Modern connected vehicle networks handle several thousand different data signals. Data signals such as wheel pulses, battery level, location and window positions.
Modern connected vehicle networks handle several thousand different data signals. Data signals such as wheel pulses, battery level, location and window positions. Vehicle and vehicle data signals, and their corresponding identification, has historically been proprietary and not exposed to 3rd parties, with new use cases stemming from smart cities, autonomous vehicles, electrical vehicles, and various other connected services, there is a need for a standardized way of describing vehicles and vehicle data. The W3C [1] and COVESA [2] have together been trying to resolve this by proposing a web standard for vehicle signal data VISS [3] [4], VSS [5]. The standard will facilitate data access and promote innovation in the vehicle data space. Mapping and matching signals to this standard is a tedious and time consuming task. We are suggesting ideas for a candidate ranking algorithm based on the lexical elements of signals names, their semantic description, type, and unit. We also use a knowledge graph - Neo4j [6] - to represent candidate matches.