Indicators of Technological Emergence

衡量研究和开发活动的方法很多，但在衡量前沿研究课题方面存在差距。该项目开发了新的技术涌现指标，以支持研究人员、研究经理、企业和其他人确定科学和技术前沿的关键主题。区分前沿研究和开发活动可以为战略发展提供信息，并揭示新的机遇。此外，能够衡量紧急主题还可以更敏锐地评估研究计划。哪些国家、组织或个人对某一领域的进步贡献最大的指标提供了至关重要的竞争技术情报。该项目的新技术涌现指标侧重于前沿贡献，以补充一般科学、技术和创新指标。我们制定了一套指标，开发了软件例程来计算它们，并设计了报告和可视化来与不同的受众沟通，包括研究人员、管理者和政策制定者。该项目实现了一个构成技术涌现的四属性模型。新出现的主题应该证明术语的新颖性、持久性和加速增长，并表明研究社区的形成。该方法从全球研究出版物和专利数据库中提取关于给定科学和技术主题的记录。这项研究尝试了不同的方法来清理和巩固这些记录的主题内容。然后，该项目设计软件脚本来对主题的出现程度进行评分。然后，计算算法根据参与者在高度新兴主题上的工作程度，对给定研究领域的参与者进行评分，例如研究组织或国家。然后，通过9个不同的科技案例研究，研究了分数的构成和它们的表现。测试包括一系列跨领域和时间段的敏感性分析。这项测试试图通过分析新兴指标在预测随后一至三年期间的研究和开发活动方面的表现，来验证这些指标。这些新的技术涌现指标将与既定的科学和技术指标一起进行审查，以帮助评估研发能力和机会。该项目将探索应用涌现指标的方法，例如衡量政府资助计划如何推动尖端研究主题活动，或跟踪从研究到专利再到商业化领域的专题内容传播。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Extensive ways to measure research and development activity exist, but there is a gap in being able to measure frontier research topics. This project develops new indicators of technological emergence to support researchers, research managers, businesses, and others in identifying key topics at the frontiers of science and technology. Distinguishing cutting edge research and development activities can inform strategy development and reveal new opportunities. Being able to measure emergent topics additionally enables sharper research program assessment. Indicators of which countries, organizations, or individuals are contributing most to advances in a given domain provide vital competitive technical intelligence. The project's new technological emergence indicators focus on frontier contributions to complement general science, technology, and innovation indicators. We formulate a suite of indicators, develop software routines to calculate them, and devise reports and visualizations to communicate to different audiences, including researchers, managers, and policy makers.The project implements a four-attribute model of what constitutes technological emergence. Emergent topics should evidence term novelty, persistence, and accelerating growth, plus show formation of a research community. The approach extracts records on given science and technology topics from global research publication and patent databases. The research experiments with different ways to clean and consolidate those records' topical content. Then the project devises software scripts to score topics' degree of emergence. The computational algorithm then scores actors in given research areas, such as research organizations or countries, based on the extent to which the actors work on the highly emerging topics. The makeup of the scores and how they behave is then studied through nine diversified science and technology case studies. Testing includes a series of sensitivity analyses across fields and time periods. The testing seeks to validate the emergence indicators by analyzing their performance in predicting research and development activity in a subsequent one-to-three-year period. These new technological emergence indicators will be examined in conjunction with established science and technology metrics to help assess research and development capabilities and opportunities. The project will explore ways to apply the emergence indicators, such as gauging how government funding programs advance cutting edge research topic activity, or tracking diffusion of topical content from research to patents to commercialization arenas.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.