图书情报工作

图书情报工作 >

2025 , Vol. 69 >Issue 2: 35 - 44

DOI: https://doi.org/10.13266/j.issn.0252-3116.2025.02.004

研究论文

科技战略决策场景下的情报智慧数据建设与服务实践

  • 王学昭 ,
  • 王燕鹏 ,
  • 陈芳 ,
  • 陈小莉 ,
  • 赵萍 ,
  • 刘细文
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  • 1 中国科学院文献情报中心 北京 100190;
    2 中国科学院大学经济与管理学院信息资源管理系 北京 100190
王学昭，情报研究部主任，研究员，博士；王燕鹏，助理研究员，硕士；陈芳，副研究员，博士；陈小莉，副研究员，博士；赵萍，副研究员，硕士；刘细文，中心主任，研究员，博士，通信作者，E-mail：liuxw@mail.las.ac.cn。

收稿日期: 2023-08-18

  修回日期: 2024-04-18

  网络出版日期: 2025-01-25

基金资助

本文系中国科学院战略研究与决策支持系统建设专项“‘两个清单’编制、动态更新等研究支撑”（项目编号：GHJ-ZLZX-2023-19）和中国科学院文献情报能力建设专项“面向决策应用的智能情报分析模型研究”（项目编号：E2290433）、“面向重大科技问题场景的智能情报分析模型研究”（项目编号：E2290455）研究成果之一。

收起

Construction and Service of Intelligent Data Oriented to Strategic Decision-Making Scenarios in S&T

  • Wang Xuezhao ,
  • Wang Yanpeng ,
  • Chen Fang ,
  • Chen Xiaoli ,
  • Zhao Ping ,
  • Liu Xiwen
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  • 1 National Science Library, Chinese Academy of Sciences, Beijing 100190;
    2 Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190
Wang Xuezhao, department director, professor, PhD; Wang Yanpeng, assistant professor, master; Chen Fang, associate professor, PhD; Chen Xiaoli, associate professor, PhD; Zhao Ping, associate professor, master; Liu Xiwen, director, professor, PhD, corresponding author, E-mail: liuxw@mail.las.ac.cn.

Received date: 2023-08-18

  Revised date: 2024-04-18

  Online published: 2025-01-25

Supported by

This work is supported by the special project on Strategic Research and Decision Support System Construction of Chinese Academy of Sciences,titled “Research Support for the Compilation and dynamic Update of the ‘Two Lists’”(Grant No.GHJ-ZLZX-2023-19) and the special project on Building Documentation and Information Capacity of Chinese Academy of Sciences,titled “Research on Intelligent Analysis Model for Decision-making Applications”(Grant No.E2290433)&“Research on Intelligent Analysis Model for Major Scientific and Technological Issues Scenarios”(Grant No.E2290455).

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摘要

[目的/意义] 提出情报智慧数据概念，为新范式下的数据密集型、数据驱动科技情报工作提供理念和路径参考。[方法/过程] 全面总结相关情报工作实践，对情报智慧数据的概念及特征进行辨析和界定，明确其产生和流转方式，提出其建设原则、建设及服务模式，并以典型案例形式剖析面向科技战略决策场景的情报智慧数据建设与服务实践。[结果/结论] 情报智慧数据是情报研究的科研数据，主要包括情报原始数据、情报核心数据和情报衍生数据三类，体现情报人员对战略决策需求的精准理解和洞见，蕴含情报服务实践的长期经验积累和沉淀，是数据驱动的情报研究与服务的核心生产要素。情报智慧数据具有决策场景导向、专家智慧嵌入、数据类型多样、情报价值高、可拓展性强五个特征（SERVE），其建设以决策场景为牵引，与决策问题深度耦合，以经验到智慧、显性到隐性、结果导向到过程导向为原则，以情报数据可存储、情报方法可复用、情报结论可循证、情报知识可转移为目标，从决策场景预设和解析、决策问题组合及解答方案制定、情报智慧数据建设、情报服务成效反馈和升级四个流程环节开展。并以出口管制和重大科技问题等科技战略决策场景下的情报智慧数据建设为案例，阐述情报智慧数据建设的思路及其驱动的战略情报工作服务成效。

关键词： 科技战略决策; 情报智慧数据; 科研数据; 决策场景; 出口管制; 重大科技问题

本文引用格式

王学昭 , 王燕鹏 , 陈芳 , 陈小莉 , 赵萍 , 刘细文 . 科技战略决策场景下的情报智慧数据建设与服务实践[J]. 图书情报工作, 2025 , 69(2) : 35 -44 . DOI: 10.13266/j.issn.0252-3116.2025.02.004

Abstract

[Purpose/Significance] This paper attempts to put forward the concept of intelligent data to provide ideas and path references for data intensive and data-driven S&T intelligence work under the new paradigm. [Method/Process] This paper comprehensively summarized relevant intelligence work practices, analyzed and defined the concept and characteristics of intelligent data, clarified its generation and circulation mode, and put forward its construction principles, construction and service mode. And then, it explored the construction and service of intelligent data facing S&T strategic decision-making scenarios in the form of typical cases. [Result/Conclusion] Intelligent data is the “scientific research data” in the process of intelligence research and service, and is the core production element of data-driven intelligence research and services, which mainly includes three types, namely, intelligence raw data, intelligence core data, and intelligence derived data. It condenses the precise understanding and insights of intelligence personnel on strategic needs, contains longterm accumulation and precipitation of intelligence service. Intelligent data is characterized by decision scenario orientation, embedded expert wisdom, rich data types, high intelligence value density and strong extensibility (SERVE). Its construction should be guided by decision-making scenarios and deeply coupled with decision-making problems. The construction process should follow the principle of experience to intelligence, explicit to implicit, and result-oriented to process-oriented, and the aim of data storage, methods reuse, evidence-based conclusion and knowledge transfer. It is carried out from four aspects: decision-making scenario preset and analysis, decision-making problem combination and solution formulation, intelligent data construction, intelligence service effectiveness feedback and data upgrading. Taking the construction of intelligent data in the context of S&T strategic decision-making such as export control and major S&T issues as examples, this paper expounds the idea of intelligent data construction and the service effect of strategic intelligence work driven by it.

Key words： S&T strategic decision-making; intelligent data; scientific research data; decision scenario; export control major; S&T issues

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