N3C治理生态系统:一个模范的社会技术伙伴关系,为未来的大规模协作分析的未来
Christine Suver1, Jeremy Harper2, Johanna Loomba3
1Research Governance & Ethics, Sage Bionetworks, Seattle, WA, USA.
Journal of clinical and translational science
|January 17, 2024
概括
国家COVID队列协作 (N3C) 为超过1700万个人创建了一个安全的数据集团,通过共享治理实现了快速的COVID-19研究. 该模型克服了数据共享障碍,促进了协作科学和数据安全.
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
- 合作研究合作研究.
背景情况:
- 冠状病毒大流行需要快速,大规模的研究.
- 现有的数据共享模式对协作研究构成了重大障碍.
- 需要一个集中,安全的数据资源来加速COVID-19研究.
研究的目的:
- 为COVID-19研究建立一个集中,安全的数据资源.
- 实施数据访问和利用的共享治理战略.
- 为团队科学展示保护隐私的数据基础设施的有效性.
主要方法:
- 建立了国家COVID队列协作 (N3C) 数据集群.
- 实施了涉及多方利益相关者的共享治理模式.
- 利用数据管理和团队科学原则的最佳实践.
主要成果:
- 启用基于云的分析,对超过1700万个人的电子健康记录进行分析.
- 促进了大规模的快速,协作性的COVID-19研究.
- 在不损害安全或信任的情况下,证明成功的数据共享.
结论:
- 共享治理可以克服研究中的传统数据共享障碍.
- N3C模型为保护隐私的数据基础设施提供了一个可持续的框架.
- N3C提供了一个有效的团队科学工作模型,超越了大流行.
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