信息资源管理学报 ›› 2025, Vol. 15 ›› Issue (3): 122-134.doi: 10.13365/j.jirm.2025.03.122

• 研究论文 • 上一篇    下一篇

数智驱动下科技知识协同机制与提炼路径的理论框架研究

项波1　颜兆萍1　潘卓娅2　余德建3　石进1   

  1. 1.南京大学信息管理学院，南京，210023；　
    2.中南财经政法大学工商管理学院，武汉，430073；　
    3.南京审计大学商学院，南京，211815
  • 出版日期:2025-05-26 发布日期:2025-06-16
  • 作者简介:项波，博士研究生，研究方向为大数据管理与应用、创新计量学；颜兆萍，博士研究生，研究方向为知识发现、技术创新；潘卓娅，硕士，研究方向为技术创新、知识产权评估；余德建，教授，博士，博士生导师，研究方向为科技计量学、决策理论；石进（通讯作者），教授，博士，博士生导师，研究方向为大数据分析与技术、情报学，Email：shijin@nju.edu.cn。
  • 基金资助:
    本文系国家社会科学基金重点项目“维护国家科技安全视域下技术锁定的形成机制、预警与突破对策研究“（24AGL002）及国家档案局科技项目“基于电网档案数据的生成式AI应用能力体系研究”（2024-X-025）的研究成果之一。

Theoretical Framework on Synergistic Mechanism and Extraction Strategy of Scientific and Technological Knowledge Driven by Data-Intelligence

Xiang Bo1　Yan Zhaoping1　Pan Zhuoya2　Yu Dejian3　Shi Jin1   

  1. 1.School of Information Management, Nanjing University, Nanjing, 210023;　
    2.School of Business Administration, Zhongnan University of Economics and Law, Wuhan, 430073;　
    3.School of Business, Nanjing Audit University, Nanjing, 211815
  • Online:2025-05-26 Published:2025-06-16
  • About author:Xiang Bo, Ph.D student, research interests include big data management and application, innometrics; Yan Zhaoping, Ph.D candidate, research interests include knowledge discovery, technological innovation; Pan Zhuoya, master, research interests include technological innovation, intellectual property evaluation; Yu Dejian, professor, Ph.D., Ph.D supervisor, research interests include informetrics in science and technology, decision theory; Shi Jin(corresponding author), professor, Ph.D., Ph.D supervisor, research interests include big data analysis and technology, informatics, Email: shijin@nju.edu.cn.
  • Supported by:
    This paper is one of the research outcomes of the key project funded by the National Social Science Foundation of China "Research on the formation mechanism, early warning and breakthrough countermeasures of technological lock-in under the perspective of safeguarding national scientific and technological security"(24AGL002), and the scientific and technological project funded by the National Archives Administration of China "Research on generative AI application ability system based on power grid archive data" (2024-X-025).

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摘要： 梳理科技知识的多方利益主体、多源异构数据及其协同机制，并明确大数据与智能化技术赋能的知识提炼路径，是促进数据要素价值实现的重要议题。依据DIKW链中数据到智慧的衍变过程，构建一个涉及高校、科研院所、企业、政府和公众等多主体的科技知识协同框架，并涵盖论文、专利、产品、政策和用户生成内容等多源数据；拓展科技知识提炼路径的前后端结构，并探讨智能化策略组合模式下的知识提炼成果及其多样化的服务场景。数智驱动下，科技知识在多方利益主体的引导下形成了双向且多维交织的协同模式，以促进知识供需的交互和匹配；智能化技术是拓宽科技知识范畴，探索知识场景化应用，推动数据要素价值创造的核心手段。

关键词: 数智驱动, 多源异构数据, 多方利益主体, 知识协同, 知识提炼

Abstract: It is the important issue to promote the value realization of data elements through clarifying the multiple stakeholders and multi-source heterogeneous data of scientific and technological knowledge, and their synergistic mechanism, as well as delineating the knowledge extraction paths empowered with big data and intelligent technology. Based on the process of data-to-wisdom derivation in the DIKW chain, this study constructed a synergistic framework of scientific and technological knowledge involving multiple stakeholders, such as universities, research institutes, enterprises, government and the public, covering multi-source data such as papers, patents, products, policies and user-generated content. Furthermore, this study expanded the front-end and back-end structures of scientific and technological knowledge extraction paths, and explored the knowledge extraction outcomes and their diverse service scenarios under intelligent strategy combination patterns. Driven by digital intelligence, scientific and technological knowledge has formed a bi-directional and multi-dimensional intertwined synergy pattern under the direction of multi-stakeholders to facilitate the interaction and matching of knowledge supply and demand.

Key words: Data-intelligence driven, Multi-source heterogeneous data, Multi-stakeholder, Knowledge synergy, Knowledge extraction

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