GDS Data Architecture

• About

Data Sharing Principles

• Overview
• 1. Treat data as an asset
• 2. Federate first
• 3. Prepare for Once Only
• 4. Reuse sharing solutions
• 5. Support automation
• 6. Design for all data stakeholders
• 7. Use common standards for sharing
• 8. Share data transparently
• 9. Share data lawfully and ethically
• 10. Secure shared data proportionately

Capability Model

• Overview
• Channels
• Infrastructure
• Data Access
• Services
• Governance
• Security
• Trust

Trust

Trust

Description:
A standardised framework to align with public and stakeholder expectations, ensuring compliance and best practices.

Capabilities:

• Standardisation: Defines standards, rules, and frameworks.
• Controls: Specifies controls for data sharing.
• Explainability: Ability to describe data and decision processes, especially for AI/ML.
• Data Loss Prevention, Encryption, IAM, Authentication, Authorisation, Federation, Disaster Recovery & Business Continuity.

Outstanding Questions:

• How will consent and user-owned data be managed in this architecture?