The field kit, published.
The instruments an operator carries, the settings they shoot to, and the worked examples a delivery is checked against. These are the working documents, not a brochure about them — a buyer assessing whether this standard is real should read the paperwork it is made of.

Instruments
What a contributor signs, and what is read to them before they do.
The grant itself. Names AI and machine-learning training — pre-train, fine-tune, validate, benchmark, evaluate, generative models included — and grants sublicensing through multiple tiers. Clause 6 states plainly that a model already trained cannot be untrained.
/kit/contributor-licence.mdAppearance & voice releaseOne page, one person, signed before recording starts. Written in plain language because a release nobody understood is not consent. Records the fee paid, and states the withdrawal right and its limit.
/kit/appearance-voice-release.mdVerbal consent scriptRead on camera at the head of every take, tying a face and an asset ID to a spoken agreement. It survives a lost or smudged signature, and it is the evidence that holds when paper does not.
/kit/verbal-consent-script.mdWorked examples
A real delivery's manifest, annotation and data card — the standard as an artefact rather than a claim.
Every column, its type, and what an empty cell means. The live CSV export builds its header from the same schema this page documents.
Worked annotation — TXA-LAG-EGO-0002A real asset's annotation, with the failure events in it rather than described in the abstract.
Records schemaThe structure a records delivery is transformed into. A specification Texa authors, not a corpus Texa holds.
Records transform logWhat was changed, dropped or de-identified on the way through, recorded per field.
Field procedure
What an operator carries and the settings every session is locked to.
Documents are listed as they exist in the field kit. Where a file is not yet published here, it is marked so rather than linked to nothing.
Open corpora
The published datasets that overlap this catalogue, named so the scarcity argument can be checked rather than taken on trust.
| Corpus | Holder | Scale | Licence |
|---|---|---|---|
| Egocentric-100K | Build AI · Hugging Face, 2026 | 100,405 hours · 2,010,759 clips | Apache 2.0 — commercial training permitted |
| EgoStandard | Lightwheel · Hugging Face, 2026 | 100,000 hours · 15,000+ tasks and scenes | Open |
| Ego4D | Meta AI, 2022 | 3,670 hours · 923 participants · 74 locations | Restricts commercial use |
| WAXAL | Google with Makerere, University of Ghana and Digital Umuganda — February 2026 | 11,000+ hours · ~2m recordings · 21 languages | Open |
Read the paperwork before you read the pitch.
If the instruments do not satisfy your counsel, the material behind them will not either.