Leveraging Ontologies for Knowledge Graph Schemas

Daniela Oliveira, Ratnesh Sahay, Mathieu d'Aquin

Keywords: Knowledge Graphs, Semantic Web, Ontologies

TL;DR: In this paper, we propose a method to build a schema for Knowledge Graphs that leverages ontologies by integrating them in a single unified graph, enriched by an ontology matching step.

Abstract:

Knowledge Graphs have emerged as a core technology to enhance the search experience of users in research and industry alike. Applications are being developed to build and exploit graph structures in data repositories, to improve search and integration of knowledge. However, data is available on the Web in diverse formats and integrating data from different sources is still an open research area. In this paper, we propose a method to build a schema for Knowledge Graphs that leverages ontologies by integrating them in a single unified graph, enriched by an ontology matching step. We evaluate this method by comparing the different stages of graph structures and measuring structural properties of the resulting graphs.
We also propose an approach that groups ontology classes by conceptual type, showcasing how an underlying ontology-based schema can enhance a Knowledge Graph. The results demonstrate the viability of this approach, highlighting how the chosen techniques based on edge addition successfully make our ontology-based knowledge graph schema more complete and tightly connected.

Contribution: Full research papers (8-12 pages)