Scholarlink

Modern automotive, maritime, railway, and airborne systems generate massive streams of operational data that challenge existing solutions for storage, security, and data management. Semantic integration techniques improve interoperability across heterogeneous sources, yet often fall short in deployment automation, scalability, and real-time operation. We present CANDI, a semantic data integration framework that enables dynamic decoding and ontological access to Controller Area Network (CAN) data. Leveraging virtual knowledge graphs, CANDI links low-level logging streams with structured semantic representations, supporting advanced diagnostics and informed decision making. The framework incorporates the DBC ontology, a CAN database extension of the W3C SSN/SOSA standards that formalizes the semantics of messages, signals, ECUs, decoding schemas, and data logging processes. Using real-world datasets, we demonstrate CANDI’s contributions to end-to-end deployment automation, runtime CAN bus decoding, and secure, semantically driven analytics on streaming telemetry. The DBC ontology is rigorously evaluated for logical consistency, domain coverage, and knowledge graph instantiation, underscoring its robustness and industrial relevance.

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CANDI - A Semantic Framework for CAN Bus Data Modeling and System Integration

  • 会议论文

  • 发表日期：

    2026年

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  • Pavle Ivanovic,
  • Simon Burbach,
  • Oliver Niggemann,
  • Maria Maleshkova

摘要

Modern automotive, maritime, railway, and airborne systems generate massive streams of operational data that challenge existing solutions for storage, security, and data management. Semantic integration techniques improve interoperability across heterogeneous sources, yet often fall short in deployment automation, scalability, and real-time operation. We present CANDI, a semantic data integration framework that enables dynamic decoding and ontological access to Controller Area Network (CAN) data. Leveraging virtual knowledge graphs, CANDI links low-level logging streams with structured semantic representations, supporting advanced diagnostics and informed decision making. The framework incorporates the DBC ontology, a CAN database extension of the W3C SSN/SOSA standards that formalizes the semantics of messages, signals, ECUs, decoding schemas, and data logging processes. Using real-world datasets, we demonstrate CANDI’s contributions to end-to-end deployment automation, runtime CAN bus decoding, and secure, semantically driven analytics on streaming telemetry. The DBC ontology is rigorously evaluated for logical consistency, domain coverage, and knowledge graph instantiation, underscoring its robustness and industrial relevance.