Ontologies in Digital Twins: A Systematic Literature Review

TL;DR

This paper systematically reviews 82 research articles to analyze how ontologies and semantic web technologies are utilized in Digital Twins across various domains, highlighting current trends, challenges, and future research directions.

Contribution

It provides a comprehensive analysis of the integration of ontologies in Digital Twins, filling a gap in understanding their application and impact across different industrial domains.

Findings

Ontologies enhance interoperability and reasoning in Digital Twins.

Manufacturing and Infrastructure are key application domains.

Open issues include standardization and knowledge sharing challenges.

Abstract

Digital Twins (DT) facilitate monitoring and reasoning processes in cyber-physical systems. They have progressively gained popularity over the past years because of intense research activity and industrial advancements. Cognitive Twins is a novel concept, recently coined to refer to the involvement of Semantic Web technology in DTs. Recent studies address the relevance of ontologies and knowledge graphs in the context of DTs, in terms of knowledge representation, interoperability and automatic reasoning. However, there is no comprehensive analysis of how semantic technologies, and specifically ontologies, are utilized within DTs. This Systematic Literature Review (SLR) is based on the analysis of 82 research articles, that either propose or benefit from ontologies with respect to DT. The paper uses different analysis perspectives, including a structural analysis based on a reference DT architecture, and an application-specific analysis to specifically address the different domains, such as Manufacturing and Infrastructure. The review also identifies open issues and possible research directions on the usage of ontologies and knowledge graphs in DTs.