[国家和国际数据空间中的FAIR健康数据]
Dagmar Waltemath1, Oya Beyan2, Katrin Crameri3
1Abteilung Medizininformatik, Institut für Community Medicine, Walther-Rathenau-Straße 48, 17475, Greifswald, Deutschland. dagmar.waltemath@med.uni-greifswald.de.
确保健康数据质量对于可靠的重复使用至关重要. 公平原则 (可查找,可访问,可互操作,可重复使用) 指导数据管理,提供支持公平的工具和框架,以改善临床决策和研究.
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
- 生物医学研究生物医学研究
背景情况:
- 健康数据自动化优化流程并支持临床决策.
- 数据质量,有效性和可靠性对于合理的数据重复使用至关重要.
- FAIR (可查找,可访问,可互操作,可重复使用) 的指导原则是数据管理的关键.
研究的目的:
- 突出FAIR原则在德国医疗保健中的重要性.
- 描述 FAIR 评估和 FAIRification 的过程.
- 展示欧洲关于语义互操作性和数据丰富的倡议.
主要方法:
- 德国国家研究协会和基础设施项目的审查.
- 自2016年以来对FAIR评估和FAIR化工具和指导方针的审查.
- 分析欧洲倡议,如欧洲健康数据空间和EOSC.
主要成果:
- 德国的医疗保健基础设施 (IMI,UMC,nFDZ-PH,DZD) 明确采用了FAIR原则.
- 现有工具和指导方针用于FAIR评估和FAIR化.
- 欧洲国家正在制定语义互操作性和数据丰富的国家框架.
结论:
- 遵守FAIR原则对于可靠和可重复使用的健康数据至关重要.
- 公平评估和公平化是改善数据管理的必要步骤.
- 在EOSC等倡议的支持下,国际合作推动了医疗保健中的FAIR数据实践.
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