GDS Data Architecture
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
This site contains draft versions of the Future Data Architecture resources.
Future Data Architecture Capability Model
Overview of the Capability Model
The Future Data Architecture Capability Model sets out a vision for secure, trusted, and legal data sharing across the public sector. By setting out the capabilities needed to enable seamless data exchange, the model aims to support building these capabilities that will deliver faster services, better decision-making, and greater public trust. This framework supports the transformation of public sector data into a strategic asset, underpinned by robust infrastructure, governance, and ethical principles for data and AI.
Our approach is made up of seven building blocks. Each one focuses on a different part of how we manage and share data—like making it easy to find, keeping it secure, and making sure everyone knows the rules.
- Channels: How users and systems interact with data services.
- Services: Functionalities that meet user needs and support end-to-end data journeys.
- Data Access: Mechanisms for exchanging, managing, and using data.
- Infrastructure: The foundational technology and tools supporting data sharing.
- Governance: Oversight, transparency, and accountability across federated data domains.
- Security: Safeguards to ensure confidentiality, integrity, and availability.
- Trust: Frameworks and controls to build and maintain trust in data sharing.
Setting out the Capabilities
Each of the building blocks sets out the capabilities needed, and you can find more details about each layer.
