一个公平的词汇的特点
Fuqi Xu1, Nick Juty2, Carole Goble2
1European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Cambridge, Hinxton, CB10 1SD, UK.
Journal of biomedical semantics
|June 1, 2023
概括
定义和评估FAIR词汇对于数据科学至关重要. 本研究提出了功能和评估方法,以指导可查找,可访问,可互操作和可重复使用 (FAIR) 词汇的开发.
科学领域:
- 数据科学数据科学数据科学
- 信息科学 信息科学 信息科学
- 生物医学信息学 生物医学信息学
背景情况:
- 可查找,可访问,可互操作和可重复使用 (FAIR) 原则规定了FAIR词汇,但其定义仍然不清楚.
- 需要对FAIR词汇进行明确的定义和评估框架,以指导其发展并提高数据的可查性.
研究的目的:
- 定义 FAIR 词汇的特征.
- 开发对FAIR词汇的评估方法.
- 为了指导FAIR词汇的发展和演变.
主要方法:
- 在FAIR的背景下,差异化数据,数据资源和词汇.
- 检查了FAIR原则对词汇的应用.
- 调整FAIR词汇需求与开放生物医学本体学的原则.
- 拟议的 FAIR 词汇特征 (FVF).
- 通过将FVF与现有的FAIR评估指标进行映射来设计评估方法.
- 使用生物医学词汇表现出的评估和改进.
主要成果:
- 为FAIR词汇提议的具体特征.
- 为评估词汇的 FAIR 水平制定了指标.
- 将拟议的特征与现有的 FAIR 评估指标进行映射.
- 在评估和改进生物医学词汇表中展示了实际应用.
结论:
- 该研究为定义和评估FAIR词汇提供了一个框架.
- 确定了词汇工程师用于提高词汇质量的用例.
- 为词汇的演变提供指导,以满足FAIR数据原则.
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