一个通用策略,用于生成专家指导的,简化的观点的本体论
Anita R Caron1, Aleix Puig-Barbe1, Ellen M Quardokus2
1European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
bioRxiv : the preprint server for biology
|January 7, 2025
概括
研究人员现在可以使用新的验证工具来简化FAIR数据的复杂本体. 这些工具有助于创建定制的本体论视图,并改善地图库的数据组织.
科学领域:
- 生物信息学是一种生物信息学.
- 数据科学数据科学数据科学
- 基因组学和蛋白质组学
背景情况:
- 通过标准化术语和结构,本体学对于可查找,可访问,可互操作和可重复使用 (FAIR) 数据至关重要.
- 一般本体论的复杂性是研究人员和资源开发人员采用的障碍.
- 现有的针对特定应用程序的本体学的手动简化通常使用不合适的关系类型.
研究的目的:
- 介绍一套用于验证用户创建的层次结构与已建立的本体结构的工具.
- 为特定的地图库项目生成图形报告和定制的本体论视图.
- 为了解决复杂性障碍,并改善对FAIR数据原则的本体学采用.
主要方法:
- 开发软件工具,以验证用户层次结构与本体结构.
- 图形报告的生成,以促进讨论和识别差异.
- 为诸如HuBMAP人类参考地图和人类发育细胞地图等项目创建定制的本体论视图.
主要成果:
- 验证过程确定了对本体学和用户生成的层次结构的纠正和内容.
- 针对特定的亚特拉斯需求,成功生成了定制的本体论视图.
- 这些工具有助于在生物数据注释中更有效,更准确地使用本体学.
结论:
- 开发的工具有效地验证用户层次结构与本体结构,简化复杂的本体.
- 这种方法有助于创建更公平的数据集,通过改进生物图谱中的本体学应用.
- 验证是对两种本体学及其专业应用的代改进的机制.
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