中国科技期刊研究 ›› 2022, Vol. 33 ›› Issue (8): 1081-1087. doi: 10.11946/cjstp.202111290925

• 数字出版 • 上一篇    下一篇

学术期刊科学数据出版实践研究——以《图书馆杂志》数据出版管理平台为例

刘娴()()   

  1. 上海图书馆《图书馆杂志》编辑部,上海市静安区长乐路746号 200040
  • 收稿日期:2021-11-29 修回日期:2022-04-06 出版日期:2022-08-15 发布日期:2022-09-02
  • 作者简介:

    刘 娴(ORCID:0000-0003-3955-3334),硕士,副编审,E-mail:

Practice in scientific data publishing of academic journals: Taking Library Journal Data Publishing Management Platform as an example

LIU Xian()()   

  1. Editorial Office of Library Journal, Shanghai Library, 746 Changle Road, Jing'an District, Shanghai 200040, China
  • Received:2021-11-29 Revised:2022-04-06 Online:2022-08-15 Published:2022-09-02

摘要:

【目的】系统梳理《图书馆杂志》数据出版管理的实践和特色,为我国学术期刊的数据出版提供借鉴和参考。【方法】采用案例分析法和归纳法对《图书馆杂志》数据出版管理平台的技术方案、系统设计框架、服务功能、数据出版类型、数据论文结构框架、数据政策等进行全景扫描,归纳取得的成效。【结果】《图书馆杂志》数据出版管理平台的技术含量高、功能齐全、数据论文结构规范、数据政策较为完备,在国内期刊界有一定的影响力,具备与国际数据出版接轨的基础。【结论】《图书馆杂志》数据出版已取得一定的成效,但数据论文数量占比较低、数据评审机制有待规范、数据出版团队建设有待加强;要对标国内外数据出版期刊的经验,完善数据出版的各个环节,加强质量控制,在国际平台注册、认证与索引中扩大平台知名度,争取持续的资金支持以实现可持续发展;要在优化出版管理团队、规范数据评议方式与标准、培养科研人员的数据素养等方面持续发力。

关键词: 科学数据, 科学数据出版, 科学数据共享, 数据论文

Abstract:

[Purposes] This paper sorts out the practice and characteristics of the data publishing management of Library Journal, so as to provide a reference for the data publishing of academic journals in China. [Methods] The case analysis method and induction method were used to summarize the technical solutions, system frameworks, functions, data publication types, structure frameworks of data papers, and data policies of Library Journal Data Publishing Management Platform, and the outcomes were summed up. [Findings] With various functions, the high-tech Library Journal Data Publishing Management Platform provides standard data paper structure and sound data policies, showing extensive influence in the domestic journal industry and paving the way for developing data publishing platform of international level. [Conclusions] Despite the remarkable outcomes, Library Journal Data Publishing Management Platform, should strive to improve the proportion of data papers, data review mechanism, and data publishing team. Moreover, we should learn from the domestic and foreign data publishing journals to improve each process in data publishing and strengthen quality control, expand the visibility of the platform through registration, authentication, and indexing on international platforms, and seek for continuous financial support to achieve sustainable development. We should make efforts to optimize the publishing management team, standardize data review methods and standards, and cultivate the data literacy of scientific researchers.

Key words: Scientific data, Scientific data publishing, Scientific data sharing, Data paper