Data governance and data quality

Requirements and practices for collecting, labelling, curating, documenting and protecting datasets used for training and validating AI models, including metadata, provenance, privacy‑preserving techniques and dataset quality metrics. The Roadmap frames these as foundational technical standards to ensure model robustness, reproducibility and regulatory compliance.