This is Icebreaker One’s response to Ofgem’s Energy Digitalisation Governance – Architectural Coordination letter.

Please note that throughout this consultation, Icebreaker One (IB1) 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.

Executive summary

This response advocates for a focus on coordination of the energy sector’s data architecture and energy data governance as a fruitful starting point for architectural coordination of digitalisation governance. It emphasises that coordination is an ongoing process with human and technical components. It further works to the principle of minimisation, specifying that coordination activity must work in the leanest feasible manner, delegating to existing sector processes where possible and only acting where there are clear requirements for further intervention. We propose that the coordination challenge should be met via the appointment of an industry–independent coordination body composed of Secretariat, Research, and Monitoring functions. 

We do not propose that the coordinator should have enforcement powers, as these are most readily delivered under the existing regulatory and legislative capabilities of Ofgem and DESNZ. However, both Ofgem and DESNZ must be required to consider options from the coordination body in their determinations. 

The Secretariat should act as an independent facilitator for participatory governance processes which can adapt flexibly to evolving coordination needs and ensure accountability. 

The Research and Monitoring function should have two responsibilities:

1. mapping the domain(s) in which coordination is enacted in order to support effective participatory governance
2. monitoring and reporting on the outcomes of coordination activity to improve transparency and join-up with adjacent policy/regulatory goals (energy and cross-sector). 

We suggest that this function includes coordinating and monitoring the delivery of the sector’s digitalisation roadmap. We suggest that the body would require a small permanent staff to ensure continuity of process, with additional staffing contracted or seconded in on a short term basis for agile response to emergent needs (e.g. particular technical or domain expertise concerning a particular coordination challenge). This lightweight approach will deliver the intended benefits at a reasonable cost to the bill- or taxpayer. 

Response

Where should we focus?

Prior to addressing specific prompt questions, it is important to discuss the boundaries of the digital space and its component parts. Digitalisation is an umbrella term which can be used to refer to a wide range of different processes, technologies, activities, actors, and frameworks. Accordingly, the term is prone to some mystification as well as the drawing of false equivalences between digitalisation and technology. While we agree with Ofgem’s statement that there is an emergent need for coordination in energy sector digitalisation, we emphasise the importance of defining the boundaries of what exactly, within the wider digital space, is the target for this activity.

As discussed in IB1’s response to DBT’s Invest 2035: industrial strategy consultation, and in alignment with the National Data Strategy, the bedrock of digitalisation lies in data. In parallel, a significant proportion of industry digital activities to date involve laying the foundations for how data is governed, shared, and used within the energy sector. Accordingly, we strongly suggest that Ofgem’s architectural considerations at the present time focus on the coordination of the sector’s data architecture and associated energy data governance rather than other elements of the digital transition. Coordination in other digital arenas may well be required in future and we support future consultation accordingly. However, we do not believe that it represents value for money, nor effective prioritisation against net zero, to focus on these areas at the current time.

It is also important to draw a clear line between the valuable work currently progressing in large but focused sector-wide initiatives, such as the Data Sharing Infrastructure (DSI) or Consumer Consent Solution programmes, with the overall task of coordinating sectoral data governance. At its heart, data is not a technology, an ontology, or a standard. Rather, data is highly contextual — defined by a framework of rights-based governance, shaping how it can be gathered, shared and used, by whom, and for what purpose(s). 

Many ongoing data sharing initiatives in the sector (currently in their definition, prototype, or pilot phases) are advancing technology-led projects. These technical developments augment the sector’s capacity to collect, transport, and process data which is valuable. However, we have raised concerns in several forums that these projects risk developing in a manner which results in disjointed data governance. Coordination in the data governance arena would ensure that technology buildout will be clearly linked to user needs, meet appropriate levels of security, and promote legal interoperability supporting clear and confident data use. Without coordinating energy data governance, we risk building an environment where data exchange is improved on a technical level, but the real world use of the data remains subject to the same limitations that have been established by the research literature. 

How would coordination be achieved?

