Science Policy Research Report: Metrics for Evaluating Big Science

科学政策研究报告：评估大科学的指标

• 批准号: 1735824
• 负责人: William Bianco
• 金额: $ 4.99万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2018-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1735824&HistoricalAwards=false
• 关键词: Science; Policy; Research; Report; Metrics

Big Science programs such as the International Space Station or the Large Hadron Collider expensive and their true worth is fully realized only after years or decades. The high cost of sustaining these programs often crowds out other scientific research. To address this challenge, this project reviews mechanisms to gauge the future productivity of Big Science projects. The analysis will identify waypoint mechanisms and assess their predictive power. This research will give government agencies and the scientific community an overview of tools for understanding how best to evaluate and manage Big Science projects, thereby increasing the efficient use of public and private dollars to advance scientific progress. Survey results of program directors at NSF, DOE, NASA, and NIH characterize current best-practices for making interim assessments of infrastructure-heavy research programs. New candidate waypoints are developed, and tested by analyzing the scientific research supported by the International Space Station. The quantitative analyses will control for a host of project-specific factors such as the sub-discipline of the research, the background and characteristics of the principal investigator, and the initial funding date to ascertain the degree to which candidate waypoints provide statistical rigor to predict the eventual attainment of valued outcomes.

国际空间站或大型强子对撞机等大型科学项目成本高昂，它们的真正价值只有在几年或几十年后才能完全实现。维持这些项目的高昂成本往往会排挤其他科学研究。 为了应对这一挑战，该项目审查了衡量大科学项目未来生产力的机制。该分析将确定航路点机制并评估其预测能力。这项研究将为政府机构和科学界提供一些工具的概述，以了解如何最好地评估和管理大科学项目，从而提高公共和私人资金的有效利用，以推动科学进步。 NSF、DOE、NASA 和 NIH 项目主管的调查结果描述了当前对基础设施密集型研究项目进行中期评估的最佳实践。 通过分析国际空间站支持的科学研究，开发并测试了新的候选航路点。 定量分析将控制一系列特定于项目的因素，例如研究的子学科、主要研究者的背景和特征以及初始资助日期，以确定候选路径点提供统计严谨性的程度，以预测最终实现的有价值的结果。