Internal structure -- field names, types, documentation -- makes a dataset usable by a person who downloads it. Discoverability is a separate problem: making sure search engines and AI systems can find and understand the dataset's page in the first place.

Schema.org's Dataset type is built exactly for this. Marking up a dataset page with structured data -- name, description, license, date modified, and a link to the actual file -- tells search engines this page represents a dataset, not a blog post, and can surface it in dataset-specific search results.

For products, Product schema does the equivalent job for templates and premium datasets: price, availability, and a description search engines can show directly in results.

Beyond schema.org, machine-readable endpoints help further: an llm.txt file describing what the site offers, and a single dataset-catalog.json endpoint listing every product in one place. Together, internal structure and external discoverability are what separate a dataset that sits unused from one that gets found.