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

4. Reuse sharing solutions

Directional principle

Statement

We use common data sharing capabilities, patterns and platforms where they exist and don’t develop our own solutions in isolation.

Why does this matter?

Data sharing initiatives aim to generate public value by making data assets accessible and reusable. We can multiply the benefits of data sharing exponentially by ensuring that the data sharing solutions we develop are also accessible and reusable.

To increase the potential for data reuse across government, we should centre our data sharing activities around common capabilities, patterns and platforms. Common data sharing capabilities support data federation (Principle 2) by levelling public sector understanding of data sharing requirements. With established capabilities, common data sharing patterns will allow us to mould our architecture and governance to support sharing in our unique data contexts. Finally, these patterns can be embedded into common data sharing platforms that lower the entry barriers to data sharing further.

How do we do this?

This section will change as data sharing policy and guidance progress.

Relevant work in progress:

• Data Sharing Capability Model
• Data Access Patterns

Overall, we should follow a common data sharing capability model, leverage reusable data sharing patterns and contribute to existing data sharing platforms by default.

Data providers should:

Data consumers should:

Data sharing enablers should: