AIAug 29, 2023

Ontologies in Digital Twins: A Systematic Literature Review

arXiv:2308.15168v1123 citationsh-index: 44
Originality Synthesis-oriented
AI Analysis

It provides a foundational overview for researchers and practitioners in cyber-physical systems, but is incremental as it synthesizes existing work without new empirical results.

This systematic literature review analyzed 82 research articles to address the lack of comprehensive analysis of how ontologies and semantic technologies are utilized in Digital Twins, identifying open issues and research directions across domains like Manufacturing and Infrastructure.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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