DESCRIPTION
OVeC will provide a MVP for an implementation of an Open Platform for Vehicle-related Communication. Later, it will be an integral part of the already existing Carwatch framework.
The project will enrich official recall data with country-specific official vehicle communication to close numerous of the information gaps and give private and business users the opportunity to compare, correlate and analyse car specific data.
The focussed scenario are different end user views (consisting of dashboard and data-Mashups) which are visualising correlations of the EUH4D datasets in order to help the end users to answer vehicle-relevant questions, e.g., warranty and safety issues, reasons for accidents, etc. The innovative core will be an overarching semantic structure where the different open data sources will be integrated, normalised and re-structured.
OVeC will provide different end user views based on correlations of EUH4D datasets, which help the end users to answer vehicle-relevant questions.
The main innovation of OVeC is the underlying Search-Based Application (SBA) concept. The implemented SBA uses semantic technologies to aggregate, normalize, and classify unstructured, semi-structured, or structured content across multiple repositories. The Carwatch core uses machine learning techniques to enrich classical statistics/stochastics approaches to predict future situations with significantly less data as usual.
OVeC should help to assess data collected from the Internet on the use of vehicles in terms of their correctness and quality. This is intended to enrich the current official EU information with vehicle-relevant data, e.g., on safety-relevant incidents and quality defects in vehicles or on ecological issues.
KER 1: Grow of the available vehicle relevant data for Pumacy’s Carwatch platform
KER 2: Extension of the Pumacy methodology set by innovative approaches of the selected services of the DIHs
KER 3: Open dataset for vehicle relevant communications
KER 4: Minimal Viable Product
KER 5: Exploitation and dissemination
KPI 1: Integration of EUH4D datasets with relevant vehicle communications
KPI 2: Expansion of the Volume of vehicle relevant data
KPI 3: Dynamical Visualisations of EUH4D data.
