Building Community and a New Data Infrastructure for Science Policy

为科学政策建立社区和新的数据基础设施

• 批准号: 1262447
• 负责人: Jason Owen-Smith
• 金额: $ 49.98万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-15 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1262447&HistoricalAwards=false
• 关键词: Building; Community; New; Data; Infrastructure

This project creates and maintains infrastructure and community to support policy relevant social science research. It uses newly available STAR METRICS data on how universities spend federal research grants to examine the scientific, social and economic impact of federally funded academic research. Infrastructure includes shared research tools and datasets. The community spans researchers in multiple disciplines, academic administrators, and state and federal policy makers. Employing STAR METRICS data and utilizing infrastructure for its access and use the research community can provide systematic answers to questions such as: What scientific collaborations are directly supported by research funding? What indirect effects do federal grants exert on regional economies and labor markets? The first question can be answered with systematic study of the structure and productivity of scientific collaboration networks using fine-grained information on who is paid to work on the same scientific grants. In doing so, this project is the first to characterize the productivity of campus-wide, federally funded science on 11 large university campuses. The second question can be answered using the same data source to analyze payments to vendors for scientific equipment, supplies, etc. By analyzing the distribution, geographic location, and industry of vendors that supply federally funded research, this project offers the first comprehensive picture of the effects of federal R&D spending on economic resilience and job creation via companies that support university research. These and other community research endeavors provide compelling cases for large scale, sustained research to assess the US science ecosystem and the full public value of federal support for scientific research. Broader impacts. The community and infrastructure developed by this project support a range of ongoing research projects; the results are of immediate interest to policy makers and academic administrators. Insights derived from this research can inform the allocation of resources on campus, decisions about how to pursue cutting edge scientific research and even the design and allocation of space in research facilities. At the national and state level, this project contributes to the development of a rigorous science of science policy that can inform decisions about how to allocate public resources for R&D by providing systematic evidence about the productivity of different approaches to organizing research and the larger social and economic results of discovery and learning on research university campuses.

该项目创建并维护基础设施和社区，以支持政策相关的社会科学研究。它使用关于大学如何使用联邦研究经费的最新 STAR METRICS 数据来检查联邦资助的学术研究的科学、社会和经济影响。 基础设施包括共享研究工具和数据集。 该社区涵盖多个学科的研究人员、学术管理人员以及州和联邦政策制定者。 利用 STAR METRICS 数据并利用基础设施来访问和使用研究界可以为以下问题提供系统答案：哪些科学合作是由研究经费直接支持的？联邦拨款对地区经济和劳动力市场产生哪些间接影响？第一个问题可以通过系统地研究科学合作网络的结构和生产力来回答，使用关于谁在相同的科学资助下工作的细粒度信息。 通过这样做，该项目是第一个描述 11 个大型大学校园内联邦政府资助的全校园科学生产力的项目。 第二个问题可以使用相同的数据源来分析向供应商支付的科学设备、用品等的付款来回答。通过分析提供联邦政府资助研究的供应商的分布、地理位置和行业，该项目提供了第一个全面的图片联邦研发支出对经济弹性和通过支持大学研究的公司创造就业机会的影响。 这些和其他社区研究工作为大规模、持续的研究提供了令人信服的案例，以评估美国科学生态系统以及联邦对科学研究的支持的全部公共价值。更广泛的影响。 该项目开发的社区和基础设施支持一系列正在进行的研究项目；政策制定者和学术管理人员对研究结果有直接兴趣。从这项研究中获得的见解可以为校园资源的分配、如何进行尖端科学研究的决策，甚至研究设施的空间设计和分配提供信息。 在国家和州一级，该项目有助于制定严格的科学政策，通过提供有关组织研究的不同方法的生产力以及更大的社会和群体的系统证据，为如何分配公共资源用于研发的决策提供信息。研究型大学校园发现和学习的经济成果。