一个大集合的生物信息学问题-查询对在联合知识图:方法和应用程序
Jerven Bolleman1, Vincent Emonet1, Adrian Altenhoff1
1SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.
GigaScience
|May 16, 2025
概括
这项研究提供了1000多个自然语言问题和SPARQL查询的集合,用于生物信息学知识图 (KG). 目标是简化数据检索,并支持用于语义网络服务的机器学习应用程序.
科学领域:
- 生物信息学是一种生物信息学.
- 语义网络技术 语义网络技术
- 数据互操作性数据的互操作性.
背景情况:
- 生命科学资源越来越多地使用标准化框架和查询语言来实现互操作性.
- 知识图 (KG) 在生物信息学中因其数据表示能力而被采用.
- SPARQL能够实现强大的跨资源查询,但对用户来说具有挑战性,需要示例查询.
研究的目的:
- 为了解决制定生物信息学KGs的SPARQL查询的挑战.
- 为机器学习应用程序创建一个有价值的资源,例如自然语言到SPARQL的翻译.
- 为了促进数据检索和跨分布式生物信息学知识图的互操作性.
主要方法:
- 收集并策划了大量的人类编写的自然语言问题和相应的SPARQL查询数据集.
- 基于现有标准,开发了一种方法来统一表示示例,使用最小的元数据.
- 创建开源应用程序,包括查询图表可视化和智能查询编辑器.
主要成果:
- 介绍了为联合生物信息学KG的1000多个示例问题和SPARQL查询的集合.
- 收藏中包括近100个联合查询.
- 提供可重复使用的开源工具,以帮助KG维护者.
结论:
- 鼓励社区采用和扩展拟议的方法.
- 旨在促进更丰富的KG元数据和增强的语义Web服务.
- 为SPARQL示例和相关工具提供了一个GitHub存储库.
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