TLS: Science & Technology Innovation Concept Knowledge-base (STICK): Monitoring, Understanding, and Advancing the (R)Evolution of Science & Technology Innovations

TLS：科学

• 批准号: 0915645
• 负责人: Ping Wang
• 金额: $ 71.86万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0915645&HistoricalAwards=false
• 关键词: TLS; Science; & Technology; Innovation

This project provides much needed data and tools for analyzing innovations of all possible outcomes, included failed innovations. This approach overcomes the bias in the science policy which studies only popular or ultimately successful innovations.Intellectual Merit: This comprehensive endeavor enables SciSIP researchers to build and test theories that explain the differentiated trajectories of science and technology innovations and their associated communities. The project also spans disciplinary boundaries by bridging the artificial divide in SciSIP research between the production and the use of innovations, piecing together a holistic view of the dynamic supply and demand in the innovation ecosystem. Specifically, the project builds a large-scale, multi-source, longitudinal database, Science & Technology Innovation Concept Knowledge-base (STICK), and develops a set of visual analytic tools for monitoring and understanding the emergence and revolution/evolution of innovations in three exemplar science and technology fields: information technology, biotechnology, and nanotechnology.The knowledge-base captures innovations, the individual and organizational actors associated with the innovations, and the relationships among the innovations and the actors through a hybrid approach that combines computational analysis of text (e.g., natural language processing) and social information processing (e.g., social tagging and collaborative writing by the users of the knowledge-base). State-of-the-art visualization tools are customized for SciSIP researchers and other innovation stakeholders to visualize innovation networks and analyze patterns and trends. The design of the knowledge-base and toolset is grounded in a demonstration study on the popularity of innovations. The study aims to address important questions concerning the complex relationships among innovations and the evolution of communities, with implications to the popularity and ultimate success of innovations.Broader Impacts: STICK is institutionalized at the University of Maryland at College Park as a free public service that offers web access to the data and tools developed in this project. This service also produces quarterly reports on the status of science and technology innovations, including the National Innovation Popularity Index, analogous to the Consumer Confidence Index for the state of the economy. This research-based service is an intuitive tool for science and technology education. For most fields where specialization is the theme, students' and the public's interests increase with the capability to monitor and make sense of the fast-changing arenas where innovations emerge, converge, and diverge. For scientists and engineers, STICK's visual analytic toolset helps accelerate scientific discoveries and innovations by identifying and establishing collaborations within and across innovation communities. Finally, STICK helps science and technology policy makers monitor and understand the evolutionary paths of innovations, appraise the significance of innovations in rigorously charted terrains, and proactively foster, promote, and advance innovations with benefits to the society.

该项目为分析创新的所有可能结果（包括失败的创新）提供了急需的数据和工具。这种方法克服了科学政策中只研究受欢迎的或最终成功的创新的偏见。智力价值：这一全面的努力使sciip的研究人员能够建立和测试解释科学和技术创新及其相关社区的差异化轨迹的理论。该项目还跨越了学科界限，弥合了科学知识产学研研究中创新产品和创新应用之间的人为鸿沟，将创新生态系统中动态供需的整体视图拼凑在一起。具体而言，该项目建立了一个大规模、多来源的纵向数据库——科技创新概念知识库（STICK），并开发了一套可视化分析工具，用于监测和理解信息技术、生物技术和纳米技术这三个典型科技领域的创新的出现和革命/演变。知识库通过结合文本计算分析（如自然语言处理）和社会信息处理（如知识库用户的社会标签和协作写作）的混合方法，捕捉创新、与创新相关的个人和组织行动者，以及创新与行动者之间的关系。最先进的可视化工具是为sciip研究人员和其他创新利益相关者定制的，用于可视化创新网络并分析模式和趋势。知识库和工具集的设计是基于对创新流行度的实证研究。本研究旨在解决创新与社区演变之间复杂关系的重要问题，并对创新的普及和最终成功产生影响。更广泛的影响：STICK在马里兰大学帕克分校制度化，作为一项免费的公共服务，为该项目开发的数据和工具提供网络访问。这项服务还提供关于科技创新状况的季度报告，包括国家创新普及指数，类似于反映经济状况的消费者信心指数。这项以研究为基础的服务是一种直观的科技教育工具。对于大多数以专业化为主题的领域，学生和公众的兴趣随着监测和理解创新出现、融合和分化的快速变化领域的能力而增加。对于科学家和工程师来说，STICK的可视化分析工具集通过识别和建立创新社区内部和之间的合作，帮助加速科学发现和创新。最后，STICK帮助科技政策制定者监测和理解创新的进化路径，在严格划定的领域评估创新的意义，并积极培育、促进和推进有利于社会的创新。