Our current workflow for model card submissions lacks a formal method for generating Persistent Identifiers (PIDs) for AI/ML models.
Proposed Approaches:
-
Hash-Based Generation:
- Method: Compute a cryptographic hash (e.g., SHA-256) of key metadata fields (such as model name, version, author).
- Pros:
- Simple to implement.
- No external dependencies.
- Fast and deterministic.
- Cons:
- May lead to collisions if metadata isn’t sufficiently unique.
- If model metadata changes, the PID would change unless carefully managed.
-
Dedicated PID Service:
- Method: Integrate with a dedicated PID service or registry (e.g., Handle System, DOI) that assigns and manages unique identifiers.
- Pros:
- Provides a globally resolvable and persistent identifier.
- Often comes with additional metadata management and resolution features.
- Aligns well with FAIR principles by offering external resolvability.
- Cons:
- Increases system complexity and introduces external dependencies.
- May incur costs or require administrative overhead for integration.
Our current workflow for model card submissions lacks a formal method for generating Persistent Identifiers (PIDs) for AI/ML models.
Proposed Approaches:
Hash-Based Generation:
Dedicated PID Service: