mlsanityData to 14 Oct 2026

Representing Time-Continuous Behavior of Cyber-Physical Systems in Knowledge Graphs

arXiv 2506.13773 ↗First posted 8 Jun 2025cs.AIcited by 4

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Abstract (arXiv)

Time-continuous dynamic models are essential for various Cyber-Physical System (CPS) applications. To ensure effective usability in different lifecycle phases, such behavioral information in the form of differential equations must be contextualized and integrated with further CPS information. While knowledge graphs provide a formal description and structuring mechanism for this task, there is a lack of reusable ontological artifacts and methods to reduce manual instantiation effort. Hence, this contribution introduces two artifacts: Firstly, a modular semantic model based on standards is introduced to represent differential equations directly within knowledge graphs and to enrich them semantically. Secondly, a method for efficient knowledge graph generation is presented. A validation of these artifacts was conducted in the domain of aviation maintenance. Results show that differential equations of a complex Electro-Hydraulic Servoactuator can be formally represented in a knowledge graph and be contextualized with other lifecycle data, proving the artifacts' practical applicability.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 5 of its 23 references that are in the map. First posted on arXiv 8 Jun 2025.

Builds on

5 of 23 references.

References · 5

  1. 2023Representing Timed Automata and Timing Anomalies of Cyber-Physical Production Systems in Knowledge Graphscited by 5
  2. 2024Integrating Ontology Design with the CRISP-DM in the context of Cyber-Physical Systems Maintenancecited by 4
  3. 2023Integration of Domain Expert-Centric Ontology Design into the CRISP-DM for Cyber-Physical Production Systemscited by 3
  4. 2020An Ontological Metamodel for Cyber-Physical System Safety, Security, and Resilience Coengineeringcited by 2
  5. 2025Physics-based simulation ontology: an ontology to support modelling and reuse of data for physics-based simulationcited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026From Detection to Action: Using LLM Agents for Fault-Tolerant Controlcited by 2
  2. 2026Automating Cause-Effect Specification with Knowledge Graphs and Large Language Modelscited by 0
  3. 2026A Tutorial on Autonomous Fault-Tolerant Control Using Knowledge-Grounded LLM Agentscited by 0
  4. 2026XPhysICS: Cross-Physical-Domain Threat Grounding for Industrial Control Systems Securitycited by 0