图书情报工作

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2025 , Vol. 69 >Issue 1: 68 - 79

DOI: https://doi.org/10.13266/j.issn.0252-3116.2025.01.007

研究论文

多向度的数据分类分级：目标、逻辑与路径

  • 许炜 ,
  • 李卓卓 ,
  • 方向阳
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  • 1 江苏科技大学商学院, 张家港 215600;
    2 苏州大学社会学院, 苏州 215123;
    3 苏州大学智能社会与数据治理研究院, 苏州 215123;
    4 苏州市职业大学教育人文学院, 苏州 215104
许炜，讲师，博士；李卓卓，副教授，博士，硕士生导师，通信作者，E-mail：smileforever96@126.com；方向阳，教授，硕士。

收稿日期: 2024-04-07

  修回日期: 2024-08-04

  网络出版日期: 2025-01-15

基金资助

本文系江苏省社会科学基金项目“移动应用的隐私政策合规框架与透明度测评研究”（项目编号：23TQB005）研究成果之一。

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Multidirectional Data Classification and Grading: Goals, Logic and Path

  • Xu Wei ,
  • Li Zhuozhuo ,
  • Fang Xiangyang
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  • 1 Business School, Jiangsu University of Science and Technology, Zhangjiagang 215600;
    2 School of Social Science, Soochow University, Suzhou 215123;
    3 Smart Society and Data Governance Institute, Soochow University, Suzhou 215123;
    4 School of Humanities and Education, Suzhou Vocational University, Suzhou 215104

Received date: 2024-04-07

  Revised date: 2024-08-04

  Online published: 2025-01-15

Supported by

This work is supported by the Social Science Fund of Jiangsu Province project titled “Research on Privacy Policy Compliance Framework and Transparency Measurement of Mobile Applications” (Grant No. 23TQB005).

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摘要

[目的/意义] 数据分类分级是数据治理和数据价值化的现实需要，在《数据安全法》等国家和地方多部法律法规中均提出要实施数据分类分级管理。然而，实践中不同行业和地方标准在数据分类分级的类目上存在交叉、重叠和模糊现象。由于数据本身属性及特定情境中的数据治理需求不同，对数据分类分级的要求也有所差异。[方法/过程] 研究从现行法规及标准与实践操作的差异出发，明确数据分类分级的目的和依据，构建数据分类分级的底层逻辑框架，并对现有的不同数据分类分级维度进行梳理和比较。[结果/结论] 通过归纳分类分级各维度及选择，研究提出数据元数据标准先行，构建数据分类分级的类目网络，以及先通用再专用兼容的思路，为实施数据分类分级提供可操作方案。

关键词： 数据分类分级; 数据安全; 数据分类; 数据分级; 数据治理

本文引用格式

许炜 , 李卓卓 , 方向阳 . 多向度的数据分类分级：目标、逻辑与路径[J]. 图书情报工作, 2025 , 69(1) : 68 -79 . DOI: 10.13266/j.issn.0252-3116.2025.01.007

Abstract

[Purpose/Significance] Data classification and grading is a practical necessity for data governance and data valorization, their management has been proposed in various national and local laws and regulations, including the Data Security Law. However, in practice, there are overlaps, intersections, and ambiguities in the categories of data classification and grading in different industries and local standards. Different data attributes and data governance needs in specific contexts lead to different requirements for data classification and grading. [Method/Process] Starting from the differences between current regulations and standards and practical operations, the study clarified the purpose and basis of data classification and grading, constructed the underlying logical framework, and analyzed and compared the existing dimensions for data classification and grading. [Result/Conclusion] By summarizing the dimensions and selection for classification and grading, the study proposes to prioritize data metadata standards, construct the class network of data classification and grading, and adopt a general-to-specific approach. It provides an operable scheme for the implementation of data classification and grading.

Key words： data classification and grading; data security; data classification; data grading; data governance

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