Representing Time-Continuous Behavior of Cyber-Physical Systems in Knowledge Graphs
This addresses the lack of reusable ontological artifacts for integrating behavioral information with CPS lifecycle data, though it appears incremental as it builds on existing knowledge graph standards.
The paper tackles the problem of representing time-continuous dynamic models (differential equations) of Cyber-Physical Systems in knowledge graphs by introducing a modular semantic model and an efficient generation method, with validation in aviation maintenance showing successful formal representation and contextualization of complex system equations.
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.