This talk examines decentralized data markets with components based on smart contracts, token-curated registries, DApps, voting mechanisms, etc. — blockchain technologies — which allow multiple parties to curate ML training datasets in ways that are transparent, auditable, secure, and allow equitable payouts that take social values into account.