一个全球综合的分类学结构,以支持生物多样性科学和保护
Emily L Sandall1, Aurore A Maureaud2, Robert Guralnick3
1Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT 06520, USA; Center for Biodiversity & Global Change, Yale University, New Haven, CT 06520, USA.
Trends in ecology & evolution
|September 8, 2023
概括
生物多样性研究需要更好的分类学数据整合. 改善共同的分类学元素和社区协作可以加强数据共享,克服当前的研究局限性.
科学领域:
- 生物多样性科学和分类学.
- 数据集成和互操作性.
背景情况:
- 物种名称是所有生物多样性研究的基础,从分类学到保护.
- 跨学科对分类学数据的有效整合至关重要,但目前面临着挑战.
- 现有的应用程序,即使是对精心研究的群体,也缺乏标准化的分类信息.
研究的目的:
- 评估目前对分类学数据协调和组织的努力.
- 确定必要的分类学元素,以改善数据访问和集成.
- 倡导社区驱动的解决方案,以提高生物多样性数据的互操作性.
主要方法:
- 对当前分类学数据实践的互操作性评估.
- 在关键生物多样性应用中分析分类学信息的共同性.
- 识别关键数据元素,以加强整合.
主要成果:
- 在共同的分类学信息中存在重大差距,阻碍了数据集成.
- 关键应用程序缺乏无互操作性所需的基本数据元素.
- 目前的努力表明,即使对于广泛研究的种类,也缺乏标准化.
结论:
- 专注于基本的分类学元素可以改善数据访问和整合.
- 民主化分类学专业知识和语言对于生物多样性科学至关重要.
- 需要社区驱动的努力来克服数据整合障碍,提高研究能力.
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