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。区分尖端的研究和开发活动可以为战略制定提供信息，并揭示新的机会。能够衡量新兴的主题，还可以更清晰地评估研究项目。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性技术情报。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，开发软件程序来计算它们，并设计了报告和可视化，以传达给不同的受众，包括研究人员，管理人员和政策制定者。该项目实施了一个四属性模型，什么构成了技术的出现。新兴主题应该证明术语的新奇，持久性和加速增长，并显示研究社区的形成。该方法从全球研究出版物和专利数据库中提取关于特定科学和技术主题的记录。该研究实验了不同的方法来清理和巩固这些记录的主题内容。然后设计软件脚本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，对特定研究领域的参与者（如研究组织或国家）进行评分。然后，通过九个多元化的科学和技术案例研究的分数和他们如何表现的化妆。测试包括跨领域和时间段的一系列敏感性分析。测试旨在通过分析新兴指标在预测随后一至三年内的研发活动方面的表现来验证新兴指标。这些新的技术新兴指标将与既定的科学和技术指标一起审查，以帮助评估研究和开发能力和机会。该项目将探索应用新兴指标的方法，例如衡量政府资助计划如何推动前沿研究课题活动，或跟踪主题内容从研究到专利再到商业化领域的扩散。该奖项反映了NSF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。

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.