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The main objectives are:
Develop a federated infrastructure enabling the secure and sustainable sharing of data between industry, academia, authorities, and social partners.
Address existing gaps in data exchange by harmonizing taxonomies, interfaces, and formats through strong governance.
Meet diverse needs, including support for large-scale demonstrations, the creation and maintenance of digital twins, performance and safety assessment, and the collection of real or synthetic behavioral data for AI.
Facilitate the monitoring of automated driving systems (ADS), strengthen AI training, and centralize indicators related to vehicles, infrastructures, and accidents at both national and European levels.
Anticipate and integrate GDPR implications into AI learning workflows by proposing appropriate mitigation measures.
Align outcomes with existing European initiatives such as mobility dataspaces, PrepDSpace4Mobility, the EMDS study, the deployEMDS project, and the DIGITAL-2024-CLOUD-AI-06-MOBSPACE call.