农业图书情报学报 ›› 2023, Vol. 35 ›› Issue (11): 23-39.doi: 10.13998/j.cnki.issn1002-1248.23-0483

• 研究论文 • 上一篇    下一篇

算法时代图书馆面向科学数据知识产权服务质量的影响因素与优化策略

徐悦1, 郗子捷2, 潘超3   

  1. 1.哈尔滨医科大学,哈尔滨 150076;
    2.哈尔滨国铁科技集团股份有限公司,哈尔滨 150001;
    3.哈尔滨医科大学附属第四医院,哈尔滨 150001
  • 收稿日期:2023-07-25 出版日期:2023-11-05 发布日期:2024-02-28
  • 作者简介:徐悦(1991- ),馆员,哈尔滨医科大学图书馆阅览部,研究方向为图书情报。郗子捷(1991- ),初级工程师,哈尔滨国铁科技集团股份有限公司,研究方向为北斗技术。潘超(1991- ),助理研究员,哈尔滨医科大学附属第四医院,研究方向为教学研究、课程思政
  • 基金资助:
    黑龙江省高校图工委项目“高校图书馆阅读推广服务嵌入学科课程思政”(2021-041-B)

Intellectual Property Protection of Scientific Data in the Algorithm Era: Factors Influencing Service Quality and Optimization Strategies

XU Yue1, XI Zijie2, PAN Chao3   

  1. 1. Harbin Medical University Library, Harbin 150076;
    2. Harbin National Railway Technology Group Co., Ltd., Harbin 150001;
    3. Fourth Affiliated Hospital of Harbin Medical University, Harbin 150001
  • Received:2023-07-25 Online:2023-11-05 Published:2024-02-28

摘要: [目的/意义]进入到大数据推荐时代,图书馆的信息呈现渠道从线下实体转向线上数字化,在此过程中科学数据的使用频次呈现出指数级增长。本研究旨在分析科学数据的知识产权的服务保障影响数字图书馆发展的内在机理。[方法/过程]以问卷调查法为基础,对高知群体进行问卷调查。采用问卷调查法调研获得样本252份有效样本,并利用验证性因子进行分析检验,发现问卷各因子信度介于0.724~0.913之间,问卷通过验证性因子分析检验证明具备较好效度。[结果/结论]政策法规落实效率、人才队伍建设、数据管理技术、服务模式多样化、数据产权共享协议数量5类因素均会显著正向影响科学数据知识产权服务,基于此为图书馆在科学数据知识产权服务领域提出5项优化策略。

关键词: 算法时代, 科学数据, 知识产权, 人才队伍建设, 服务质量

Abstract: [Purpose/Significance] With the advent of the algorithmic era, libraries' information delivery channels have shifted from offline physical entities to online digital platforms. This transformation has brought about significant changes in the way users access and utilize scientific data. The frequency of use of scientific data has increased exponentially, as more and more users rely on data to support their research, education, and innovation activities. The huge demand and application of use of data poses challenges to the development of libraries, among which the service guarantee of intellectual property rights (IPR) for scientific data is becoming a key factor affecting the development of digital libraries. IPR is a legal concept that protects the ownership and control of data creators and providers over their data. It also regulates the rights and obligations of data users and re-users. Therefore, this study aims to explore the influencing factors and optimization strategies of libraries' IPR service quality for scientific data. [Method/Process] To achieve this goal, this study used a questionnaire analysis method to collect data from a sample of 252 individuals belonging to a highly knowledgeable group, such as researchers, academics, and students. These individuals are the main users and producers of scientific data, and their perceptions and expectations of the quality of IPR services by libraries are crucial for improving the service. The questionnaire consists of four parts: demographic information, IPR awareness, IPR satisfaction, and IPR improvement suggestions. The reliability of the questionnaire factors is between 0.724 and 0.913, indicating a high level of internal consistency. The validity of the questionnaire is verified by confirmatory factor analysis, which shows a good fit between the data and the model. Based on the data, this study conducts a path analysis to test the hypotheses and obtain the results. [Results/Conclusions] The results show that the following factors have a significant positive impact on the quality of libraries' IPR services for scientific data: the implementation efficiency of policies and regulations (beta=0.326, p<0.001), talent team building (beta=0.274, p<0.001), the data management technology (beta=0.211, p<0.001), the diversification of service models (beta=0.358, p<0.001), and the number of data IPR sharing agreements (beta=0.329, p<0.001). These factors reflect the importance of improving the legal, human, technical, and organizational aspects of libraries' scientific data IPR services. Based on the findings, this study proposes five optimization strategies for libraries in scientific data IPR service: strengthening the implementation of policies and regulations, improving the training and motivation of talent teams, upgrading the data management technology, innovating the service model, and increasing the number of data IPR sharing agreements. These strategies can help libraries to improve the quality of their scientific data IPR services and meet the needs of the users in the algorithmic era.

Key words: algorithmic era, scientific data, intellectual property rights, talent team construction, service quality

中图分类号: 

  • G251

引用本文

徐悦, 郗子捷, 潘超. 算法时代图书馆面向科学数据知识产权服务质量的影响因素与优化策略[J]. 农业图书情报学报, 2023, 35(11): 23-39.

XU Yue, XI Zijie, PAN Chao. Intellectual Property Protection of Scientific Data in the Algorithm Era: Factors Influencing Service Quality and Optimization Strategies[J]. Journal of Library and Information Science in Agriculture, 2023, 35(11): 23-39.