Coordination is an ongoing process between people and organisations, which will contend with ‘live’ and sensitive factors such as vested interests as well as wider factors such as the economic climate. We would anticipate a common digital architecture coordination function extending beyond a document, to capture the scale and nature of the coordination problem. The “function” of architectural coordination delivers the value – a document could describe it, but would not enact it. We believe that an independent entity is required to operationalise effective coordination. We also advocate that this should be achieved through as thin a layer of activity as possible, in order to present the best value for money and time. 

Additionally, we emphasise that our engagement with industry via the Open Energy Advisory and Working Groups has highlighted a need to think of coordination not as all organisations within the sector doing things in the same way. Rather, coordination should  focus on harmonisation and interoperability within company contexts of operation and as a common framework which aligns activities and reduces duplication. 

Open Energy

We believe that Open Energy is the only initiative currently operating within the energy sector that holds the independence, governance approach (designed in collaboration with the Institute of Directors), cross-sector experience, technical knowledge and flexible capacity to address architectural coordination of energy data governance. 

Open Energy, the competition-winning programme developed under the UKRI Modernising Energy Data Access initiative, identified and articulated the need to make it straightforward to find, access and share energy data. Open Energy was funded by £1.3m public money through three phases and is currently funded by commercial members. 

Open Energy is coordinated by the public-benefit nonprofit body, IB1, and has been specifically developed for this purpose using a combination of radically transparent methods of open working, extensive consultation with stakeholders, and the input of specific domain expertise from energy industry, academic, cybersecurity and Smart Data specialists.

Successful governance initiatives, including Open Banking, have taken the model of having an independent, non-sectoral incumbent body take on an architectural coordination role. Additionally a key recommendation from the 2021 Energy Digitalisation Taskforce Report summarises:

It is recommended that an independent, commercially disinterested body is established by Government to develop and/or incubate Public Interest Digital Assets on behalf of the sector. The Body should be given a mandate and funding to develop and deploy assets (either directly or via partners), directed by a stakeholder panel interested in the current and future needs of the energy sector. The benefit of this is that it would report to government but operate to the side of it.

As part of discussions following this letter, we appeal to Ofgem and DESNZ to enter into dialogue with Open Energy and its membership to discuss how Open Energy might be appropriately strengthened (e.g. participation or enforcement mandates) or configured (e.g. as a special purpose vehicle) to enable it to meet the required coordination function.

Our focus on governance is driven by the view that making data work harder for net zero isn’t a technology challenge. Rather than a deficit of data or technologies to manage it, it’s a deficit of effective processes for groups of organisations to come together, cooperate on and set the terms of data sharing that’s really holding us back.

In our work, governance is an ongoing process. The execution of this process produces decisions that enable data sharing to take place. In practice, this involves establishing principles, defining clear roles and responsibilities, and agreeing priorities and tasks. It also involves collaborating to create artefacts to express and enforce these decisions, such as legal agreements and technical standards.

We have a particular approach to organising data governance at IB1. We use a tiered system of Steering, Advisory and Working Groups to bring organisations together. These groups work together to agree and adopt:

• User needs & impact: commercial priorities, business cases, and prospective new products and services.
• Technical infrastructure: shared ontologies, APIs, schemas and standards to support data exchange. 
• Licensing & legal: data sharing agreements, modes of redress and liability frameworks.
• Engagement & communications: common language, stakeholder engagement and recruitment.
• Policy: alignment with corporate policy and industry regulations.

Participation in this process can be either voluntary (initiated by the market), or mandatory (demanded by regulators).

Using this collaborative process within the Open Energy programme, IB1 has designed, implemented and operates the Open Energy data search engine, the Energy Sector Trust Framework (ESTF), and within it, the Assured Open Data scheme. The ESTF is supported by IB1-developed open source Trust Services, including common technical specifications, a registry providing human- and machine-readable data sharing rules, a public directory of members and a secure portal for members to manage their information and issue digital identity certificates. These atomic, reusable services also power the cross-sector Perseus scheme that automates emissions reporting based on smart meter consumption data for UK SMEs. 

