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

6. Design for all data stakeholders

Continuity principle

Statement

We put the needs of data providers, consumers, subjects and end users at the centre of decisions about data sharing.

Why does this matter?

Data sharing is, by nature, a joint endeavour. Because data providers and data consumers are equally important participants of data sharing initiatives, and the needs and experiences of both groups should be reflected in their design.

Moreover, data sharing is also an ‘upstream’ pursuit: data is always shared for further use. These uses must be clearly defined prior to data sharing for legal and ethical purposes (Principle 9), but also to ensure that the needs of data subjects and downstream service end users are factored into the design of data sharing initiatives.

By centring decision-making on all those who are affected by sharing data, we can create initiatives with clarity, inclusivity and stakeholder needs at their core. This style of user-centred design is key to reducing barriers to participation in data sharing and fostering trust among data stakeholders.

How do we do this?

Overall, we should follow government guidance on automated decision-making, machine-readability and ethical AI practices when automating data sharing processes.

Data providers and consumers should:

• Actively participate in user research for data sharing initiatives, ensuring that solution designers understand their user needs and journeys.
• Continuously gather their own feedback from service end users and data subjects on how data sharing should be performed to meet their needs.
• Supply data sharing enablers with evidence of challenges and help them understand the context in which data sharing should be performed.
• Help data sharing enablers iterate and test solutions by providing users, representative data or permissions as necessary.

Data sharing enablers should:

• Engage in regular user research to understand the needs and experiences of all stakeholders involved in data sharing.
• Engage with user research communities to share findings and ensure that data sharing initiatives reflect the full scope of user journeys.
• Work closely with data providers and consumers to iterate and test solutions, and improve data sharing initiatives across their lifecycles.
• Design data sharing processes that are inclusive and accessible to reduce barriers to participation for both data providers and consumers.
• Explore how live data sharing initiatives could be evolved to serve new user needs.
• Minimise the environmental impact of data sharing solutions.