This is Icebreaker One’s response to The Department for Science, Innovation & Technology’s Data intermediaries call for evidence. Please note that throughout this consultation, Icebreaker One uses the terms Open, Shared and Closed data as defined here.
If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org.
Call for evidence response:
Section B: Data intermediaries
Q4. Does the taxonomy above fully reflect the range of models of data intermediaries in the UK or elsewhere?
Based on the call for evidence definition, “data intermediaries” refers to a range of organisations that facilitate access to and exchange of data. The EU Data Space Support Centre’s Data Space Intermediary definition, also refers to “service providers for enabling services and functions: These providers do not intermediate the Exchange of Data Products. Instead, they intermediate the exchange of trust-related information or data product metadata”. IB1 proposes considering another interpretation of a data intermediary matching the EU definition above, termed “Trust Services”. This table should include an entry for Trust Services as follows:
Trust Services:
Trust Services enable members to adhere to the agreed rules for sharing data at scale within a Trust Framework (IB1 definition – https://ib1.org/trust-frameworks/). These services do not intermediate the exchange of data products. Instead, they intermediate the exchange of trust-related information or data product metadata.
The “Orchestration Service Providers” described in the UK Digital Identity and Attributes Trust Framework are examples of Trust Services:
- Identity and attribute broker service providers
- Identity and attribute hub service providers
- Identity access management service providers
- Distributed ledger service providers
This list isn’t exhaustive though. Other functions may be needed for other use cases.
Trust Frameworks: Defining and applying the rules
Trust Frameworks create the transparent rules and processes for sharing data at scale – across an entire sector, market, or geography. They set openly-published rules around:
- How organisations prove who they say they are
- Who is publishing data
- For Shared Data, who is accessing data and for what purpose
- Legal and operational responsibilities
Trust Frameworks are not intermediaries, but use humans and machine governance as market enablers. Schemes are the rulebooks of how organisations can share data. They define what can be shared, why, by whom, how, and what protections exist. Trust Frameworks and related Trust Services help apply the rules in a way that both humans and machines can understand. A critical design feature of a Trust Framework is that it does as little as possible. It doesn’t define the rules, nor does it touch the underlying data, or know who the end users are. It just verifies that rules have been agreed and can enable their enforcement.
Trust Framework design and operation: The role of Implementation Entity
Based on our work over the past 5 years on data governance for sectors such as energy, water and supply chains, Icebreaker One has developed a structured approach that we call Icebreaking. As a neutral, non-partisan non-profit we help stakeholders deliver impact by unlocking trusted data sharing at market scale. This open market architecture for data sharing includes both commercial and non-commercial data.
The Icebreaking process convenes stakeholders around purpose and priority use cases – building on our experience to save time and money. With strong governance and oversight, stakeholders and experts collaborate to co-design Schemes that address legal, technical, policy and communications needs. Trust Services can (optionally) be used to implement Schemes at market scale.
Ensuring that digital infrastructure balances the value to all stakeholders against security, cost and complexity considerations requires a neutral co-ordinating body. Icebreaker One is an implementation entity that can deliver governance and Trust Frameworks as a service. Open Banking Ltd fulfils a similar role, specifically for the Open Banking Trust Framework.
Section C: Barriers to data intermediary sector
Q6. What are the main barriers to performing data intermediation services in the UK, and how do they differ across sectors and models?
In IB1’s response to the Department for Science, Innovation, and Technology’s Technology Adoption Review, and IB1’s response to the Department of Energy Security & Net Zero Developing an energy smart data scheme call for evidence, IB1 noted a key barrier to technology adoption, investment, and participation is a lack of a consistency in vision and policy which is vital for the decision makers in the organisations and companies to de-risk technical and innovation investments. Having a cohesive, consistent vision with clear actions allows for stakeholders to incorporate data sharing and data access at the core of their decisions.
IB1 also notes that successful data intermediation requires specificity to be effective, in the form of a use case. Focusing on a use case avoids the pitfall of being designed too broadly and generically, rather than being designed to meet a narrow set of purposes and outcomes and then expand to other use cases.
IB1 supports following a use case approach to data sharing initiatives. This approach centres user needs, makes a business case for the effort of data sharing, and allows for:
- Market incentives: there must be an economic argument that policy can then amplify or mandate. If there is no financial incentive, there will be no movement.
- Removal of transactional friction: There must be “something in it” for everyone, or at least a path to cost reduction or a new business model. Removing friction can help everyone go together: this is never a ‘technology problem’ (e.g. absence of a data ontology).
