论文标题
G2GML：图形到图形映射语言，用于桥接RDF和属性图
G2GML: Graph to Graph Mapping Language for Bridging RDF and Property Graphs
论文作者
论文摘要
我们如何最大化累积的RDF数据的价值？尽管可以使用SPARQL语言查询RDF数据，但即使基于SPARQL的操作也有限制在实现遍历或分析算法方面。最近，出现了各种用于分析（PG）模型分析的数据库实现。将RDF数据集导入这些图形分析引擎，通过各种应用程序接口可以访问对累计数据集的访问。但是，RDF模型和PG模型无法互操作。在这里，我们开发了一个基于图形映射语言（G2GML）的框架，用于将RDF图映射到PGS，以充分利用累积的RDF数据。使用此框架，可以将RDF模型中描述的累积图数据转换为PG模型，然后将其加载到图形数据库引擎以进行进一步分析。为了支持不同的图形数据库实现，我们重新定义了PG模型并提出了可交换的序列化格式。我们证明了几种用例，其中提取了公开可用的RDF数据并将其转换为PG。这项研究桥接了RDF和PGS，并有助于对知识图的互操作管理，从而扩大了RDF数据的用例。
How can we maximize the value of accumulated RDF data? Whereas the RDF data can be queried using the SPARQL language, even the SPARQL-based operation has a limitation in implementing traversal or analytical algorithms. Recently, a variety of database implementations dedicated to analyses on the property graph (PG) model have emerged. Importing RDF datasets into these graph analysis engines provides access to the accumulated datasets through various application interfaces. However, the RDF model and the PG model are not interoperable. Here, we developed a framework based on the Graph to Graph Mapping Language (G2GML) for mapping RDF graphs to PGs to make the most of accumulated RDF data. Using this framework, accumulated graph data described in the RDF model can be converted to the PG model, which can then be loaded to graph database engines for further analysis. For supporting different graph database implementations, we redefined the PG model and proposed its exchangeable serialization formats. We demonstrate several use cases, where publicly available RDF data are extracted and converted to PGs. This study bridges RDF and PGs and contributes to interoperable management of knowledge graphs, thereby expanding the use cases of accumulated RDF data.