Our approach is inspired and practically informed by the UK’s Open Banking ecosystem, which enables data to be shared in new ways across banks and other financial services. It now has 15 million users and is projected to sustain a $12bn market of data-driven products and services. This change has been achieved not by building a big, centralised database of customer banking data, but by governing who should access it and how it should flow. 

Key questions:

1. Where is there a need for architectural coordination across the sector to unlock the full value of energy system digitalisation? 

As outlined above, we advocate that data governance, including the governance of data sharing, represents the clearest priority for coordination activity in the current moment. Needs are likely to change over time, so this must be regularly re-assessed in light of the wider sectoral environment (e.g. digital maturity, progress towards net zero, contextual policy challenges, economic environment etc). Additionally, we urge Ofgem to approach coordination through the lens of cross-sector interoperability and harmonisation, rather than a “one size fits all” standardisation. 

There is a need for coordination of data governance in the following arenas:

Secretariat:

• Participatory processes: An independent facilitator is needed to support the involvement of a range of participants (directly or via a representative structure) which can adapt flexibly according to coordination needs. This requires:
  • Strong governance processes – e.g. covering participant selection, means of input, minuting, reporting, and decision-making
    • Ability to offer tailored mechanisms where required – e.g. working groups to focus on specific parts of the sector, or task and finish style groups to support elements of digitalisation strategy delivery.
  • Independent Secretariat function with experienced administrators to execute governance processes and communicate expectations of timescales, plans, key decisions etc.
  • Where required, the provision of independent chairing or facilitation services
  • Dispute resolution process, linked to existing sector mechanisms and to participatory governance processes.
  • Participant accountability mechanisms (linked to enforcement – see below).
• Enforcement: we suggest that enforcement activity occurs under the umbrella of either Ofgem or DESNZ. This may include:
  • Ability to compel involvement in participatory processes (at least at some defined level) of regulated entities to ensure fair and balanced process
  • Ability to invite external stakeholders as and when required, in a transparent manner (e.g. pinned to a published methodology for a certain use case / decision / piece of research).
  • Ability to action change
• Accountability: any coordinating entity must be accountable to its stakeholders. We suggest this is supported by the following:
  • Openness policies enabling scrutiny (e.g. of methodologies, processes, minutes, reports)
  • Where required (for security purposes), clear rules defining how scrutiny will be undertaken among closed audiences
  • Defined process for dispute resolution integrated with existing sector mechanisms
  • Clear processes for change management
  • Defined avenues for external involvement in participatory processes
• Other:
  • We strongly suggest that the Secretariat is empowered to communicate across sectors in order to best learn and harmonise with digital and data sharing initiatives that cross sector boundaries.

Research and monitoring:

• Mapping: light touch, but regularly re-visited, research and documentation to understand current and emergent actors, activities, points of interaction/crossover/competition, and gap analysis – this will also help draw the boundaries around the remit of current coordination priorities and future considerations. This must:
  • Include cross-sector activities
  • Include cross-scalar activities (e.g. map devolved authorities, local etc as well as national initiatives)
  • Include identification of priority use cases / sets of use cases, particularly which require addressing via pre-competitive activity.
  • Highlighting areas where government or regulatory input may be required to meet policy goals.
  • De-mystify parts of the digital transition into clear component elements (both socio-economic and technical) with defined terminology
• Monitoring: 
  • Devising, implementing and openly publishing Monitoring, Evaluation and Learning (MEL) methodologies and reports in accordance with a transparent schedule – including ways to ensure digitalisation supports other policy goals (e.g. Net Zero, Warm Homes Plan, Flexibility development etc) and increases transparency in an area of rapid sector growth.
  • Coordinating the delivery of the sector’s digitalisation roadmap to ensure that effort is not duplicated and complexity is minimised. While we welcome NESO’s work to address sector-wide digitalisation planning, we suggest that this function should be devolved to an independent body in order to appropriately hold all actors to account. 

