Connected-vehicle ecosystems increasingly span multiple data models and standards ,e.g. vehicle signals and services, fleet/telematics schemas, simulation and validation formats, and emerging regulatory interfaces. Each layer often introduces its own “local” vocabulary (optimized for a product, UI, or pipeline), and the translation cost between these vocabularies compounds over time. This session presents knowledge graphs as a pragmatic harmonization mechanism: a semantic spine that preserves local flexibility while enabling shared discovery, reuse, and cross-domain analytics. Starting from COVESA artifacts (e.g., VSS/VISS and CDSP data pipelines), we describe a pattern language for building an automotive knowledge graph that connects to complementary standards such as ASAM OpenX (OpenDRIVE/OpenSCENARIO/OpenLABEL/OpenODD), ISO/ITS concepts, and generic vocabularies (SSN/SOSA for sensing, QUDT for quantities/units, and SAREF extensions). The focus is incremental adoption: lightweight mappings, versioning and governance to prevent drift, and “just enough” semantics to enable validation and reusable queries across vehicles and environments. Attendees will leave with an actional playbook for reducing integration friction without forcing a one-size-fits-all ontology.