Indicators of Technological Emergence

衡量研究和开发活动的方法广泛存在，但在能够衡量前沿研究课题方面存在差距。该项目开发了新的技术新兴指标，以支持研究人员、研究经理、企业和其他方面确定科学和技术前沿的关键主题。区分前沿研究和发展活动可以为战略发展提供信息，并揭示新的机会。能够衡量紧急主题还可以更准确地评估研究项目。哪些国家、组织或个人对某一特定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，并设计报告和可视化，以与不同的受众交流，包括研究人员、管理人员和政策制定者。该项目实现了构成技术涌现的四属性模型。新兴课题应具有新颖性、持久性和加速增长的特点，并表现出一个研究共同体的形成。该方法从全球研究出版物和专利数据库中提取给定科学和技术主题的记录。本研究尝试用不同的方法对这些文献的专题内容进行清理和整理。然后设计软件脚本对话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（如研究组织或国家）的参与者进行评分。然后通过9个不同的科技案例研究来研究分数的构成及其表现。测试包括一系列跨领域和时间段的敏感性分析。该测试旨在通过分析新兴指标在预测随后一至三年的研发活动方面的表现来验证这些指标。这些新技术的出现指标将与现有的科学和技术指标一起进行审查，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，例如衡量政府资助项目如何推动前沿研究主题活动，或跟踪主题内容从研究到专利再到商业化领域的传播。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。

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.