Collection, Generation and Validation of Datasets suitable for training AI Models for 6G Networks and for AIaaS
Funds one project to build curated real-world and synthetic datasets, plus a shared data space, for training AI models that run 6G networks.
Where two proposals tie after coverage scoring, the JU's tie-break order for this 2026 call runs coverage, then impact, then excellence, before falling to SME participation and IKOP level -- the reverse of the impact-and-excellence order used in the SNS JU's 2025 calls, so a team assuming last year's sequence would misjudge where they stand. Award scoring itself folds the same SME and IKOP sub-cri…
This topic wants a curated collection of high-quality, real-world datasets capturing realistic 6G deployment conditions (user density, mobility, network traffic), an open-source simulator for generating synthetic equivalents, and a governed data space that manages the full data lifecycle for the SNS JU community. It also wants an audit framework to validate synthetic-data credibility and activities that drive adoption of the datasets, for example through CAMARA or Network APIs.
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