Data type guide

Prepare text and archives for AI licensing

Depth, authorship, and dependable provenance.

Sources and guidance · Reviewed October 2026

What makes this collection useful

A specialist archive may provide context missing from general web text. Useful metadata includes author, publication date, edition, topic and document boundaries.

Prepare before approaching buyers

Separate original material from syndicated, quoted or commissioned content. Reconcile rights by author and edition. Document OCR error rates and retain page references for quality review.

Possible evaluation contexts

Domain adaptation; retrieval; long-document evaluation. These are possible uses, not statements of current buyer demand.

Where preparation breaks down

Syndication limits, unattributed excerpts, inconsistent OCR and missing withdrawal procedures.

What to put in the datasheet

Document count; language; time span; token estimation method; rights coverage. State how each measure was calculated and which records were excluded. Keep the sample aligned with the collection described.

A practical next step

Create a one-page inventory, separate rights-cleared material from unresolved records and use the readiness checklist. Only then prepare a sample for a verified counterparty under appropriate evaluation terms.

Common questions

Does owning the files mean I can license them?

No. Ownership of the storage or account does not settle copyright, privacy, confidentiality or third-party restrictions. Review the rights in the content and the intended use separately.

Can I get a price without sending the full collection?

A high-level datasheet can support an initial discussion. A buyer may later request a reviewed sample and diligence; avoid sending raw archives at the first contact.

Use this as a preparation framework. It is not legal advice, a valuation or a promise that a buyer will accept your data.