对于数据链接社区的RDF图形对配置文件数据集
Raphaël Conde Salazar1, Clément Jonquet1,2, Danai Symeonidou1
1MISTEA, University of Montpellier, INRAE & Institut Agro, France, 2, place Pierre Viala, 34060 Montpellier Cedex 2, France.
Data in brief
|November 4, 2024
概括
一个新的RDF图形对配置文件数据集通过提供工具开发和评估的特征来帮助数据链接. 本资源支持在语义网络上整合链接数据.
科学领域:
- 计算机科学 计算机科学
- 数据科学数据科学数据科学
- 语义网络技术 语义网络技术
背景情况:
- 越来越多的RDF数据集需要有效的方法来连接不同来源的类似实体.
- 数据链接对于整合和增强数据网络中的信息至关重要.
研究的目的:
- 引入"RDF图形对资料数据集",以支持数据链接社区.
- 通过全面的数据集配置文件,促进数据链接工具的开发,选择和验证.
- 为数据链接中的机器学习应用提供一个有价值的资源.
主要方法:
- 数据集包括30个RDF图对的配置文件,按本体学匹配 (OM),实例匹配 (IM) 或两者 (OM + IM) 分类.
- 每个配置文件包括统计指标,定性和定量信息,以及通过自动化工具生成的描述模型.
- 简要概述了配置文件生成的方法,并提供了原始的RDF图表及其配置文件.
主要成果:
- 该数据集提供了描述RDF图形的详细配置文件,有助于理解其属性.
- 个人资料作为机器学习模型的输入参数,增强它们在数据链接任务中的应用性.
- 该数据集是公开可用的,促进研究人员和从业人员使用它.
结论:
- "RDF图形对资料数据集"是一个全面的资源,将大大促进数据链接工作.
- 它的可用性支持RDF数据在语义网络上的集成和增强.
- 这项工作有助于提高数据链接工具和方法的能力.
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