农业大数据学报2024，Vol.6Issue(3)：307-324,18.DOI:10.19788/j.issn.2096-6369.000069
科学数据分类分级保护探索:框架与模式
Navigating the Distinctiveness of Research Data Protection:Framework and Mode
摘要
Abstract
In recent years,increasing data security regulations have posed significant compliance challenges for scientific data management.Data classification and grading for protection has become a focal point for academia,practitioners,and regulatory bodies.However,existing research mostly focuses on compliance interpretation and reactive measures,lacking a systematic theoretical analysis of scientific data protection.This gap limits the development of frameworks and models in the field.To address this,based on an extensive survey of current practices,this paper identifies six key security characteristics of scientific data:multi-regulation,strict ethical regulation,disciplinary differences,Pareto distribution of"scale-risk,"public interest,and dynamic sensitivity.It proposes a classification and grading framework,along with three protection models:comprehensive,balanced,and streamlined.Additionally,the paper introduces a"compliance-cost-benefit"triangle to explain the trade-offs among these factors.The proposed framework clarifies the complexity of classifying scientific data,distinguishing between data classification and grading,and offering insights into their interaction.This theoretical model provides valuable reference for future research and practical tools for addressing challenges in scientific data security management.关键词
科学数据/数据安全/数据保护/数据分类/数据分级/数据伦理Key words
scientific data/data security/data protection/data classification/data grading/data ethic引用本文复制引用
王健,周国民,张建华,许哲平,刘婷婷..科学数据分类分级保护探索:框架与模式[J].农业大数据学报,2024,6(3):307-324,18.基金项目
国家科技基础条件平台中心委托课题"数据流动政策对科学数据管理与应用影响研究" （）
中央级公益性科研院所基本科研业务费专项(JBYW-AII-2024-05、JBYW-AII-2023-06) （JBYW-AII-2024-05、JBYW-AII-2023-06）
中国农业科学院科技创新工程(CAAS-ASTIP-2024-AII、CAAS-ASTIP-2023-AII). （CAAS-ASTIP-2024-AII、CAAS-ASTIP-2023-AII）
