Increasing Access to Data Across the Economy
INCREASING ACCESS TO DATA ACROSS THE ECONOMY
This report prepared by Frontier Economics for the UK Department for Digital, Culture, Media and Sport (DCMS) provides an evidence-based framework to help government prioritize policy interventions designed to increase access to and sharing of data across the economy. It reviews the rationales for government intervention, identifies six key data-sharing issues and corresponding levers, and outlines an initial application involving economic sizing and high-level assessment criteria. The study serves as a starting point for developing public policy to unlock the economic and social benefits of expanded data access.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Policy makers and researchers looking for an analytical framework to prioritize public interventions that expand data access and sharing across the economy.
What the document contains
The document covers the theoretical rationales for government intervention in data sharing, categorizes common barriers and opportunities, defines six government policy levers, and establishes an evaluation framework supported by initial economic sizing and case studies.
It does not provide binding legislation, enforceable regulations, or definitive conclusions for final policy design, noting that further primary research and ecosystem reviews are required.
- Government intervention to increase access to data can be structured around six distinct policy levers ranging from knowledge-building to mandates.
- Addressing data sharing risks and reducing costs through better data foundations directly affect the largest amounts of economic activity.
- Improving incentives and increasing knowledge of data sharing generate wide-ranging, indirect effects across ecosystems.
- Evidence on the effectiveness of existing data policy interventions remains very limited, highlighting the need for caution and further research.
· Executive Summary · 1 Introduction · 2 Rationales for Government intervention · 3 Evidence of barriers to access to data · 4 Determining the set of levers for Government intervention · 5 Our approach to assess levers for intervention · 6 Initial application of the framework · 7 Conclusions · 8 References · Annex A Further detail on evidence of data sharing issues · Annex B Further detail on case studies of data sharing ecosystems
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
0/5Clear responsibility for AI outcomes
screening score · 2026-10-23
Fairness
0/5Non-discrimination and equitable treatment
screening score · 2026-10-23
Human Dignity
0/5Respect for the inherent worth of persons
screening score · 2026-10-23
Human Oversight
0/5Humans remain in control of consequential decisions
screening score · 2026-10-23
Privacy
2/5Protection of personal data and private life
Perceived or actual risks of breaching data protection, intellectual property rights, or regulatory requirements may also provide a deterrent to sharing.
Figure 2 Data sharing issues
screening score · 2026-10-23
Transparency
0/5Openness about how AI systems work and are used
screening score · 2026-10-23
Enforcement
4/5Consequences and compliance mechanisms with real force
In March 2020, five suppliers had failed to comply and were banned from taking on new customers until they became DCC users.
Annex B.1 One-to-many case study 1: smart meters
screening score · 2026-10-23
Impact Assessment
2/5Required assessment of an AI system's risks/impacts before or during use
Support (new) ways to address the risks associated with data sharing
Figure 3 Levers for intervention
screening score · 2026-10-23