Tutorials
The role of the tutorials is to provide a platform for a more intensive scientific exchange amongst researchers interested in a particular topic and as a meeting point for the community. Tutorials complement the depth-oriented technical sessions by providing participants with broad overviews of emerging fields. A tutorial can be scheduled for 1.5 or 3 hours.
Tutorial on
Semantic Foundations for Digital Twins: The Missing Knowledge Layer
Instructor
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Fatma Chamekh
BRGM
France
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Short Bio
Fatma Chamekh holds PHD in computer science at Lyon University. Her studies are focused on semantic web and symbolic IA for intelligent systems. He gets 10 years experience as professor assistant and research assistant in knowledge engeneering. Actually, she works on BRGM. Her areas of interest are: semantic web, knowledge reasoning, NLP, knowledge graph, LLM, digital Twin.
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Abstract
Digital Twins; Semantic Digital Twins; Semantic Interoperability; Ontologies; Knowledge Graphs; Knowledge Representation; Semantic Reasoning; Industry 4.0; Cognitive Digital Twins.
Keywords
Digital Twins; Semantic Digital Twins; Semantic Interoperability; Ontologies; Knowledge Graphs; Knowledge Representation; Semantic Reasoning; Industry 4.0; Cognitive Digital Twins.
Aims and Learning Objectives
The tutorial aims to provide participants with a concise and practical understanding of why semantic foundations matter for Digital Twins and how a semantic knowledge layer can be constructed and exploited.
At the end of the tutorial, participants will be able to:
Identify the semantic challenges arising from heterogeneous data, models, and information sources in Digital Twin environments.
Understand the role of ontologies and Knowledge Graphs in providing explicit and machine-interpretable representations of Digital Twin entities, relationships, and context.
Explain the added value of a semantic knowledge layer for semantic interoperability, knowledge integration, contextualisation, querying, and reasoning.
Apply the main steps of semantic modelling to a simplified Digital Twin case study, from heterogeneous data to an integrated Knowledge Graph.
Recognise how semantic foundations can support future knowledge-aware and cognitive Digital Twins, including perspectives involving neuro-symbolic AI
Target Audience
The tutorial is intended for researchers, PhD students, engineers, and practitioners working with Digital Twins, Industry 4.0, cyber-physical systems, industrial interoperability, data integration, Knowledge Engineering, Semantic Web technologies, Knowledge Graphs, and Artificial Intelligence.
It is particularly relevant to participants dealing with heterogeneous Digital Twin data and models who want to understand how explicit semantics can improve their integration and exploitation.
The tutorial is designed to create a bridge between participants coming from industrial Digital Twin and systems engineering communities and those coming from Knowledge Engineering and Semantic Web communities.
Prerequisite Knowledge of Audience
No advanced knowledge of Semantic Web technologies is required.
Basic familiarity with Digital Twins, data modelling, information systems, or Knowledge Graphs may be useful but is not mandatory. The necessary concepts related to ontologies, Knowledge Graphs, semantic interoperability, and reasoning will be introduced during the tutorial.
The practical example will focus on the underlying concepts rather than requiring prior expertise in RDF, OWL, or SPARQL.
Detailed Outline
The Missing Knowledge Layer: Why Do Digital Twins Need Semantics?
Building the Missing Layer: Semantic Foundations for Digital Twins
What Does the Knowledge Layer Enable?
Practical Case Study: From Heterogeneous Data to a Knowledge-Aware Digital Twin?
Beyond the Missing Layer: Perspectives