2. What are the constituent elements of architectural coordination of digitalisation in the energy sector?

We have interpreted this question to refer to how architectural coordination could be operationalised through a coordinating body. We suggest that the body is composed of an experienced Secretariat, which is vital to good governance processes. It must also have a small research and MEL team as outlined below. Additional elements should be flexible and responsive to the developing ecosystem. Accordingly, it may be beneficial for the body to be able to second in expert staff on a temporary basis. Across the board it is vital for the coordination body to be independent.

Secretariat component

A Secretariat coordinates and supports group meetings to ensure the programme is making effective and timely decisions and is aligned with strategic objectives. Secretariat  administrative support includes: meeting arrangements, pre-read and agenda dissemination, note-taking and drafting of formal minutes. Maintenance of an effective, experienced Secretariat requires an appropriate budget for ongoing roles.

As outlined in question 1, the Secretariat component would support participatory processes, enforcement, and accountability functions. It is vital that the Secretariat retains independence from other sector bodies in order to navigate conflicts of interest and build trust among participants.

Research and monitoring component

An effective research and monitoring function requires the maintenance of a small team with expertise in research methods, knowledge transfer, and reporting. We suggest that primary research should be participatory, bringing in experts to minimise cost and duplication. The research element of this component may require a small flexible fund to support short term targeted projects (e.g. mapping stakeholders who must be consulted when developing a specific area of pre-competitive activity). The monitoring element requires access to participation from sector authorities to define the target and frequency of monitoring activity and dialogue with the wider sector, and appropriate experts, to identify or devise appropriate methodologies. It is essential for this component to have the ability to freely publish monitoring results, with sensitivity to factors such as security when defining the appropriate level of openness. This component should provide a forum for feedback from scrutiny as and when required.

We again emphasise the importance of independence in this arena as there may be cases where the component sheds light on poor performance or emergent issues. This requires an independent entity to perform; it cannot be nested in an existing body without risking conflict of interest.

3. What value could a common digital architecture document for the energy sector provide?

Coordination is an ongoing process between people and organisations, which will contend with ‘live’ and sensitive factors such as vested interests as well as wider factors such as the economic climate. We would anticipate a common digital architecture coordination function extending beyond a document, to capture the scale and nature of the coordination problem. The “function” of architectural coordination delivers the value – a document could describe it, but would not enact it. We believe that an independent entity is required to operationalise effective coordination

Potential benefits of architectural coordination include:

• Avoiding duplication — e.g. multiple Trust Framework providers that potentially aren’t interoperable
• Learning from other sectors — lacking clear deadlines and costs. The Pensions Dashboard Programme has an estimated cost of £289m, with no released date of when the dashboard will be made available to the public
• Saving money and reducing time-to-value by providing market participants with repeatable processes and building on well-understood standards 
• Prioritisation of key use cases
• Avoid the time and financial costs of a lack of coordination, especially on urgent causes such as net zero

4. What function may be needed to deliver architectural coordination and how would it interact with functions/organisations that are delivering digital public infrastructure (DSI/NESO, Consumer Consent Solution/RECCo, Smart Metering Network/DCC, FMAR and SDR/Elexon) 

• Ability to liaise and harmonise across sectors — e.g. Smart Data schemes, DSIT, Smart Data Council
• Cross-sector thinking is required to achieve the size of impact that the Industrial Strategy and The Clean Power Plan have outlined
• Must be a non-profit dedicated to the public good to avoid distorting the market and discouraging commercial members
• A function should be judged against the criteria of:
  • How light-touch and small it can be in order to deliver the needed effect
  • How much value is gained by stakeholders from their participation

5. Is coordination an ongoing task (including monitoring), or a temporary task to deliver the elements needed (from q2)? 

We strongly encourage that coordination must be an ongoing task, including monitoring, and acknowledge that it will adapt and change as energy digitalisation evolves. Governance must be designed to assess and adapt to changes. 

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. We have omitted questions which we did not answer.

Consultation response:

18. Please provide any feedback on the proposal to refine the definition of scope 2, to emphasize its role within an attributional value chain GHG inventory and clarify that scope 2 must only include emissions from electricity generation processes that are physically connected to the reporter’s value chain, excluding any emissions from unrelated sources?