- Documentation with the identified problem statement, actors and stakeholders, a clear goal, and the envisaged impact.
To maximise the benefits, use cases must:
- Address governance, user needs, business, social, legal, engagement and communications to ensure the solution is fit for purpose, and can be adopted by the market. IB1 observes that technical-led programmes tend to fail to gain traction or deliver against material user needs.
- Foster a community to ensure there is cross-sector collaboration. IB1 strongly recommends taking a joined up approach which is interoperable with initiatives across the economy.
Q7. What role should the government have in addressing these barriers? Are there examples of effective or ineffective government interventions in other countries or markets?
As mentioned in IB1’s response to the Department for Science, Innovation, and Technology’s Technology Adoption Review, and IB1’s response to the Department of Energy Security & Net Zero Developing an energy smart data scheme call for evidence,
To meet the combined needs of economic growth, environmental sustainability and social equity, the UK must fund institutions that can help convene and aid multi-stakeholder collaborations. Such support is essential to deliver open and accessible markets (available to the whole UK economy) and equally to protect our economy from monopoly behaviours. This applies to data intermediaries as much as it applies to the data publishers and data consumers they service.
Our previous experience has been that projects to co-design market-wide solutions without external or public neutral funding suffer from a collective action problem in which prospective partners are unwilling to contribute to the costs as the benefits of the developed outcome will accrue to them whether they contribute or not. Failure to fund risks a lack of cohesion, duplication, or a very limited trial with limited reusability.
Public signalling and funding enables IB1 as an implementation entity and facilitator of industry co-design to support an effective methodology and increase buy-in from partners and testers, resulting in better outputs and adoption.
More generally, IB1 supports developing, supporting, and promoting a principles-based approach to implement its national data infrastructure so different sectors can move at pace on their own, develop their own customer-facing values and business propositions, get them out into the market, but all anchored on principles of data rights, of machine interoperability and of fair value exchange: reciprocity is at the heart of all of this work.
Key principles for designing data sharing as infrastructure:
- Decentralised solution: guiding principles while allowing different sectors or other operational environments to tailor to user needs/circumstances, minimising barriers to scaling-up
- As digitalisation of the wider economy accelerates it is essential that any governance mechanism is built to function flexibly within a shifting technical landscape. There will be a continual balance between addressing user needs and potential threats, necessitating robust governance to be participatory and responsive to a full spectrum of social and environmental considerations shaping the operational landscape, for example including capacity to respond to forthcoming Net Zero 2030 milestones, negative incentives, corporate capture, unintended monopoly positions, and data misuse.
- Security: Data required for investment must undergo a thorough assessment of risks, benefits, security measures, and potential international standards as there may be implications for data transfer and use across the UK and international borders.
- Clear and consistent use of definitions and communications surrounding data. IB1 uses the data spectrum to communicate the definitions and differences between Open, Shared, and Closed data.
- Build upon prior art: IB1 recommends simple and low friction options which builds on previous implementation in other industries, for example Open Banking which has been endorsed by the Competition and Markets Authority (CMA) and the Financial Conduct Authority (FCA)
- Joined up approach to be interoperable with initiatives across the economy.
Q8. Can you provide examples of successful data intermediaries and the technological and non-technological factors that contributed to their success?
As noted in IB1’s response to the Department of Energy Security & Net Zero Developing an energy smart data scheme call for evidence, Open Banking is a case study for engagement for Smart Data within a Trust Framework. It has over 10 million users and over 22.1 million transactions per month. This provides strong evidence that there is both appetite and capability for British consumers to engage with Smart Data utilising a Trust Framework approach.
It is essential that Open Banking is viewed holistically as a Trust Framework – an entity incorporating technical, communications, engagement, legal and ongoing governance arrangements – rather than a technical solution.
Through providing clear roles and purposes for data intermediaries alongside openly-published compliance, legal and technical requirements, Open Banking has enabled a range of data intermediaries providing trust, integration and permission management services. Notable companies providing these services include Klarna, Plaid, Tink, TrueLayer, and Yapily, with combined valuations of billions of dollars.
IB1’s foundational work on Open Energy, Open Net Zero and approach to data sharing is based on the foundations of Open Banking. IB1 practises this through:
- Decentralised architecture implementation
- Advocating for common secure web standards (i.e. FAPI)
- Openly published rules and clear governance structure
- Openly listing service providers that are available
- Providing member services
A key learning from the success of Open Banking is to follow a use case driven approach.
See more information on the development of UK Open Banking here: https://dgen.net/0/2018/04/04/report-development-of-uk-open-banking/