Frontiers of Data and Computing ›› 2024, Vol. 6 ›› Issue (6): 10-18.

CSTR: 32002.14.jfdc.CN10-1649/TP.2024.06.002

doi: 10.11871/jfdc.issn.2096-742X.2024.06.002

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Data Classification: Practice Progress and Experience Enlightenment

WANG JIan1,2(),ZHAO Ruixue1,2,YANG Xiaorong1,TU Yuanyuan1,*()   

  1. 1. Agricultural information institute of CAAS, Beijing 100081, China
    2. Key Laboratory of Agricultural Integrated Publishing Knowledge Mining and Knowledge Services of the National Press and Publication Administration, Beijing 100081, China
  • Received:2024-05-16 Online:2024-12-20 Published:2024-12-20
  • Contact: TU Yuanyuan E-mail:wangjian02@caas.cn;tuyuanyuan@caas.cn

Abstract:

[Purpose/significance] Data classification and grading, as a prerequisite and key work for data security protection, is of great significance for the promotion of national data security strategy. [Method/process] Based on the systematic analysis of the relatively mature domestic and foreign practices in data classification and grading, this paper clarifies the key elements in the design of existing data classification and grading mechanisms, reviews data classification and grading standards and industry guidelines, identifies the experience and deficiencies in data classification and grading practices and judges their reference paths and inspirations for constructing data classification and grading mechanisms. [Result/conclusion] This work studies the possible paths for building a data classification and grading mechanism, and provides inspiration for promoting data resource management in our country from three aspects: classification and grading standards and methods, top-level design and management system construction, and protection assessment mechanism. It also looks forward to the development trend of data classification and grading and the impact of future technological progress in order to provide theoretical and practical references for promoting accurate, sustainable protection and high-quality development of data resources.

Key words: classification and grading, data openness, data security, practice progress, inspiration