VSS is known for vehicle-to-cloud and inter-ECU communication, but automotive researchers face a different standardization problem: data heterogeneity across platforms. A colleague's ML project analyzing autonomous driving algorithms required aligning 200+ features from multiple vehicles in different formats—manual feature mapping became a major bottleneck. When combining simulation data (BeamNG, CARLA) with real vehicle telemetry, researchers waste time on format conversion instead of analysis. VSS could solve this, but it hasn't been available in simulation tools. We've developed VSS-compliant telemetry exporters for BeamNG and SimHub (tested across multiple sim racing games). These tools demonstrate a new VSS application: dataset standardization for research workflows. By generating simulation data in VSS format, we eliminate preprocessing overhead when integrating with real vehicle datasets. This isn't just simulation-to-vehicle integration—it's showing VSS as a practical solution for the data wrangling problems researchers actually face. We will be extending this to CARLA and exploring other widely-used simulation platforms. The goal: establish VSS as the common data schema for automotive research, enabling seamless dataset portability between virtual and real testing environments. We welcome collaboration with COVESA members to identify priority platforms and develop guidelines for VSS in research contexts.