Data governance

Observation, permission and provenance.

Sinuosity’s intended data-governance approach connects every research record to its source, permissions, transformations and permitted uses.

Public framework · Last reviewed July 2026

Consent and lawful collection

Field and human-provided data should be collected under a clear research or operational purpose with role-appropriate consent and permission.

Provenance

Records should preserve where, when and how an observation was collected, which system transformed it and which human or automated reviews occurred.

Source and collection context
Capture device and protocol
Permission state
Transformations and labels
Review history
Related actions and outcomes

Permission boundaries

Internal research use, partner research use and public release are distinct permissions. Access at one level does not imply permission at another.

Quality and correction

Quality control should include deduplication, uncertainty records, expert review where appropriate, correction pathways and versioned changes.

Public release

A public dataset should include a dataset card, version, intended use, limitations, consent and de-identification approach, access terms and citation. No public dataset is currently listed.

Retention and deletion

Retention and deletion should follow the approved purpose, participant or partner rights and applicable obligations. Detailed schedules will be documented per program before collection expands.

Questions and concerns

Potential privacy, provenance or permission concerns may be reported to hello@sinuosity.ai.