This response is on behalf of the Perseus programme’s member organisations. Perseus aims to unlock access to finance that reduces emissions, by automating sustainability reporting for every SME business in the UK. Perseus operationalises one granular use case focusing on the sharing of 30-minute electricity consumption data, which is combined with corresponding 30-minute local grid carbon intensity readings to calculate assurable monthly GHG emissions (See Perseus’ emissions calculations: https://registry.core.sandbox.trust.ib1.org/scheme/perseus/process/emissions-calculations/2025-10-23). The consumption data is sourced from SMEs with either a) a single business premise and a single, unshared smart meter, or b) an account with Perseus member Energy Data Provider that can provide half-hourly electricity consumption data. 

We welcome the GHG Protocol’s efforts to update the Scope 2 guidance. As the grid decarbonises, the current annual, market-wide accounting framework is increasingly insufficient for capturing the reality and complexity of electricity consumption. Perseus is currently UK focused and requires 30-minute electricity consumption and local grid carbon intensity granularity, however, we encourage the protocol to globally require reporting organisations to use the best possible available data. 

The proposal to restrict sourcing to the same “deliverable market boundary” rightly addresses the disconnect where companies claim emission reductions from grids they do not physically use. However, boundaries must be pragmatically defined.

Perseus member companies note that restricting procurement to narrow pricing zones could strangle market liquidity and prevent companies from supporting high-impact projects in adjacent, interconnected grids where decarbonisation is necessary. The final standard should explicitly allow for procurement across recognised interconnected power pools (e.g., EU-wide) rather than strictly enforcing narrow pricing zones.

19. Please provide any feedback on the proposal to clarify the LBM definition to reflect scope 2 emissions from generation physically delivered at the times and locations of consumption, with imports included in LBM emission factor calculations where applicable? 

As Perseus uses location-based method emissions calculations, we will only comment on LBM changes. 

The proposal to refine the Location-Based Method by prioritising a hierarchy of “Local” and “Hourly” data over national annual averages is scientifically sound. It correctly identifies that grid carbon intensity varies significantly by time and place. The administrative burden of the proposals may affect different business structures in quite different ways, potentially introducing new costs to distributed business with sites that are geographically dispersed. We suggest that the potential for an element of aggregation is considered. For example, this could mirror the ESOS model where a relevant proportion of the portfolio is surveyed and information is then extrapolated to the rest of the portfolio.

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.

Consultation response:

Regarding paragraph 3.36 in the Statutory Consultation on the RIIO-3 Licence Drafting modifications – reasons and effects document:

Generally IB1 supports a common Digitalisation Re-opener to encourage digitalisation by allowing network companies to seek funding for data and digital related projects with a broader scope than just IT hardware or software upgrades and to align with RIIO-ED2.

IB1 supports digitalisation as key for energy sector decarbonisation, and required for the investment in flex services and the coordination between sectors who rely on energy to meet their decarbonisation targets (water, transportation, built environment, industry).

IB1 supports sector-wide convening and governance to ensure digitalisation happens in a coordinated manner and can enable ‘whole system solutions,’ as promoted in RIIO-ED2 and realise the subsequent cost savings. IB1 supports Ofgem to continue to promote and finance whole system digitalisation coordination in RIIO-ED3.

As there are many ongoing data sharing and data governance initiatives e.g. consumer consent solution, flexibility services, Data Sharing Infrastructure (DSI), which are currently in progress at different stages of development (definition, prototype, or pilot). Ofgem should not expect these programmes and underlying challenges the projects aim to solve to be resolved by the end of RIIO-ED3 (2031). Data sharing and data governance needs and subsequent solutions will evolve over time as we continue to electrify and connect the UK’s grid. As mentioned above, Ofgem needs to ensure ongoing governance and sector collaboration on data and digitalisation – reinforcement of this would be welcomed in addition to specific plans to expand/evolve data governance initiatives.

