图书情报工作 ›› 2020, Vol. 64 ›› Issue (22): 11-24.DOI: 10.13266/j.issn.0252-3116.2020.22.002

• 专题:科学数据开放共享中的数据治理研究 • 上一篇    下一篇

科学数据开放共享中的数据质量治理研究

盛小平1, 田婧1, 向桂林2   

  1. 1 上海大学图书情报档案系 上海 200444;
    2 中国科学院生物物理研究所 北京 100101
  • 收稿日期:2020-06-09 修回日期:2020-07-21 出版日期:2020-11-20 发布日期:2020-11-20
  • 作者简介:盛小平(ORCID:0000-0002-6341-6973),教授,博士,博士生导师,E-mail:shengxp68@126.com;田婧(ORCID:0000-0002-3760-5308),硕士研究生;向桂林(ORCID:0000-0002-0880-8106),副研究馆员,博士。
  • 基金资助:
    本文系国家社会科学基金项目"开放科学环境下的科学数据开放共享机制与对策研究"(项目编号:18ATQ007)研究成果之一。

Research on Data Quality Governance in Open Sharing of Scientific Data

Sheng Xiaoping1, Tian Jing1, Xiang Guilin2   

  1. 1 School of Library, Information and Archives, Shanghai University, Shanghai 200444;
    2 Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101
  • Received:2020-06-09 Revised:2020-07-21 Online:2020-11-20 Published:2020-11-20

摘要: [目的/意义] 探究科学数据开放共享中的数据质量问题及其治理对策,以便促进科学数据开放共享的有效实施。[方法/过程] 运用规范分析法和因果分析法,分析当前科学数据开放共享中的数据质量问题和引发问题的根本原因,构建科学数据开放共享数据质量治理模型,并从诱因入手提出4类治理对策。[结果/结论] 科学数据开放共享中的数据质量问题涉及科学数据的准确性、完整性、一致性、及时性、可靠性、关联性、开放可访问性。可以从政策法规、组织管理、技术与平台、利益相关者4个方面制定科学数据质量治理对策,从而解决相关科学数据质量问题,进一步推动科学数据开放共享的实施。

关键词: 科学数据, 开放共享, 数据质量, 质量治理, 治理对策

Abstract: [Purpose/significance] In order to promote the effective implementation of open sharing of scientific data, this paper explores the data quality problems in open sharing of scientific data and its governance countermeasures.[Method/process] By means of normative analysis and causal analysis, this paper analyzed the data quality problems in open sharing of scientific data and the root causes of the problems, then constructd the governance model of open sharing of scientific data, finally proposed four types of governance countermeasures from the perspective of inducements.[Result/conclusion] The problems of data quality in open sharing of scientific data involve the accuracy, completeness, consistency, timeliness, reliability, relevance and open accessibility of scientific data. In order to solve the problems of scientific data quality and further promote the implementation of open sharing of scientific data, countermeasures for scientific data quality governance can be formulated from four aspects of policies and regulations, organizational managements, technologies and platforms, and stakeholders.

Key words: scientific data, open sharing, data quality, quality governance, governance countermeasure

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