What is AURA?
AURA (AI Use Registry and Archive) is a registry for documenting AI involvement in digital creations. Each registered object receives an AIDOI (AI Digital Object Identifier): a unique, permanent identifier backed by a resolution infrastructure. It offers a consistent way to reference AI outputs and preserve their metadata across hosting changes, organizational transitions, and long-term archival.
From registration to a citable record.
- 1
Register an AI Digital Object
A researcher, lab, or organization submits core metadata about an AI model, dataset, workflow, or output.
- 2
Validate provenance details
AURA captures ownership, lineage, and context so each object can be traced back to its source and responsible party.
- 3
Issue a persistent identifier
The platform assigns an AIDOI identifier that can be referenced in publications, systems, and audit trails.
- 4
Reuse with confidence
Others can discover the object, verify provenance, and cite or integrate it while preserving attribution and trust.
Provenance you can verify.
AI systems are increasingly built from layered components, reused datasets, and generated outputs that move across teams and platforms. Without standardized provenance, it becomes difficult to verify origin, accountability, and proper attribution. AURA addresses this by making provenance explicit and referenceable across the AI lifecycle, ensuring durable traceability, transparency, and auditability.
Built for AI, not adapted to it.
AI-aware identifier
Unlike traditional identifiers, the AIDOI is purpose-built for AI-generated objects. The identifier and its record carry AI-specific context rather than treating an AI output like any other static file.
Mandatory provenance metadata
Each record requires core provenance fields such as the AI–human contribution ratio, dataset sources, and model provenance, so every object carries the context needed to understand how it was produced.
Persistent across change
The identifier remains stable and resolvable across hosting changes, organizational transitions, and long-term archival, preserving the link between an object and its metadata over time.
Built for scholarly workflows
AURA simplifies referencing and integrating AI-generated outputs into publications, repositories, and audit trails, ensuring durable traceability, transparency, and auditability.
How different teams use AURA.
Researchers
A research team publishes a foundation model and uses AURA to make its training lineage, versions, and citations clear for peers and reviewers.
Institutions
A university tracks AI assets produced across departments, ensuring governance, responsible use, and transparent reporting.
Publishers
A journal verifies that AI-generated content and referenced models are traceable, making peer review and publication integrity stronger.
AI Developers
A product team integrates third-party models and datasets, using AURA records to confirm origin, permissions, and dependency chains.
Answers to what people ask most.
What exactly is an AIDOI?
An AIDOI is a unique, permanent identifier for an AI-generated object, backed by a resolution infrastructure that always points to the object's current location and metadata. It gives AI outputs a consistent, citable reference.
How is it different from a regular DOI?
A standard DOI identifies a static document or dataset. An AIDOI is AI-aware: the identifier carries mandatory metadata about AI–human contribution, dataset sources, and model provenance, capturing how the AI output was created and not just where it lives.
What happens if the object moves or the host changes?
The AIDOI stays the same. The resolution layer updates to track the new location, so references in publications and systems keep working through hosting changes, organizational transitions, and long-term archival.
Why does AI provenance matter?
AI systems are built from layered models, reused datasets, and generated outputs that move across teams and platforms. Capturing provenance makes origin, accountability, and attribution verifiable, supporting transparency and auditability across the AI lifecycle.
Who can register an AIDOI?
Researchers, labs, institutions, publishers, and AI developers can register AI models, datasets, workflows, or outputs and receive a persistent identifier they can cite, share, and integrate with confidence.
Give Your Creation an Identity.
Make AI Use Transparent.
Start documenting AI involvement and help make digital creation more understandable and accountable.