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: 2332573
• 负责人: Anna Harvey
• 金额: $ 123.51万
• 依托单位: Social Science Research Council
• 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=2332573&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.

思想行业：一种原型系统，用于衡量研究投资对区域公司和就业建议的影响，以测试端到端数据驱动的试点框架中的第一个，用于评估研究投资对特定技术领域对相应区域公司和工作的影响。 《芯片与科学法》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建立技术中心。鉴于当前的数据和方法，可以挑战此类投资在芯片和科学法中描述的十个技术领域的影响，因为AI，量子计算，生物制造等新技术很难将其映射到特定领域，并且也很快就会发展。目前没有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，Ideas的行业项目将通过外展和社区参与与各种利益相关者互动，创建一个原型仪表板，以有效访问可访问的可视化和相关信息的交流，并为成果的有效性开发指标。该项目的最初重点是俄亥俄州 - 俄亥俄州 - 一个庞大的潜水国家，其中已经建立了许多必要的数据基础设施，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）。该项目将建立计划和合作伙伴关系，以将这一努力从一个国家扩展到国家一级。对投资影响的跟踪以多种方式受到挑战。很难确定对与现有分类系统不符的快速发展的跨学科技术领域的投资。现有的方法和数据还无法识别受新兴技术研究投资影响的公司，工作和个人先验的研究投资，这使传统的样本调查方法不足。由于数据限制和隐私要求，可以在区域层面上进行报告。及时报告的要求也受到相关数据源的当前状态的阻碍，这些数据源在生成数据时暴露了很大的时间滞后。该项目通过使用基于数据链接和归纳性，迭代性限制的框架来解决这些挑战，以利用已建立的网络效应。这种方法的核心是，研究资金可以使创新者的工作产生价值和熟练者的工作，这些人然后通过知识工人的流动性创造的网络为经济做出了贡献。拟议的新方法将公司分类为基于：（1）这些公司雇用的研究培训的个人以及（2）提供投入的研究项目。这是通过将与实时文献计量/文本数据，大学行政记录和州劳动力数据联系在一起的连接，并使用“雪球”逻辑来识别科学投资的行业和劳动力效应，而这些逻辑难以衡量，这些逻辑难以衡量，这实现了。该项目建立在现有的，证明项目团队具有丰富经验的平台的基础上。这项工作的新颖性在于其综合，可扩展的迭代性质。该项目将吸引区域社区，并为扩展到该国其他地区的扩张，计划和支持。该项目将开发一个原型仪表板，随着时间的流逝，可以在迭代上进行改进和扩展。这项工作还将开发用于系统构建的方法和模板，这些方法和模板可以与其他分析工作集成在一起，从而允许在多个数据源和方法之间进行三角测量。该框架旨在通过三种方式扩展：（1）包括更多的技术领域和其他状态； （2）通过合并其他数据源，例如有关大专证书和学位获得者的信息； （3）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的利益相关者团体，即大学领导者，区域创新生态系统领导者和国家代理机构负责人紧密合作，以帮助告知系统的设计，为成功制定指标，并改善系统。与利益相关者社区的宣传和参与将有助于确保原型的最广泛使用，并为计划的未来扩展提供支持和势头。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响标准通过评估来诚实地诚实地获得了支持。