Converting property graphs to RDF: a preliminary study of the practical impact of different mappings

Shahrzad Khayatbashi, Sebastián Ferrada, O. Hartig
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引用次数: 3

Abstract

Today's space of graph database solutions is characterized by two main technology stacks that have evolved separate from one another: on one hand, there are systems that focus on supporting the RDF family of standards; on the other hand, there is the Property Graph category of systems. As a basis for bringing these stacks together and, in particular, to facilitate data exchange between the different types of systems, different direct mappings between the underlying graph data models have been introduced in the literature. While fundamental properties are well-documented for most of these mappings, the same cannot be said about the practical implications of choosing one mapping over another. Our research aims to contribute towards closing this gap. In this paper we report on a preliminary study for which we have selected two direct mappings from (Labeled) Property Graphs to RDF, where one of them uses features of the RDF-star extension to RDF. We compare these mappings in terms of the query performance achieved by two popular commercial RDF stores, GraphDB and Stardog, in which the converted data is imported. While we find that, for both of these systems, none of the mappings is a clear winner in terms of guaranteeing better query performance, we also identify types of queries that are problematic for the systems when using one mapping but not the other.
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将属性图转换为RDF:对不同映射的实际影响的初步研究
今天的图数据库解决方案空间的特点是两个主要的技术堆栈,它们已经相互分离:一方面,有一些系统专注于支持RDF标准家族;另一方面,有系统的属性图类别。作为将这些堆栈组合在一起的基础,特别是为了促进不同类型系统之间的数据交换,在文献中引入了底层图数据模型之间的不同直接映射。虽然大多数映射的基本属性都有很好的文档记录,但选择一个映射而不是另一个映射的实际含义却不是这样。我们的研究旨在为缩小这一差距做出贡献。在本文中,我们报告了一项初步研究,我们选择了两个从(标记的)属性图到RDF的直接映射,其中一个使用RDF-星形扩展到RDF的特征。我们根据两种流行的商业RDF存储GraphDB和Stardog实现的查询性能来比较这些映射,其中导入了转换后的数据。虽然我们发现,就保证更好的查询性能而言,对于这两个系统来说,没有一个映射是明显的赢家,但我们还确定了当使用一个映射而不是另一个映射时,系统会出现问题的查询类型。
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Knowledge graph representation learning and graph neural networks for language understanding Converting property graphs to RDF: a preliminary study of the practical impact of different mappings Multilayer graphs: a unified data model for graph databases Batch dynamic algorithm to find k-core hierarchies Anti-vertex for neighborhood constraints in subgraph queries
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