economic problems. The project?s suite of tools allows users to interactively explore datasets and decision spaces as well as compare alternate hypothesis and develop new hypothesis. Further, keystrokes and information pertinent to understanding decision-making and knowledge generation are recorded, allowing the investigators to make predictions about the decision-making process on a broad scale and providing guidance for theoretical models of decision-making. This is the first thorough investigation of the value of visual analytics for economic decision-making.Intellectual MeritThis project brings together a team of scientists from economics, electrical and computer engineering and cognitive science, fields that are rarely linked. The fundamental objective of this three-year project is to improve individual and group economic decision making through the introduction of visual analytics as a necessary tool for dealing with complex information sets. The project?s second objective is to quantify the effectiveness of visual analytics for decision making. Visual analytics has emerged as an important approach to data analysis in many fields such as medicine, business, and the physical sciences, and the investigators are the first to quantify its value for decision-making using rigorous experimental methods. The final objective is to develop a unique suite of visual analytics tools to help economists and policy-makers analyze large datasets. Broader Impact: The use of visual analytics for economic decision-making is extremely beneficial to policy makers. Use of these tools should have an immediate and positive impact on the capacity to analyze complex economic datasets. These tools can also be used in many fields with problems in analytical reasoning. The visual analytics tools that result at the completion of the project will be made available online for classroom use, which will have a broad impact on education. Visual analytics tools are unique in that they are both simple enough and captivating for K-12 students, while also being helpful to students at the undergraduate and graduate levels. The project will use over 650 undergraduate student subjects drawn from a large and diversified student population and will provide these students with important exposure to modern research methods. The VSEEL laboratory at Purdue has an excellent record of involving members of underrepresented minority groups at both the undergraduate and graduate levels and this project is expected to continue this tradition. Over 40 percent of these student subjects will be women and about one-third will be underrepresented minorities. Based on past experience, we expect that at least one-half of the Ph.D. student researchers will be women and/or minorities.

科学家发现，当问题复杂时，由于认知能力的限制，个人往往无法做出最佳决定。这个跨学科的项目使用视觉分析作为经济学中的一种变革性分析工具。研究人员使用视觉分析来改进决策，并在各种经济问题中确定知识创造的关键动机。该项目-S工具套件允许用户交互地探索数据集和决策空间，以及比较备选假设和开发新假设。此外，还记录了与理解决策和知识生成相关的击键和信息，使调查人员能够在广泛的范围内对决策过程进行预测，并为决策的理论模型提供指导。这是对视觉分析对经济决策价值的第一次彻底调查。智力价值这个项目汇集了来自经济学、电气和计算机工程以及认知科学的科学家团队，这些领域很少联系在一起。这个为期三年的项目的基本目标是通过引入视觉分析作为处理复杂信息集的必要工具来改进个人和群体的经济决策。S项目的第二个目标是量化视觉分析在决策中的有效性。视觉分析已经成为医学、商业和物理科学等许多领域数据分析的重要方法，研究人员首先使用严格的实验方法量化了它对决策的价值。最终目标是开发一套独特的可视化分析工具，帮助经济学家和政策制定者分析大型数据集。更广泛的影响：使用可视化分析进行经济决策对政策制定者非常有利。这些工具的使用应该会对分析复杂经济数据集的能力产生立竿见影的积极影响。这些工具还可以用于分析推理中有问题的许多领域。项目完成后产生的视觉分析工具将在网上供课堂使用，这将对教育产生广泛影响。视觉分析工具是独一无二的，因为它们对K-12学生来说足够简单和迷人，同时也对本科生和研究生水平的学生有帮助。该项目将使用650多个本科生科目，这些科目来自庞大而多样化的学生群体，并将为这些学生提供接触现代研究方法的重要机会。普渡大学的VSEEL实验室在吸收本科生和研究生中代表性不足的少数群体成员方面有着出色的记录，该项目预计将延续这一传统。这些学生中超过40%将是女性，大约三分之一将是代表不足的少数族裔。根据过去的经验，我们预计至少一半的博士生研究人员将是女性和/或少数民族。