DATA for GOOD FOUNDATION
Build Trust and Innovation
When data is used ethically and intelligently, it drives innovation, builds customer trust, and keeps your business ahead of change.
Gain deeper insight into customer needs and behaviour by accessing relevant data.
Securely connect new and existing data sources—internal and external—via DATA for GOOD’s platform and infrastructure.
Protect your business with a secure, neutral platform built on strong governance principles — designed to reduce data-leak risk and support GDPR-aligned use.
Give customers clear transparency and control over the data they have consented to share.
Seamlessly integrate DATA for GOOD and your consent workflows into existing customer journeys.
DATA for GOOD Governance Tools
Embedding governance directly into operational data use
DATA for GOOD Governance Tools apply consent, governance, and evidence directly in how data is accessed, shared, and analysed. They are designed to make responsible data use practical in day-to-day operations, enabling insight and collaboration without sacrificing trust or accountability.
Rooted in DfG’s BLTSEC principles — Business, Legal, Tech, Society, Ethics, and Culture — the tools ensure that governance considerations are embedded across organisational, regulatory, and technical dimensions from the outset. Rather than treating governance as a compliance afterthought, DfG operationalises it as a shared, inspectable infrastructure.
Governance in Practice
DfG’s Governance Spine provides the operational structure that connects declared scope, aligned responsibilities, and verifiable evidence across the lifecycle of a data use case. It ensures that governance expectations are defined before activation, remain consistent during operation, and are inspectable over time.
Rather than relying on policy statements alone, the Spine embeds governance directly into onboarding, collaboration, and change management. It creates a shared accountability reference point that supports transparency, regulatory engagement, and coordinated ecosystem participation.
The Three-Layer Governance Stack
Each tool addresses a different stage of data use, but all operate within a shared governance and evidence model. Together, they enable organisations to move from defensible consent, to governed data collaboration, to trusted insight generation — while retaining control, legitimacy, and auditability.
By generating verifiable evidence of consent and data use, the tools help organisations meet regulatory expectations and demonstrate responsible data handling to regulators, partners and users.
Consent Evidence forms the foundation of the stack, creating a verifiable record of consent state from the point of integration onward. This evidentiary layer establishes the trust anchor on which all further data use depends.
Data Collaboration and Insight Generation are layered on top of this foundation. They operate only within the consent state and governance constraints defined below them, thus depending the guarantees provided by the lower layer.
System Principles
Progressive adoption by use case
Shared governance framework
Evidence-based, not trust-based
No centralisation of raw data
The product stack is delivered through three governance tools, each addressing a different stage of data use.
Governance Tool Layers in the DfG Stack
01. ConsentEvidence
FOUNDATION LAYER
Many organisations already collect consent — but struggle to prove how it has been handled when scrutiny arises. Consent Evidence provides a verifiable, independent record of consent state changes across systems, from the point of integration onward.
Instead of relying on fragmented logs, internal claims, or after-the-fact explanations, Consent Evidence forms a foundational evidence layer that shows:
What consent existed
When it changed
What it applied to
This makes consent handling inspectable and defensible when questions arise — from regulators, partners, or the public — reducing regulatory and reputational risk.
Consent Evidence forms the foundation for Data Collaboration and Insight Generation, which rely on the same underlying consent records and governance guarantees.
Dependancy
Required foundation for Data Collaboration and Insight Generation
What you get
An independent evidentiary layer on top of existing consent systems
Cross-system visibility into how consent is handled, not just within a single CMS
Ongoing, go-forward evidence of consent handling in practice
A way to demonstrate responsible consent handling under regulatory or public scrutiny
02. DataCollaboration
COLLABORATION LAYER
Many organisations want to collaborate around data, but are blocked by trust, liability, and governance risk once data crosses organisational boundaries. This is often worked around through bespoke contracts, manual controls, or avoided altogether — slowing partnerships, business development, and increasing risk.
Data Collaboration provides a governed, consent-based framework for working with data across organisations. It operates within declared consent and governance conditions and generates verifiable records of data access and interaction, rather than relying on assurances alone.
By making collaboration inspectable and accountable in practice, Data Collaboration reduces governance and coordination friction and enables organisations to realise value from data partnerships under clear, agreed rules.
Dependancy
Requires Consent Evidence to verify consent state and permitted use across participating organisations.
What you get
A governed framework for sharing and combining data across organisations
Collaboration that balances value creation with control, grounded in Consent Evidence and a neutral, citizen-centric governance model
Clear, inspectable records of who accessed which data, under what consent and conditions
A way to make data partnerships legitimate, defensible, and easier to manage over time
03. InsightGeneration
ANALYTICS LAYER
Organisations want to develop new insights, services, or products using sensitive or distributed data. But trust, consent, and governance expectations often constrain how analysis can be done. In practice, this leads to data being centralised, scope being limited, or analysis avoided altogether due to governance risk.
Insight Generation enables predefined, governed analytical workflows that operate within declared consent and governance conditions. It produces verifiable outputs and execution records without exposing raw data or bypassing consent.
This allows insight-driven work to move forward while maintaining accountability and confidence in how insights are generated — supporting innovation without eroding trust.
Dependancy
Requires Data Collaboration and Consent Evidence to execute governed analysis within declared consent and governance constraints.
What you get
A governed way to generate insights under defined governance and declared consent constraints
Verifiable execution records showing how insights were produced, not just the results
An enablement layer for analytics, innovation, and insight development that operates within permitted use
The ability to work with complex or sensitive data while retaining accountability and auditability
Discuss your use case with us
Get in touch, and we’ll help you identify the adoption pattern that fits your use case.
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Our Partners
DfG Projects & Results
Learn more about ongoing projects and how individuals, organisations, and society have benefited from the power of data.
Across health, social impact, and digital governance, DATA for GOOD initiatives demonstrate how trusted data sharing can improve outcomes, strengthen collaboration, and support evidence-based decision-making.
See all DfG projects
DfG Projects