PGO: Describing Property Graphs in RDF

Dominik Tomaszuk,Harsh Thakkar,Renzo Angles

doi:10.1109/access.2020.3002018

Dominik Tomaszuk, Harsh Thakkar + Show 1 more

Open Access

https://doi.org/10.1109/access.2020.3002018

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Abstract

RDF and Property Graphs are data models that are being used to represent Knowledge Graphs. The definition of methods to transform RDF data into Property graph data is fundamental to allow interoperability among the systems using these models. Although both models are based on a graph structure, they have special features that complicate the definition of data transformation methods. This article presents an ontology-based approach to transform (automatically) property graphs into RDF graphs. The ontology, called PGO, defines a set of terms that allows describing the elements of a property graph. The algorithm corresponding to the transformation method is described, and some properties of the method are discussed (complexity, data preservation, and monotonicity). The results of an experimental evaluation are also presented.

Highlights

A graph is a powerful abstract model that allows representing different types of interconnected data
THE PROPERTY GRAPH ONTOLOGY (PGO) we present our ontology for describing property graphs, called PGO
2) Despite the lack of semantic descriptions before transformation, the data can be extended with appropriate vocabularies and ontologies

Summary

Introduction

A graph is a powerful abstract model that allows representing different types of interconnected data. We concentrate our interest in two popular approaches for graph data management: Resource Description Framework (RDF) databases and Property Graph (PG) databases. RDF database systems ( called Triple Stores) [2] are systems designed to store and query linked data [3]. These systems are based on Semantic Web standards, in particular the Resource Description Framework (RDF) [4], [5] and the SPARQL query language [6]. RDF is a graph data model that allows to describe the attributes and relationships of web resources in the form of labeled, directed multigraphs

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