在复杂的国际多站点研究中实现FAIR数据管理:用于加速药物伙伴关系®精神分裂症计划的数据操作.
Tashrif Billah1, Kang Ik K Cho1, Owen Borders2
1Department of Psychiatry, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Schizophrenia (Heidelberg, Germany)
|April 3, 2025
概括
本研究详细介绍了精神分裂症研究中的敏感健康数据的数据治理生态系统. 它强调了FAIR原则和实时质量控制,以加强数据共享和研究合作.
科学领域:
- 神经科学是一个神经科学.
- 精神病学是一个精神病学.
- 数据科学数据科学数据科学
背景情况:
- 公开资助的研究要求共享数据,这对敏感的健康信息构成了挑战.
- 在复杂的研究中,平衡参与者隐私与研究社区需求至关重要.
研究的目的:
- 描述加速药物伙伴关系®精神分裂症 (AMP® SCZ) 项目的数据操作生态系统.
- 将数据管理与FAIR原则保持一致,同时满足道德和监管要求.
主要方法:
- 实施强大的数据采集,字典和组织原则.
- 使用自动化管道进行数据流,安全和质量控制 (QA/QC).
- 利用NIMH数据档案进行数据传播.
主要成果:
- 设计了一个无的数据流,坚持公平原则.
- 接近实时的QA/QC能够立即纠正错误并提高数据质量.
- 该系统促进了在多站点研究中加强协作.
结论:
- 开发的数据操作生态系统有效地管理敏感的心理健康数据.
- 这种方法推进了涉及高风险个体的多站点研究的研究实践.
- 实时QA/QC对于保持数据完整性和研究效率至关重要.
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