Overview
Data Ownership
User control over their data lifecycle and retention
dataprivacyownership
Docs
Data Ownership gives users visibility into and control over the data that AI systems collect, store, and process on their behalf. It presents a clear inventory of data types, their retention periods, and the actions users can take — export, delete, or modify retention. This pattern is critical for building trust and meeting privacy regulations like GDPR, which require transparent data management and the right to erasure.
Variants
- Data inventory list — A table or list of data categories with retention info and action buttons for each, providing a comprehensive overview.
- Dashboard cards — Visual cards for each data category with storage metrics, retention timelines, and prominent action buttons.
- Settings panel — A privacy settings section where data management controls are grouped alongside other privacy preferences.
Use Cases
- AI assistants that store conversation history and user preferences
- Enterprise tools managing team-level AI interaction data
- Applications subject to GDPR or other data privacy regulations
- Multi-tenant platforms where data isolation must be transparent
- Tools that process sensitive documents and need clear data lifecycle management
Best Practices
- List all data types collected with clear descriptions of what each contains.
- Show retention periods and explain what happens when data expires.
- Provide both individual item deletion and bulk 'delete all' options.
- Include data export functionality so users can take their data elsewhere.
- Confirm destructive actions and explain their consequences before proceeding.