图书情报知识 ›› 2021, Vol. 38 ›› Issue (6): 12-20.doi: 10.13366/j.dik.2021.06.012

• 专业教育 • 上一篇    下一篇

“以人为本”的数据科学教育: 图书情报学科的新发展

吴丹,许浩   

  • 出版日期:2021-11-10 发布日期:2022-01-13

Human-centered Data Science Education: New Development of Library and Information Science

  • Online:2021-11-10 Published:2022-01-13

摘要: [目的/意义]旨在分析图书情报学科视角下数据科学教育的核心特征,有助于图书情报学科向数据科学融入的同时把握学科自身的核心优势,并彰显专业及人才培养特色。[研究设计/方法]通过归纳分析,凝练了数据科学的学科内涵及其与图书情报学科的相关关系,总结了全球图书情报学科开展数据科学教育的现状及其核心特征。[结论/发现] 数据科学与图书情报为两个独立学科,但交融趋势明显。图书情报学科正成为全球开展数据科学教育的重要力量;“以人为本”是图书情报学科视角下数据科学教育的核心特征,为培养兼具创新技术方法与深厚人文关怀的数据科学人才奠定了基础。[创新/价值]系统总结了图书情报学科视角下数据科学教育的核心特点与优势,为我国图书情报学科在积极融入数据科学过程中把握自身优势、完善数据科学教育体系、提升数据人才培养效能提供借鉴。

关键词: 数据科学, 数据科学教育, 以人为本, 图书情报, 学科展望, 人才培养, 学科交叉融合

Abstract: [Purpose/Significance]This paper aims to analyze the core characteristics of data science education from the perspective of library and information science. It is helpful for the integration of library and information science into data science, while maintaining its own core advantages. Moreover, it could showcase the features of the subject and its talent cultivation.
[Design/Methodology]Through inductive analysis, the disciplinary connotations of data science and its correlativity with libraryand information science were condensed. Moreover, the current status and core features of data science education in the field of library and information science all over the world were summarized.[Findings/Conclusion]Although data science and the subject of library and information science are two distinct fields, there is an obvious blending trend between them. The subject of library and information science has become the backbone force of data science education worldwide. From the standpoint of library and information science, "human-centered" is the core feature of data science education, which could lay a foundation for making data science talents familiar with innovative technical methods and minded with great humanistic care.[Originality/Value]The core features and superiority of data science education are systematically summarized from the perspective of library and information science in order to provide a reference for library and information science to keep its own strengths, perfect the data science education system, and improve talent cultivating effectiveness in the integration of library and information science into data science.

Keywords: Data science, Data science education, Human-centered, Library and information science, Disciplinary prospect, Talent cultivation, Disciplinary cross-fertilization and integration