Enforcement
Protocol or coordination standard. Defines shared messages, workflows, or interfaces for communicating and applying data-use conditions.
Practical force depends on implementation, interoperability, adoption, and any legal or technical controls built around it.
Catalog status describes public availability, not legal validity, adoption, or proven effectiveness.
What it is
Data Diligence is a developer-facing compliance tool for filtering or checking data before model training. It aims to make opt-out respect more practical by wrapping multiple signals behind a single interface for common ML workflows.
That makes it a good fit for this catalog as downstream compliance-support tooling: it is not the signal itself, but a library that training pipelines can use when deciding whether to include a work.
Spawning Data Diligence defines a shared protocol or technical standard for multimodal material across the collection, training, and fine-tuning stages. The protocol coordinates participating systems; practical coverage depends on implementation, interoperability, and adoption. Public materials describe a currently available initiative; the newest dated source in this profile is “PyPI package remains available at version 0.1.7” (July 16, 2026). These details describe the published mechanism and evidence, not a finding about legal validity, adoption, or effectiveness.
Limitations
The documented checks cover the Spawning API, DeviantArt X-Robots-Tag headers, and C2PA/CAI metadata. The package neither blocks access nor guarantees complete opt-out coverage or legal compliance; some workflows also depend on services maintained by Spawning.
Evidence trail
- Jul 16, 2026 · Primary sourcePyPI package remains available at version 0.1.7
Adoption signals
No public adoption figure found.