TL;DR
This paper introduces methods for constructing ontology-compliant knowledge graphs, including novel algorithms and metrics, with a case study in the building sector to demonstrate their effectiveness.
Contribution
It presents new term-matching algorithms, a pattern-based compliance approach, and metrics for building ontology-compliant knowledge graphs.
Findings
Ontology compliance improves KG interoperability and reusability.
Case study validates the effectiveness of proposed methods.
Recommends ontology-compliant KGs for heterogeneous data harmonisation.
Abstract
Ontologies can act as a schema for constructing knowledge graphs (KGs), offering explainability, interoperability, and reusability. We explore \emph{ontology-compliant} KGs, aiming to build both internal and external ontology compliance. We discuss key tasks in ontology compliance and introduce our novel term-matching algorithms. We also propose a \emph{pattern-based compliance} approach and novel compliance metrics. The building sector is a case study to test the validity of ontology-compliant KGs. We recommend using ontology-compliant KGs to pursue automatic matching, alignment, and harmonisation of heterogeneous KGs.
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