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Traditional approaches that retrofit FAIR principles onto existing repositories fail at scale and perpetuate the research integrity and reproducibility crises. This project addresses this systemic failure by implementing nanopublication-based FAIR Digital Objects (FDOs) as minimal, but precise metadata tags at the source, combining automated and human curated machine-actionable assertions that establish unambiguous provenance chains before data enters any workflow. 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