增加植物研究数据公平性的本体学
Kathryn Dumschott1, Hannah Dörpholz1, Marie-Angélique Laporte2
1Institute of Bio- and Geosciences (IBG-4: Bioinformatics) & Bioeconomy Science Center (BioSC), CEPLAS, Forschungszentrum Jülich, Jülich, Germany.
Frontiers in plant science
|December 15, 2023
概括
改进FAIR数据原则对于OMIC研究至关重要. 本次审查强调了植物科学本体学,以提高数据的可查性,可访问性,互操作性和可重复使用性.
科学领域:
- 植物生物学 植物生物学
- 生物信息学是一种生物信息学.
- 数据科学是数据科学.
背景情况:
- 奥米克技术产生了庞大而复杂的数据集,需要改进 FAIR 数据原则 (可查找性,可访问性,互操作性,可重复使用性).
- 整合多样化的数据集增加了新的研究问题和数据再利用的潜力.
- 实体学是用于语义数据标记的宝贵工具,增强元数据理解和互操作性.
研究的目的:
- 识别和审查与植物科学基础研究相关的本体学.
- 展示如何使用本体学来注释植物特定的实验数据,在诸如调查-研究-测试 (ISA) 等元数据框架内.
- 引导研究人员从相关存储库和平台中找到适用的本体和术语.
主要方法:
- 关于植物科学相关的本体学的文献综述.
- 在元数据框架 (如ISA) 中分析本体论的应用.
- 为本体学发现确定资源.
主要成果:
- 这里列出了植物科学相关本体学的精心策划的列表.
- 提供了使用本体学来注释植物数据的指导方针.
- 概述了用于本体学搜索的关键存储库和平台.
结论:
- 实体学对于提高植物科学数据的公平性至关重要.
- 与本体学的语义注释增强了数据的解释性和可重复使用性.
- 本综述为植物科学家提供了一份实用指南,以有效地利用本体学.
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