With the progress of the Data Sharing Infrastructure (DSI) programme, IB1 anticipates ‘Shared Data’ sharing will evolve and will inform the evolution of data best practice (DBP) guidance. In particular, as data sharing scales, the need to standardise and harmonise legal and technical approaches will become more pressing in order not to slow innovation and add unnecessary cost. IB1 recommends that DBP should include guidance around Shared Data within the triage processes and licensing decisions, highlighting the role of Shared Data Schemes to provide definitions that aid interoperability and maximise impact.

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. We have omitted questions which we did not answer.

Consultation response:

Do you agree with the proposed implementation approach? Yes.

Rationale: We appreciate that there is a governance in place to discuss and approve the proposed implementation. We would welcome further transparency on the outcomes of applications to access data via this method and suggest that a summary of cases are made openly available after a 6-12 month trial period. Ongoing avenues for scrutiny remain important.

Please provide any further comments you may have.

As we are looking holistically at the smart meter data landscape, we will continue to work with the SEC and engage as it develops on a case by case basis and impacts wider use cases.

A draft of this position paper was circulated ahead of a licensee working group meeting held on November 26, 2025. Following input from the workshop, this updated draft is being circulated for further feedback from wider energy data stakeholders. 

Open Energy members hope that all RIIO-2 licensees, and the users of their data, will benefit from a clearly-articulated position on Open Data classification and access control. They would particularly welcome feedback from licensees who use third-party data platforms.

The Google version of the position paper is open to comments. Alternatively, interested parties may download a Word version. 

Please send comments or feedback to openenergy@ib1.org before February 2, 2026.

Key points from the position paper

RIIO-2 licensees that are members of Open Energy will:

• Adopt and enact an updated Assured Open Data definition that includes purposes for registration:

• D1.5.3 Anonymous downloads of open data is strongly preferred, but where the dataset requires compulsory registration before download:
  • D1.5.3.1 Registration is only conditional on completion of a lightweight challenge necessary for technical measures to minimise spam and bot abuse, such as verifying receipt of an email
  • D1.5.3.2 Acceptance of registration is automatic and immediate
  • D1.5.3.3 Registration may only be denied or withdrawn for misuse
  • D1.5.3.4 The registration process does not introduce any barriers to automated downloads or API access. Access to data is identical in all respects to a simple HTTP download of a published URL or API, except for the addition of a static credential or token that does not need renewing
  • D1.5.3.5 Require additional opt-in consent to use registration data for any further purpose. Data access must not be made conditional on obtaining any additional consents (e.g. use of registration data for analytics)
  • D1.5.3.6 If registration is only available via a third party platform (Data Controller), the third party must also comply with conditions D1.5.3.1 – D 1.5.3.5
  • D1.5.3.7 Third parties must transparently provide privacy policies and terms and conditions to the user if/where these differ from those of the Data Publisher.

• Apply the definition to metadata and data, meaning either or both may require registration
• Classify data requiring this form of registration as Open
• Licence data requiring this form of registration with either CC-BY-4.0 or OGLv3
• Implement information on registration forms/access gating screens making clear the purpose of this form of registration to end users and work with other licensees to align this language
• As required for compliance with UK GDPR, ensure privacy policies correctly reflect the use and protection of registration data, the length of time the data will be held, the situations where it would be disclosed
• Ensure terms of service for data portals do not contradict the Open Data licence being asserted for datasets on the portals
• Provide information in the registration process and/or the dataset listings that clearly separates Open Data “lightweight” registration from Shared Data registration requirements where registration may be used for other purposes, including limitations on access or use of the data
• Use registration as an opportunity, on a strictly opt-in basis, to provide additional benefits to users such as subscription to dataset update notifications or notifications of training opportunities

If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org. We have omitted questions which we did not answer.

About Icebreaker One

Icebreaker One (IB1) makes data work harder to deliver net zero. We do this by orchestrating the development of focused, decentralised Schemes that unlock data from across organisations at market scale.
Perseus, for example, enables businesses to access over $100B of green finance, by automating high-quality sustainability reporting for every SME in the UK. The Schemes we orchestrate are inspired by the architecture of the UK’s successful Open Banking ecosystem and the interventions that brought it about.

