一个通用数据协调框架:支持可重复和可扩展的数据集成在RADx数据中心.
Jimmy K Yu1, Marcos Martínez-Romero1, Matthew Horridge1
1Center for Biomedical Informatics Research, Stanford University, Stanford, CA, USA.
AMIA ... Annual Symposium proceedings. AMIA Symposium
|February 23, 2026
概括
本研究引入了一个软件框架,以简化数据协调,使研究数据更易于查找,可访问,可互操作和可重复使用 (FAIR). 该工具简化了复杂的数据调整流程,以提高数据质量和可用性.
科学领域:
- 数据科学数据科学数据科学
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 在大数据时代,初级研究数据必须遵守FAIR原则 (可查找性,可访问性,互操作性,可重复使用性).
- 数据协调对于提高互操作性和可重复使用性至关重要,但由于所需的专业知识而具有挑战性.
研究的目的:
- 提出一个软件框架,以促进原则和可重复的数据协调协议.
- 让数据从业人员能够执行透明和目标一致的协调.
主要方法:
- 开发了一个软件框架,使用可参数化的原始运算来构建协调转换.
- 实现了对执行的转换的自动会计.
- 建立了一个新的数据表示模型和协调策略.
主要成果:
- 在RADx数据中心展示了一个概念验证应用程序.
- 该框架允许创建透明和可重复的协调协议.
结论:
- 该软件框架简化了复杂的数据协调,提高了数据的互操作性和可重复使用性.
- 促进对大数据研究的FAIR数据原则的遵守.
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