Provenance review of a training data set: documents to prepare
A provenance review checks where each record in a training data set came from, under what licence, and whether that licence covers use inside your model. The review itself takes days once the right documents are on the table. Most delays come from documents that should have existed from day one and do not.
What changes once the review starts
Before the review, a data set is a working asset. Once a formal review is opened — by a client audit, a due diligence request, or an internal flag — every gap in the paper trail becomes a question someone has to answer in writing. A dataset with no licence record is not automatically unusable, but it moves from "probably fine" to "unresolved" the moment the review begins. That shift is the point of no return: after it, silence about a missing document reads as an admission, not as an oversight.
The practical effect lands on three fronts. Deployment plans slip while the gap is closed. Contract warranties tied to the data set become harder to give in good faith. And any buyer or licensor on the other side of a deal gains a reason to renegotiate price or scope.
What to prepare
Assemble the file before the review meeting, not during it. The order below reflects how reviewers actually work through a data set.
- List every source. The engineering team lists each dataset, scrape, vendor feed, or contributor upload that fed the training set, with dates.
- Pull the licence or terms for each source. Legal or IP counsel collects the licence text, terms of service, or written permission tied to each source on the list.
- Flag scraped or unlicensed material separately. Anything collected without a written licence goes into its own line — it is not merged with licensed material.
- Trace personal or third-party content. Data engineering marks any record that includes personal data, copyrighted text, images, or code contributed by someone outside the organisation.
- Reconcile against actual use. Someone compares what the licence permits against what the model actually does with the data — training, fine-tuning, or output generation.
- Prepare a one-page summary for the decision-maker. IP counsel drafts a short summary: sources, licence status, gaps, and recommended next step.
A staged log of this kind mirrors what appears in Post-issue reporting: stages and deadlines: each stage is closed off with its own document before the next one opens, so nothing gets reviewed out of order.
Documents that make up the file
| Document | Purpose | Who provides it |
|---|---|---|
| Source inventory | Complete list of datasets, feeds and contributions used in training | Data engineering |
| Licence or terms of use per source | Confirms what use is actually permitted | Vendor management / legal |
| Scrape or collection logs | Shows how and when unlicensed material entered the pipeline | Data engineering |
| Contributor agreements | Covers material submitted by employees, contractors or the public | HR or contracts team |
| Personal data mapping | Flags records containing identifiable individuals | Data protection lead |
| Use-versus-licence comparison | Matches actual model use against what each licence allows | IP counsel |
A file missing the source inventory cannot move forward — every other document depends on it.
Who decides and the timeline
Inside most organisations, IP counsel or the head of legal makes the call on whether a data set is clear to use, clear with conditions, or blocked pending further work. External counsel is brought in when a source involves a third-party rights holder who might object. A well-prepared file lets a decision-maker rule within a week; a file assembled during the review itself can stretch that to a month or more, mostly waiting on vendors to produce licence copies.
The same staged discipline shows up in Service credit calculation, where each deadline is tracked against a document, not against memory.
Typical forks
If the data set was purchased under a written licence — the review is largely a matching exercise: confirm the licence text covers training and, separately, covers the specific model output you generate from it.
If part of the data set was scraped internally without a licence — that portion is isolated, its risk assessed on its own, and a decision is made on whether to retrain without it, seek a retroactive licence, or accept the exposure with sign-off from the decision-maker above.
If a third party later claims rights over a contribution — the contributor agreement or its absence becomes the central document; without one, the claim is harder to dismiss and the file moves into a formal dispute track.
Sources and limits
This review establishes what documents exist and what they say. It does not establish who owns the resulting model or its outputs — that question sits closer to Asset report france, where ownership of a specific asset is the object of the check.
It also does not resolve a dispute with a data supplier once one has started; at that stage the file feeds into a broader assessment, closer to what is covered in Debtor report before selling the claim in detail.
Because national implementing rules for this area are not yet mapped into this file, the procedure above describes practice and sequencing only — no statute, regulation or court decision is cited on this page. Last checked: this page reflects current internal practice as of the review date recorded in the site's change log.
Related reading
A closely related file-building exercise is described in Open source compliance in a deliverable: documents to prepare, which covers the same discipline applied to code rather than data.
FAQ
How long does provenance review of a training data set take in practice?
With a complete source inventory and licence file ready in advance, a decision-maker can usually rule within a week. Missing documents push the timeline out by weeks while vendors and contributors are chased for paperwork.
Which documents are needed to start?
The review cannot begin without a source inventory. Everything else — licences, scrape logs, contributor agreements — is gathered against that list once it exists.
What happens if the other side does not respond?
A vendor or contributor who does not respond to a licence request does not stop the review. The gap is recorded as unresolved, the affected data is isolated, and the decision-maker rules on the remaining file with that gap flagged rather than waiting indefinitely.
Next step
Before you commit to a training run, it helps to know What it costs to be wrong in this situation.
If a dispute over the data set is already brewing, the next question is usually Who decides and when in this situation.
Licensing gaps in a training set often surface the same problems described in When royalties are underreported in practice.