| 严炜炜,谢顺欣,潘静,陆伟.数据分类分级：研究趋势、政策标准与实践进展[J].数字图书馆论坛,2022,(9):2~12 |
| 数据分类分级：研究趋势、政策标准与实践进展 |
| Data Classification: Research Progress, Policy Standards and Enterprise Practice |
| 投稿时间：2022-08-29 |
| DOI：10.3772/j.issn.1673-2286.2022.09.001 |
| 中文关键词: 数据分类分级；学术研究；政策条例；行业指南；企业实践 |
| 英文关键词: Data Classification; Academic Research; Policy Regulations; Industry Guide; Enterprise Practice |
| 基金项目: |
| 作者 | 单位 | | 严炜炜 | 武汉大学信息管理学院 | | 谢顺欣 | 武汉大学信息管理学院 | | 潘静 | 武汉大学信息管理学院 | | 陆伟 | 武汉大学信息管理学院 |
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| 摘要点击次数: 2548 |
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| 中文摘要: |
| 随着数据要素成为国家战略性资源，数据分类分级主题研究呈现爆发式增长趋势，相关政策和标准也陆续出台，以推进数据安全保护工作。本文在对我国数据分类分级学术研究动态进行定量揭示的基础上，提炼相关公开政策标准拟定趋势，结合企业实践规律，综合探究我国数据分类分级工作进展。研究发现，科学研究层面，相关研究聚焦于数据安全管理、数据治理、数据挖掘与应用等主题；政策标准层面，中央政策的提出经历了由点到面的过程，地方标准多以政务数据和公共数据的分类分级为重点，在突出地域特色的同时不断更新内容，行业指南也已具备一定基础；企业实践层面，已形成以用户主体型、主题场景型和业务模块型为代表的数据分类分级实践模式。研究建议，发挥图情学科优势推进数据分类分级理论和标准规范的跨学科研究合作，提高地方标准的覆盖面和内容质量，并推进行业指南完善和企业数据顶层规范建立。 |
| 英文摘要: |
| As data elements have become national strategic resources, research on data classification has shown an explosive growth trend, and relevant policies and standards have been introduced to build a data security protection system. This paper quantitatively reveals the academic research trends of data classification in China by using information measurement and social network analysis, refines the development trend of open data classification policy standards by using the method of policy text analysis, and comprehensively explores the progress trend of data classification in China in combination with the refining law of enterprise practice. The research found that at the level of scientific research, relevant research focused on topics such as data security management, data governance, data mining and application. As for policy standards, the proposal of the central policy has experienced a process from point to area. Local standards mostly focus on the classification of government data and public data, focus on the security protection of the whole life cycle of data, and constantly update the content while highlighting regional characteristics. For industrial standards, data classification and grading industry guidelines and standard formulation have also formed a basic framework. For enterprise practice, data classification and grading practice modes represented by user main body type, theme scene type and business module type has been formed. The research suggests that give full play to the advantages of library and information science, promote the interdisciplinary research cooperation of data classification and classification theory and standard specifications, improve the coverage and content quality of local standards, and promote the improvement of industry guidelines and the establishment of enterprise data top-level specifications. |
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