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Beyond asset-to-asset relationships, Dataerai stamps each asset with a cryptographic provenance token when it’s created, and lets machine-learning workflows record a lineage graph of how data flowed through training and inference.
Provenance and lineage flow: mint on create, public verify, lineage ingest and bounded query

Provenance is minted on create and publicly verifiable; lineage records how data moved through training and inference.

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Provenance tokens

When you create an asset or collection, Dataerai resolves the creator’s stable identity and mints an Ed25519-signed token that binds the asset to that creator at that moment. The token is exposed on the asset as provenance_token. Key properties:
  • Tamper-evident. The token is signed; any change to its contents invalidates the signature.
  • Stable creator anchor. The creator fingerprint is derived from an immutable person identifier, so it survives account changes without re-issuing tokens.
  • Publicly verifiable. Anyone can verify a token without logging in.
The token is returned as the provenance_token field on an asset (or collection) when you fetch it through the REST API or an SDK. It’s a behind-the-scenes integrity stamp rather than something you manage in the web app — for a citable, human-facing identifier you publish and share, use the asset’s DID instead.

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Verify a token

Two public endpoints let anyone confirm a token is authentic:
  • POST /api/provenance/verify/ — submit a token in the request body to decode it and check its signature.
  • GET /api/provenance/keys/ — fetch the published Ed25519 public keys used to verify.
These endpoints are intentionally unauthenticated so provenance can be checked by third parties — and they’re rate-limited. The verifier is fail-closed: a misconfigured key never silently downgrades verification.

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ML training & inference lineage

Training and inference workflows can record how data moved — which inputs produced which outputs — as a lineage graph of runs and edges.
  • Ingest. A run submits its edges (input → output relationships) in batches.
  • Query. A bounded traversal walks the graph up- or downstream from any node to answer “what produced this?” or “what was this used for?”.
The query traversal is bounded by design — depth-capped, node- and edge-budgeted, and deterministic — so tracing lineage on a large graph stays fast and predictable.
Lineage ingestion is for authenticated producers and is scoped to the run’s owner; the query API requires authentication.

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When to use which

The provenance token and the DID are two distinct signed artifacts on an asset: the token proves who created it, while the DID is a citable, resolvable name you can publish and verify. They complement each other.