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，由于认知能力的限制，当问题很复杂时，个人通常无法做出最佳决定。该跨学科项目采用视觉分析作为经济学的转化分析工具。研究人员使用视觉分析来改善决策并确定各种经济问题中知识创造的关键动机。该项目的工具套件允许用户交互探索数据集和决策空间，并比较替代假设并提出新的假设。此外，记录了与理解决策和知识产生有关的击键和信息，从而使研究人员可以大规模地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的价值的首次彻底调查。智能优点项目将来自经济学，电气和计算机工程和认知科学的科学家团队汇集在一起​​，这些科学很少有联系。这个三年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善个人和团体经济决策。项目的第二个目标是量化视觉分析对决策的有效性。视觉分析已成为许多领域的重要方法，例如医学，业务和物理科学，研究人员是第一个使用严格的实验方法量化其决策价值的人。最终目标是开发独特的视觉分析工具，以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：将视觉分析用于经济决策对政策制定者极为有益。这些工具的使用应该对分析复杂经济数据集的能力产生直接和积极的影响。这些工具也可以用于许多在分析推理方面存在问题的领域。在项目完成后导致的视觉分析工具将在线提供用于课堂使用，这将对教育产生广泛的影响。视觉分析工具的独特之处在于它们既简单又吸引了K-12学生，同时也对本科和研究生级别的学生有帮助。该项目将使用从大型且多元化的学生群体中提取的650多名本科生学科，并将为这些学生提供重要的现代研究方法。普渡大学的VSEEL实验室在本科和研究生级别的代表人数不足的少数群体的成员中有很好的记录，预计该项目将继续这一传统。这些学生中有40％以上是女性，大约有三分之一的人代表人数不足。根据过去的经验，我们希望至少有一半的博士学位。学生研究人员将是女性和/或少数民族。