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Title:	The Machine-Interpretable Standards Ecosystem: Standards, Profiles, Building Blocks, and Registers. An Architectural Framework for a Composable, Disco
DOI:	10.62973/26-021
Editors:	Ingo Simonis, Rob Atkinson, Francesca Noardo, Alejandro Villar, Mayte Toscano
Published Date:	2026-04-16
Keywords:	AI, The Machine, Standards, Profiles, Building Blocks, Registers
Description:	The paper is framed as a proposal about standards, but the commercial payoff lands one layer higher — on the data itself. Machine-interpretable standards are a means; machine-interpretable data offerings are the end. When a dataset is published against a registered profile, every value it carries arrives with its meaning declared in a form an AI agent can consume safely: units of measure point to a shared reference, coordinate systems are explicit, feature types resolve to catalog entries, date and time conventions are declared rather than assumed, and provenance is a traversable chain rather than a PDF footnote.