综合数据术语的审查,以保护隐私的使用案例
Lora Frayling1, Shah Suraj Bharat2, Elizabeth Pattinson2
1Health Data Insight CIC, CPC4, Capital Park, Fulbourn, Cambridge, CB21 5XE, United Kingdom.
International journal of population data science
|November 19, 2025
概括
标准化术语对于研究中安全生成和使用合成数据至关重要. 本文提出了关键术语的定义,如合成数据,实用性,实用性测量和忠实性,以提高一致性和共享.
科学领域:
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
- 保护隐私的技术 保护隐私的技术
背景情况:
- 合成数据生成对于使用安全的行政和健康数据的研究至关重要.
- 缺乏标准化的术语阻碍了合成数据的质量标准,治理和知识共享.
- 这对于从受保护的个人信息中获得的合成数据尤其重要.
研究的目的:
- 审查有关合成数据术语的现有文献.
- 探索当前的定义并识别不一致性,特别是在保护隐私的用例中.
- 为关键合成数据术语提出标准化定义.
主要方法:
- 关于合成数据生成和术语的文献综述.
- 在保护隐私的应用中分析术语定义.
- 开发关于核心术语的拟议广泛定义.
主要成果:
- 对于合成数据属性的现有术语往往不一致和缺乏.
- 合成数据类型和用例的多样性使通用定义变得复杂.
- 由于受保护的源数据特征,保护隐私的合成数据带来了独特的定义挑战.
结论:
- 对术语的共识对于推动合成数据研究和应用至关重要.
- 未来文献中的更清晰的描述应该具体说明数据的预期使用和评估措施.
- 拟议的合成数据,实用性,实用性测量和忠实性的定义旨在促进一致性.
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