Convergence Accelerator Phase I (RAISE): Building the Federalism Data and Advanced Statistics Hub (FDASH)

NSF融合加速器支持以团队为基础的多学科努力，解决国家重要性的挑战，并在不久的将来显示出可交付成果的潜力。“融合加速器”第一阶段项目的更广泛影响和潜在社会效益是，开发一个关于美利坚合众国各州政府机构和公共政策的单一、全面的数据和分析来源。该资源被该项目称为联邦主义数据和高级统计中心（F-DASH），通过整合前所未有的政策、社会和经济数据，以及开发分析工具，使用户能够轻松地探索、可视化和分析这些数据，有可能为研究人员、教育工作者和公众提供重大利益。该项目是一项融合研究工作，涵盖了应用统计学、计算机科学、地理学、哲学、政治学、公共政策和社会学。它还利用技术专长和渠道，通过与开放国家、公共卫生教育工作者协会和美国政治科学协会国家政治和政策科等几个伙伴组织的合作，将工作与用户联系起来。这些合作和F-DASH的整体努力应该促进研究人员的突破，从业者的创新，教师的新课堂材料，以及公民参与的新机会。国家层面的公共政策对公民有直接影响吗？日常生活，包括健康、教育和就业，第一阶段的F-DASH项目将提供关于这些和其他主题的即时和可获取的信息。公共政策研究是研究联邦制度下代议制政府如何将公民偏好转化为影响社会的法律。美国各州是了解政策选择影响的理想场所，因为各州经常针对重要挑战尝试不同的解决方案。然而，美国联邦制的分散性阻碍了对各州经济、社会或其他结果进行比较的努力。事实上，由于每个州数据采集的独特挑战，研究人员必须经常参与50个单独的数据收集过程。因此，研究人员或政府机构通常只收集他们解决特定问题所需的最低限度的信息。此外，他们通常不共享这些数据，而那些公开数据的人也没有明显的方法将他们的数据与他人收集的数据联系起来。F-DASH将为美国各州有关制度、政策及其影响的数据收集和分析提供一个集中的位置。这些数据将包括政府制定的政策文件，如立法法案，以及常用的衍生指标。此外，F-DASH将促进复杂数据库设计的创新，并为对文本挖掘、大规模关系数据库、静态和动态网络分析以及许多其他主题感兴趣的研究人员提供广泛的测试平台。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The NSF Convergence Accelerator supports team-based, multidisciplinary efforts that address challenges of national importance and show potential for deliverables in the near future. The broader impact and potential societal benefit of this Convergence Accelerator Phase I project is the development of a single, comprehensive source of data and analysis on governing institutions and public policies across the states of the United States of America. This resource, which the project calls the Federalism Data and Advanced Statistics Hub (F-DASH), has the potential to provide significant benefits to researchers, educators, and the public by integrating an unprecedented amount policy, social, and economic data, as well as developing analytic tools that will allow users to easily explore, visualize, and analyze these data. The project is a convergence research effort encompassing applied statistics, computer science, geography, philosophy, political science, public policy, and sociology. It also draws on technical expertise and channels for connecting the work to users through collaborations with several partner organizations, such as Open States, the Society for Public Health Educators, and the State Politics and Policy Section of the American Political Science Association. These collaborations and the overall F-DASH effort should facilitate breakthroughs by researchers, innovations by practitioners, new classroom materials for teachers, and new opportunities for engagement by citizens. Public policy at the state level has a direct impact on citizens? daily lives, including their health, education, and employment, and this phase I F-DASH project will provide immediate and accessible information on these and other topics. The study of public policy is the study of how representative government in a federal system translates citizen preferences into laws that impact society. The American states represent an ideal venue for understanding the effects of policy choices because states routinely experiment with different solutions to important challenges. However, the decentralized nature of the American federal system impedes efforts to compare economic, social, or other outcomes across the states. Indeed, researchers must often engage in 50 separate data collection processes due to the unique challenges of data acquisition in each state. Consequently, researchers or government agencies commonly collect only the minimum of what they need to address a particular question. Moreover, they often do not share these data, and those who do make data publicly available have no obvious way to connect their data to data collected by others. The F-DASH will provide a centralized location for data collection and analysis related to institutions, policies, and their implications in the American states. These data will include policy documents produced by government, such as legislative bills, as well as commonly-used derivative measures. In addition, the F-DASH will promote innovation in complex database design and provide an extensive test-bed for researchers interested in text mining, large-scale relational databases, static and dynamic network analysis, and many other topics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.