用户数据维度的数字资源评价方法及实例——以电子科技大学图书馆为例

Methods and Examples of the Digital Resource Evaluation in the User Data Dimension——Taking the Library of University of Electronic Science and Technology of China as an Example

[目的/意义]以电子科技大学图书馆为例,研究基于不同用户数据分类的数字资源评价方法及实例,以期改变目前数字资源评价中重理论轻实践的现状,为高校图书馆的数字资源评估工作提供思路和借鉴。[方法/过程]根据图书馆数字资源用户数据的分类归纳不同数字资源的评价方法,结合电子科技大学图书馆资源评价工作实例,采用评价目的、评价方法及指标、用户数据提取整理、分析及结论的数据分析流程对横向对比法、纵向对比法、零点击率分析法、综合评价法、匹配法、收录分析法、引文分析法、学科馆员嵌入法等用户数据的数字资源评价方法进行系统研究。[结果/结论]用户数据维度的数字资源评价更具科学性和客观性。电子科技大学图书馆的数字资源评价以用户数据研究为切入点,针对不同的用户数据采用不同的评价方法,构建不同的评价指标体系,评价工作系统、高效,具备可操作性。其方法和经验能够为高校图书馆数字资源评价工作提供有益参考。

[ Purpose/significance ] Taking University of Electronic Science and Technology of China （UESTC） Library as an example, this paper carries out case studies of the digital resource evaluation in the user data dimension in order to change the current digital resource evaluation status which stresses theories and pay little attention to practice. It also provides the thought and reference for academic libraries. [ Method/process ] According to the user data classification, digital resource evaluation methods of user information behavior data, user teaching research activity data and user social activity data were summarized. The data analysis process such as the evaluation purpose, the evaluation method and index, user data extraction, collation, analysis and conclusion was carried out. With library resources evaluation examples, the digital resource evaluation methods of user data including the horizontal comparison method, the vertical comparison method, the zero click-through rate analysis method, the synthetic evaluation method, the match method, the register analysis method, the citation analysis method and the subject librarian embedding method were systematically studied in this paper. [ Result/conclusion] The digital resource evaluation in the user data dimension is more scientific and objective. The evaluation work in UESTC library takes user data research as the breakthrough point. They use different evaluation methods and construct different evaluation index systems for different user data, which makes the evaluation system efficient and operable. The methods and experience can provide useful reference for the digital resources evaluation in academic libraries.