基于数据字典最小信息模型 (DDMIM) 规范的元数据搜索门户的设计和开发
Leslie Diana Wamba Makem1,2, Abishaa Vengadeswaran1, Dupleix Achille Takoulegha2
1Goethe University Frankfurt, University Medicine, Institute of Medical Informatics (IMI), Frankfurt am Main, Germany.
Studies in health technology and informatics
|September 3, 2025
概括
基于数据字典最小信息模型 (DDMIM) 的新元数据搜索门户可以提高健康数据的可查性和互操作性. 这有助于更好地整合和利用医学数据进行研究和临床应用.
科学领域:
- 卫生信息学
- 数据科学
- 医学研究
背景情况:
- 在医疗保健领域,元数据的异质性是一个重大挑战.
- 数据字典最小信息模型 (DDMIM) 旨在提高不同数据标准和字典之间的互操作性.
- 促进无的元数据交换对于有效的健康数据管理至关重要.
研究的目的:
- 介绍一个元数据搜索门户的设计和开发.
- 该门户基于DDMIM规范,以提高健康数据的可查性和可访问性.
- 一个主要目标是改善不同健康数据集的互操作性.
主要方法:
- 进行文献审查以确定相关的现有元数据存储库.
- 来自各种来源的元数据被映射到DDMIM格式中.
- 评估了整合多种公共元数据库的原型搜索门户的要求.
主要成果:
- 一个基于DDMIM的搜索门户有效地整合了异构的元数据来源.
- 该门户网站显著提高了寻找相关健康数据集的能力.
- 证明了将不同元数据整合到统一的,可搜索的格式的能力.
结论:
- 开发的门户支持不同类型的元数据的整合,符合FAIR原则.
- 为研究和临床应用优化健康数据的利用.
- 解决医疗数据整合和利用的关键问题,促进数据驱动的医疗保健进步.
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