Integrating Ontology Design with the CRISP-DM in the context of Cyber-Physical Systems Maintenance

• URL: http://arxiv.org/abs/2407.06930v1
• Date: Tue, 9 Jul 2024 15:06:47 GMT
• Title: Integrating Ontology Design with the CRISP-DM in the context of Cyber-Physical Systems Maintenance
• Authors: Milapji Singh Gill, Tom Westermann, Gernot Steindl, Felix Gehlhoff, Alexander Fay,
• Abstract summary: The proposed method is divided into three phases. In phase one, ontology requirements are systematically specified, defining the relevant knowledge scope. In phase two, CPS life cycle data is contextualized using domain-specific ontological artifacts. This formalized domain knowledge is then utilized in the Cross-Industry Standard Process for Data Mining (CRISP-DM) to efficiently extract new insights from the data.
• Score: 41.85920785319125
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In the following contribution, a method is introduced that integrates domain expert-centric ontology design with the Cross-Industry Standard Process for Data Mining (CRISP-DM). This approach aims to efficiently build an application-specific ontology tailored to the corrective maintenance of Cyber-Physical Systems (CPS). The proposed method is divided into three phases. In phase one, ontology requirements are systematically specified, defining the relevant knowledge scope. Accordingly, CPS life cycle data is contextualized in phase two using domain-specific ontological artifacts. This formalized domain knowledge is then utilized in the CRISP-DM to efficiently extract new insights from the data. Finally, the newly developed data-driven model is employed to populate and expand the ontology. Thus, information extracted from this model is semantically annotated and aligned with the existing ontology in phase three. The applicability of this method has been evaluated in an anomaly detection case study for a modular process plant.

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