图书情报工作

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2026 , Vol. 70 >Issue 1: 16 - 30

DOI: https://doi.org/10.13266/j.issn.0252-3116.2026.01.002

专题：构建面向强国建设的科技文献资源保障发展体系

术语资源建设与服务进展及展望

  • 陈学娟 ,
  • 许哲平 ,
  • 钱力 ,
  • 常志军
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  • 1 中国科学院文献情报中心 北京 100190;
    2 国家新闻出版署学术期刊新型出版与知识服务重点实验室 北京 100190;
    3 中国科学院大学经济与管理学院信息资源管理系 北京 100190
陈学娟，馆员，博士，E-mail：chenxuejuan@mail.las.ac.cn；许哲平，研究馆员，博士；钱力，正高级工程师，博士；常志军，正高级工程师，硕士。

收稿日期: 2024-09-04

  修回日期: 2025-03-01

  网络出版日期: 2026-01-16

基金资助

本文系全国科学技术名词审定委员会科研项目“国内外术语资源建设与服务模式研究”(项目编号:WT2022025)研究成果之一。

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Progress and Prospect of Terminology Resource Construction and Service

  • Chen Xuejuan ,
  • Xu Zheping ,
  • Qian Li ,
  • Chang Zhijun
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  • 1 National Science Library, Chinese Academy of Sciences, Beijing 100190;
    2 Key Laboratory of New Publishing and Knowledge Services for Scholarly Journals, Beijing 100190;
    3 Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190

Received date: 2024-09-04

  Revised date: 2025-03-01

  Online published: 2026-01-16

Supported by

This work is supported by the Scientific Research Project of China National Committee for Terminology in Science and Technology titled “Research on the Resource Construction and Service Mode of both Domestic and Overseas Terminology”(Grant No. WT2022025).

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摘要

[目的/意义] 术语是重要的语言资源，是话语体系的基础和核心要素。在人工智能和大语言模型迅猛发展的趋势下，系统梳理国内外术语资源建设与服务进展及问题，对于未来人工智能驱动术语研究及术语支撑人工智能发展具有重要价值。[方法/过程] 通过文献调研和网络调研，梳理国内外术语机构、政策及标准相关情况；基于文献知识图谱和理论研究内容，概述术语资源建设与服务研究热点；从术语平台基本属性、覆盖领域、功能模块等角度，分析国内外典型术语平台及特征；结合理论研究与应用案例，总结术语资源建设与服务的主要模式；最后，从加强术语资源建设和提升术语服务质量等方面提出建议与展望。[结果/结论] 术语资源建设与服务热点主题包括术语翻译、基于知识组织的术语服务、术语资源建设与服务方法技术、领域术语资源研究及应用等；国内外术语组织机构制定政策和标准保障术语工作的开展，建设多样化术语库平台；形成多方主体协同共建、科研项目驱动、专家参与、学术交流社区共建和人工智能技术支撑的术语资源建设模式，以及基于移动端、多媒体、专业词典、专业平台、学术交流传播和人工智能大模型的术语服务模式。当前及未来人工智能驱动的科学研究范式（AI4S）对术语资源建设和服务提出更高要求，应继续加强术语标准化和规范化研究，建设术语资源集成平台，打造面向AI4S的术语资源底座和智能化平台，完善组织协调和保障机制，加强术语人才培养和国际合作交流，以推动术语资源和服务的高效可持续发展。

关键词： 术语; 术语管理; 术语库; 术语资源建设; 术语服务

本文引用格式

陈学娟 , 许哲平 , 钱力 , 常志军 . 术语资源建设与服务进展及展望[J]. 图书情报工作, 2026 , 70(1) : 16 -30 . DOI: 10.13266/j.issn.0252-3116.2026.01.002

Abstract

[Purpose/Significance] Terminology is an important linguistic resource and serves as the foundation and core element of the discourse system. In the context of the rapid advancement of artificial intelligence and large language models, a systematic review of the progress and challenges of terminology resource construction and service at home and abroad holds significant value for AI-driven terminology research in the future and for terminology to support the development of artificial intelligence. [Method/Process] Through literature review and online research, this paper organized the situation of terminology institutions, policies, and standards both domestically and internationally. It explained the research hotspots of terminology resource construction and service based on literature knowledge mapping and theoretical research content. Typical terminology platforms were analyzed from various perspectives, including their fundamental attributes, domains, and functional modules. The modes of resource construction and service delivery for terminology were synthesized by integrating theoretical research with practical case studies. Finally, this paper offered suggestions and prospects for enhancing terminology resource development and improving service quality. [Result/Conclusion] The hot topics of terminology resource construction and service include terminology translation, terminology services based on knowledge organization, its methodologies and technologies, and the research and application of domain-specific terminology resources. Both domestic and international terminology organizations have established policies and standards to facilitate terminological work, and developed diverse terminology database platforms. Current modes of terminology resource construction involve collaborative efforts among various stakeholders, driven by scientific research projects, expert contributions, academic community building, and the support from artificial intelligence technologies. Terminology service models are based on mobile platforms, multimedia resources, professional dictionaries, specialized platforms, academic dissemination, and large AI models. The current and future paradigm of AI-driven scientific research（AI4S） places increasing demands on the construction and service of terminology resources. It is essential to continue strengthening research on terminology standardization and normalization, to build an integrated platform for terminology resources, to create a foundational and intelligent platform for AI4S terminology resources, to improve organizational coordination and support mechanisms, and to enhance the training of terminology professionals as well as international cooperation and exchange, in order to promote the efficient and sustainable development of terminology resources and services.

Key words： terminology; terminology management; terminology database; terminology resource construction; terminology services

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