Decentralized identifiers (DIDs) for sustainable AI in the Dataverse data network

The open web lacks persistent, verifiable identity and ownership mechanisms for web pages. This proposal introduces Decentralized Identifiers (DIDs) as a foundational layer to enable verifiable ownership, provenance, and control for every page on the Internet, while also integrating with AI workflows. With infrastructure capable of adding a sovereign layer to original web pages, this approach can support FAIR principles and sustainability for AI primitives used in the Model Context Protocol (MCP) preserving the provenance of all prompts, resources, and tools, and linking them to metadata expressed in the Semantic Croissant for Machine Learning standard as Linked Data.