Connected vehicles generate and consume data in various formats and modalities—ranging from onboard sensor inputs (e.g., camera, LiDAR, radar) to external feeds (V2X signals, traffic, and transit data)—which collectively power ADAS, predictive maintenance, and intelligent fleet services. However, disparate standards like COVESA Vehicle Signal Specification (VSS), ASAM OpenXOntology, OpenDRIVE, OpenSCENARIO, W3C Semantic Sensor Network Ontology, and General Transit Feed Specification (GTFS) —complicate data integration and fusion in (near) realtime, making it difficult to derive consistent meanings and insights across diverse vehicle platforms and stakeholder ecosystems. This talk introduces Semantic Streams as a unified semantic layer that harmonizes these heterogeneous models and standards to enable multimodal data stream integration and fusion. We will demonstrate how a low-code toolchain enabling such a semantic layer can reduce engineering overhead while fostering semantically interoperable exchange of vehicle, sensor, and contextual data. By showcasing how this toolchain supports lowering effort in building V2X applications within the SmartEdge and SMARTY projects, we will share our experience aligning COVESA VSS with other ontologies and standards. The presentation will conclude with our vision and plan to extend Semantic Streams to Software-Defined Vehicle (SDV) initiatives such as HAL4SDV.