农业图书情报学报 ›› 2024, Vol. 36 ›› Issue (3): 32-45.doi: 10.13998/j.cnki.issn1002-1248.24-0173

• 研究论文 • 上一篇    下一篇

AI就绪的科技情报数据资源建设模式研究

钱力1,2,3, 刘志博1,2, 胡懋地1,2,3, 常志军1,2,3   

  1. 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 100049;
    3.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
  • 收稿日期:2024-02-03 出版日期:2024-03-05 发布日期:2024-06-24
  • 作者简介:钱力,博士,正高级工程师,硕士生导师,中国科学院文献中心数据资源部,主任,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,主任,研究方向为科技文献大数据与知识挖掘。刘志博,研究生,中国科学院大学,研究方向为智慧数据。胡懋地,高级工程师,硕士生导师,中国科学院文献情报中心,研究方向为知识图谱。常志军,正高级工程师,硕士生导师,中国科学院文献情报中心数据资源部,副主任,研究方向为大数据处理
  • 基金资助:
    国家重点研发计划项目“科技文献内容深度挖掘及智能分析关键技术和软件”(2022YFF0711902); 国家社科基金重大项目“大数据驱动的科技文献语义评价体系研究”(21&ZD329)

Construction Model of AI-Ready for Scientific and Technological Intelligence Data Resources

QIAN Li1,2,3, LIU Zhibo1,2, HU Maodi1,2,3, CHANG Zhijun1,2,3   

  1. 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;
    3. Key Laboratory of New Publishing and Knowledge Services for Scholarly Journals, Beijing 100190
  • Received:2024-02-03 Online:2024-03-05 Published:2024-06-24

摘要: [目的/意义]AI就绪建设是连接当前先进AI技术与应用场景之间发展间隔的重要举措,本研究旨在探讨和设计科技情报领域的AI就绪的科技情报数据资源建设方法,为情报领域的AI就绪建设提供参考。[方法/过程]本研究基于国内外各界AI就绪发展现状的调研结果,对AI就绪建设进行了初步定义,并从含义范畴、建设角度、建设对象、建设原则、控制维度和模式类型六大方面对科技情报领域的AI就绪建设模式进行系统地探讨和设计。[结果/结论]当前全球AI发展迅速,科技情报领域作为科学研究与先进技术应用的前沿观察与战略指导性学科,应当建立AI就绪的科技情报数据资源体系。研究提出了AI就绪的科技情报数据资源建设的总模式,并结合现有建设实践探讨并呈现科技情报数据资源AI就绪化建设的具体实践路径。

关键词: AI就绪, 科技情报, 数据资源建设, 科技文献大模型, GPT-4o

Abstract: [Purpose/Significance] The new quality productivity advancing AI technology, especially exemplified by large language models (LLMs), is rapidly updating and attracting wide attention. In order to accelerate the implementation of AI technologies, it is urgent for advanced AI technologies to acquire support from knowledge resources in scientific and technological (S & T) information and libraries. Meanwhile, S & T information provides significant potential service scenarios for the application of AI technologies such as LLMs. This study aims to explore and design the method and path for constructing AI-ready data resources in the field of S & T information, and proposes a comprehensive and operable construction model that adapts to the new technical environment of AI, thereby facilitating comprehensive readiness in the field of intelligence. [Method/Process] This study first focuses on the concept and development status of AI-ready construction, and examines the development of AI-ready construction at home and abroad from three aspects: governments, enterprises and research institutions. The survey shows that the application of artificial intelligence has been highly valued by various fields of scientific research and production. However, the groundwork and preparation for AI applications are still relatively lagging behind, and AI tools cannot be fully implemented in key application scenarios due to the lack of high-quality and refined data resources. Based on the research results, the study made a preliminary definition of AI-ready construction, that is, we defined AI-ready construction as: the various development and improvement actions to adapt the object to the AI technical environment and promote the long-term benefits. The research then focuses on the field of S & T information, and systematically discusses and designs the AI-ready construction mode in the field of S & T information from six aspects: connotation category, construction angle, construction object, construction principle, control dimension and types of construction mode. [Results/Conclusions] The construction of AI-ready S & T information resources is a comprehensive and multi-angle transformation and upgrading process, which is located between the knowledge resource end and the intelligence application end. It is carried out in four aspects, including standards, methods, tools and platforms. The main content of the construction includes channels of AI technology, data transformation, data resources, and data management. At the same time, the construction is comprehensively controlled by six principles and four control dimensions. Besides, this study proposes the way of the practical construction of AI-ready S & T data resources, including the construction of intelligent data systems, and the construction of integrated platforms for the whole life cycle of S&T information data. The path reflects the process of the variation of knowledge resources from diversification to organization and then to integration, which not only serves the scientific information field itself, but also provides more intelligent, convenient, rich and powerful S&T information support for various fields. In the future, it is hoped that further research can delve into more micro and practical aspects, review the specific characteristics of different AI technologies, and provide more detailed suggestions for specific application scenarios at the operational level, providing a solid guarantee for scientific research institutions to achieve the leading strategic position in research and development.

Key words: AI-ready, scientific and technological information, data resource construction, LLMs for scientific and technological literature, GPT-4o

中图分类号:  G25;TP271

引用本文

钱力, 刘志博, 胡懋地, 常志军. AI就绪的科技情报数据资源建设模式研究[J]. 农业图书情报学报, 2024, 36(3): 32-45.

QIAN Li, LIU Zhibo, HU Maodi, CHANG Zhijun. Construction Model of AI-Ready for Scientific and Technological Intelligence Data Resources[J]. Journal of Library and Information Science in Agriculture, 2024, 36(3): 32-45.