生物多样性的FAIR数字双胞胎:使数据,模型和工作流集成成为可能
Sharif Islam1, Hanna Koivula2, Carrie Andrew3
1Naturalis Biodiversity Center, Leiden, Netherlands. sharif.islam@naturalis.nl.
npj biodiversity
|February 2, 2026
概括
公平数字双胞胎集成复杂的生物多样性数据和模型. 这种方法通过使数据可查找,可访问,可互操作和可重复使用来增强研究和决策.
科学领域:
- 环境科学 环境科学
- 计算生物学 计算生物学
- 数据科学数据科学数据科学
背景情况:
- 生物多样性危机需要先进的计算工具来进行数据集成和分析.
- 现有的生物多样性数据和模型往往复杂且不一致,阻碍了研究进展.
研究的目的:
- 为生物多样性研究引入FAIR数字双胞胎 (FDTs) 的概念.
- 展示如何将数字双胞胎与FAIR原则相结合,可以改变生物多样性研究和决策.
- 在FAIR框架内提出整合异质数据,模型和工作流程的策略.
主要方法:
- 利用生物多样性数字双胞胎 (BioDT) 项目 (2022-2025) 开发原型数字双胞胎.
- 实施FAIR原则 (可查找,可访问,可互操作,可重复使用) 用于数据和模型集成.
- 使用像Research Object Crate (RO-Crate) 这样的工具进行元数据包装和标准化.
主要成果:
- 开发十个数字双胞胎原型,解决各种生物多样性挑战 (例如,草原动态,鸟类监测,生态系统服务).
- 展示整合异质数据,模型和计算工作流程的策略.
- 确定实施挑战,包括数据碎片化和语义互操作性.
结论:
- 公平数字双胞胎提供了一个可扩展和可重复使用的生物多样性建模和仿真方法.
- 这种趋同通过强大的数据整合和分析来推动基于证据的政策决策.
- 生物多样性研究中存在动态适应,模块化工作流程和跨领域合作的机会.
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