Collaborative Research: Industries of Ideas: A prototype system for measuring the effects of research investments on regional firms and jobs

协作研究：创意产业：衡量研究投资对区域企业和就业影响的原型系统

• 批准号: 2332572
• 负责人: Bruce Weinberg
• 金额: $ 166.32万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2332572&HistoricalAwards=false
• 关键词: Collaborative; Research; Industries; Ideas; prototype

The Industries of Ideas: A prototype system for measuring the effects of research investments on regional firms and jobs proposes to test a first of its kind end-to-end data-driven pilot framework for assessing the impact of research investment in specific technology areas on corresponding regional firms and jobs. The CHIPS and Science Act supports investments in key technologies to drive innovation, create jobs, and establish technology hubs across the United States. Understanding the impacts of such investments in the ten technology areas described in the CHIPS and Science Act can be challenging given current data and methods because new technologies such as AI, quantum computing, biomanufacturing and others are difficult to map to specific sectors and are also quickly evolving. There are no current means to systematically identify all the industries, employers, and workers which those technologies might affect. To address these challenges the Industries of Ideas project will engage with various stakeholders through outreach and community engagement, create a prototype dashboard for effective accessible visualization and communication of relevant information, and develop metrics for effectiveness of the outcomes. The initial focus of this project is on the State of Ohio — a large, diverse state with much of the requisite data infrastructure already in place and with two rapidly emerging technology areas, viz., Artificial Intelligence (AI) and Electric Vehicles (EV). The project will establish plans and partnerships for scaling this effort from a single state to the national level. The tracking of investment impacts is challenging in multiple ways. Identifying investments in rapidly evolving, trans-disciplinary technology areas that do not align with existing classification systems is difficult. Existing methods and data also cannot identify the companies, jobs, and individuals affected by research investments in emerging technologies a priori, rendering traditional sample survey methods inadequate. Reporting at the regional level can be challenging due to data limitations and privacy requirements. Requirements for timely reporting are also hindered by the current state of relevant data sources which exhibit significant time lags in producing the data. The project addresses these challenges by using a framework based on data linkage and inductive, iterative expansion of inclusion restrictions to take advantage of established network effects. Core to the approach is the idea that research funding enables the work of innovators, which generates valuable ideas and skilled people who then contribute to the economy through networks created by the mobility of knowledge-workers. The proposed novel approach categorizes firms into "idea industries" based on: (1) the research-trained individuals employed by those firms and (2) the research projects to which they supply inputs. This is achieved by linking together close to real-time bibliometric/textual data, university administrative records, and state workforce data, and using a “snowball” logic to identify industry and workforce effects of scientific investments that are difficult to measure otherwise. The project builds upon existing, proven platforms with which the project team has significant experience. The novelty of the work is in its integrative, scalable, iterative nature. The project will engage the regional community and create measures, plans and support for expansion to other regions of the country. The project will develop a prototype dashboard that can be improved and expanded upon iteratively over time. The work will also develop methods and templates for system building that can be integrated with other analysis efforts, allowing for triangulation across multiple data sources and approaches. The framework is designed to be expanded in three ways: (1) by including more technology areas and additional states; (2) by incorporating additional data sources like information on post-secondary certificate and degree recipients; and (3) by transitioning from prototype development to a software platform and data production system suitable for a wealth of use cases. The project will collaborate closely with three major stakeholder groups, viz., university leaders, regional innovation ecosystem leaders, and state agency leaders to help inform the design of the system, develop metrics for success, and make improvements to the system. The outreach and engagement with the stakeholder community will help secure the broadest possible use of the prototype and build support and momentum for planned future expansions.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.

创意产业：一个衡量研究投资对区域公司和就业影响的原型系统建议测试第一个端到端数据驱动的试点框架，以评估特定技术领域的研究投资对相应区域公司和就业的影响。CHIPS和科学法案支持对关键技术的投资，以推动创新，创造就业机会，并在美国各地建立技术中心。考虑到当前的数据和方法，了解这些投资对CHIPS和科学法案中描述的十个技术领域的影响可能具有挑战性，因为人工智能，量子计算，生物制造等新技术很难映射到特定部门，而且也在快速发展。目前还没有办法系统地确定这些技术可能影响的所有行业、雇主和工人。为了应对这些挑战，创意产业项目将通过外联和社区参与与各种利益相关者互动，创建一个原型仪表板，以有效地访问相关信息的可视化和沟通，并制定成果有效性的衡量标准。该项目的最初重点是俄亥俄州--一个大的、多样化的州，大部分必要的数据基础设施已经到位，并且有两个快速新兴的技术领域，即，人工智能（AI）和电动汽车（EV）。该项目将制定计划和建立伙伴关系，将这一努力从一个州扩大到国家一级。跟踪投资影响在多个方面具有挑战性。很难确定在与现有分类系统不一致的快速发展的跨学科技术领域的投资。现有的方法和数据也无法事先确定受新兴技术研究投资影响的公司、工作和个人，这使得传统的抽样调查方法不够充分。由于数据限制和隐私要求，区域一级的报告可能具有挑战性。有关数据来源的现状也妨碍了及时报告的要求，因为这些数据来源在产生数据方面存在很大的时间滞后。该项目通过使用基于数据链接和归纳的框架来应对这些挑战，迭代扩展包容性限制，以利用既定的网络效应。这一方法的核心思想是，研究资金使创新者的工作成为可能，从而产生有价值的想法和技术人才，这些人然后通过知识工作者的流动性所建立的网络为经济做出贡献。这种新的方法将企业分为“创意产业”，其依据是：（1）这些企业雇佣的受过研究训练的个人;（2）他们提供投入的研究项目。这是通过将实时文献计量/文本数据、大学行政记录和州劳动力数据紧密联系在一起，并使用“滚雪球”逻辑来确定难以以其他方式衡量的科学投资对行业和劳动力的影响来实现的。该项目建立在现有的、经过验证的平台之上，项目团队在这些平台上拥有丰富的经验。这项工作的新奇在于它的综合性、可扩展性和迭代性。该项目将使区域社区参与，并制定措施、计划和支持，以便向该国其他地区推广。该项目将开发一个原型仪表板，可以随着时间的推移不断改进和扩展。这项工作还将为系统建设开发方法和模板，这些方法和模板可以与其他分析工作相结合，从而允许跨多个数据源和方法进行三角测量。该框架旨在通过三种方式进行扩展：（1）通过包括更多的技术领域和其他州;（2）通过纳入更多的数据源，如有关中学后证书和学位获得者的信息;以及（3）通过从原型开发过渡到适合大量用例的软件平台和数据生产系统。该项目将与三个主要利益攸关方群体密切合作，即：大学领导人、区域创新生态系统领导人和国家机构领导人帮助为系统设计提供信息，制定成功指标，并改进系统。与利益相关者社区的外联和参与将有助于确保原型的最广泛使用，并为计划中的未来扩展建立支持和动力。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。