Ontologies in Digital Twins: A Systematic Literature Review
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 6 of its 162 references that are in the map. First posted on arXiv 29 Aug 2023.
Builds on
6 of 162 references.
References · 6
- 2020Knowledge Graphscited by 621
- 2018SOSA: A Lightweight Ontology for Sensors, Observations, Samples, and Actuatorscited by 27
- 2021Actionable Cognitive Twins for Decision Making in Manufacturingcited by 5
- 2019Cognitive Twins for Supporting Decision-Makings of Internet of Things Systemscited by 4
- 2022Populating the Digital Space for Cultural Heritage with Heritage Digital Twinscited by 2
- 2023The Heritage Digital Twin: a bicycle made for two. The integration of digital methodologies into cultural heritage researchcited by 1
Built on by
Citing papers per year: 2023: 1; 2024: 2; 2025: 1; 2026: 3.
7 papers.
- 2023Semantic Association Rule Learning from Time Series Data and Knowledge Graphscited by 2
- 2024Learning Semantic Association Rules from Internet of Things Datacited by 2
- 2024AE SemRL: Learning Semantic Association Rules with Autoencoderscited by 0
- 2025Unraveling Media Perspectives: A Comprehensive Methodology Combining Large Language Models, Topic Modeling, Sentiment Analysis, and Ontology Learning to Analyse Media Biascited by 0
- 2026From USD Scenes to Knowledge Graphs: Zero-Shot Ontology Grounding with LLMscited by 0
- 2026Improving Interoperability among Defence and National Security Ontologies: Analysis and Evaluation Taskscited by 0
- 2026DTScribe: Generating Models for Digital Twin Reporting using Local Large Language Modelscited by 0
- 2026DTScribe: Generating Models for Digital Twin Reporting using Local Large Language Models13 Oct 2026
- 2026Improving Interoperability among Defence and National Security Ontologies: Analysis and Evaluation Tasks6 Aug 2026
- 2026From USD Scenes to Knowledge Graphs: Zero-Shot Ontology Grounding with LLMs8 Jun 2026
- 2025Unraveling Media Perspectives: A Comprehensive Methodology Combining Large Language Models, Topic Modeling, Sentiment Analysis, and Ontology Learning to Analyse Media Bias3 May 2025
- 2024Learning Semantic Association Rules from Internet of Things Data4 Dec 2024
- 2024AE SemRL: Learning Semantic Association Rules with Autoencoders26 Mar 2024
- 2023Semantic Association Rule Learning from Time Series Data and Knowledge Graphs11 Oct 2023
Similar, not cited
Close in wording, no citation either way
- 2025Semantic Grounding of Digital Twin Metamodels Using RDF Graphs ↗
- 2024Generation of Asset Administration Shell with Large Language Model Agents: Toward Semantic Interoperability in Digital Twins in the Context of Industry 4.0
- 2026Semantic Graph Unification for Industrial Digital Threads: Bridging 11 Heterogeneous Manufacturing Systems Through Ontology-Driven Knowledge Graphs
- 2025Ontology-Based Knowledge Graph Framework for Industrial Standard Documents via Hierarchical and Propositional Structuring
- 2026Agentic AI-enabled Semantic Commissioning of a Cognitive Digital Twin for Reconfigurable Manufacturing
- 2026AgenticTwin: An Agentic LLM Framework Integrated with Digital Twin for Anomaly Detection
- 2026Digital Twin AI: Opportunities and Challenges from Large Language Models to World Models
- 2026A Multi-Viewpoint Modeling Framework for Digital Twin Integration and Reuse with LLM-Assisted Compatibility Analysis ↗