1. What issues do customers face in accessing their data held by digital markets firms and sharing that data with third parties?   

‘Digital markets’ are hard to define, given the pervasiveness of the web and related technologies. Almost all companies will use web technologies to exchange goods, services or information. 

The following are examples of consumer markets that we think are particularly reliant on network effects, data-driven operations and multi-sided interactions: 

• Social media (such as Facebook, Twitter, TikTok, Instagram, Threads and Bluesky).
• Messaging (such as Whatsapp, Messenger, Telegram and Discord).
• Online marketplaces and retailers (such as Amazon, Temu, Shein, eBay, Gumtree, Etsy and Depop).
• Payment and transaction (such as Shopify, Klarna, Visa, PayPal and Stripe).
• Operating systems (such as Microsoft Windows, MacOS, Linux, Android and iOS).
• Web browsers (such as Chrome and Firefox). Email (such as Gmail and Outlook).
• Search (such as Google Search and Bing).
• App stores (such as Apple App Store and Google Play Store).
• Virtual assistants (such as Siri and Alexa).
• Large language models and interfaces to them (such as GPT-4, Chat-GPT, Copilot, Gemini, Claude and Perplexity).
• Cloud services (such as Google Photos, DropBox and OneDrive).
• Online courses and learning (such as Coursera and Udemy).
• Jobs (such as LinkedIn, Indeed and Adzuna).
• Loyalty schemes (such as Nectar, Clubcard and Avios).
• Gaming (such as Steam, PlayStation Network and Xbox Live).
• Gambling and betting (such as Bet365, 888 and SkyBet).
• Music streaming (such as Apple Music, and Spotify).
• Podcast streaming (such as Spotify, BBC Sounds sounds and Apple Podcasts).
• Books and audiobooks (such as Audible and Kindle).
• Video streaming (such as BBC iPlayer, Sky, Netflix, Amazon Prime and Disney+).
• News (such as Sky News, BBC News and Apple News).
• Content distribution (such as YouTube, OnlyFans and Substack).
• Travel (such as Airbnb, booking.com, Expedia and Skyscanner).
• Ticketing (such as Viagogo, StubHub and EventBrite).
• Navigation (such as Google Maps, Apple Maps and CityMapper).
• Ride hailing and food delivery (such as Uber, Bolt, Deliveroo, UberEats and JustEat).
• Gig economy (such as Upwork and TaskRabbit).
• Smart devices (such as Philips Hue and Apple Homepod).
• Health applications and wearables (such as ClassPass, Fitbit, Oura, Whoop, and Flow).

IB1 is generally involved in data sharing schemes where businesses initiate data sharing, rather than individual customers directly. However, we understand that both individual consumers and businesses can face a variety of issues in accessing their data from the services they use and sharing that data with third parties, including:

• A lack of transparency in obtaining consent, including overly legalistic wording, items hidden in small print, and a lack of clarity around the full range of partners’ data will be shared with and/or for what purpose(s).
• Lack of trust – this is key for obtaining consent. 
• Individual/household dilemma – consent for data sharing pertaining to a whole household of people is obtained from a single individual (there may also be a gender bias here if the account holders tend to be male) who may or may not actually live at that address (eg shared subscription service) – there is no mechanism to ensure household members are consulted.
• Revoking or changing consent – it is often easy to give consent (e.g. automatic pop-up) but much harder to change or revoke consent (e.g. requires a log in, hidden in a long settings menu, not available by non-digital means) – this requires much more transparency and an easy process.
• Linked services – Lack of understanding about the impacts of giving, changing, or revoking consent for services that may be linked (e.g. reliant on data flows) but potentially operated by different companies. For example, consumers may not understand the impact of rejecting access to a type of consumption data on access to smart products and services.

2. The government would like to identify where businesses are being held back by poor data access and where these data access issues could be helped through a Smart Data scheme. What use cases do you believe could be supported through a Smart Data scheme to address those issues, including types of products and services that ATPs might be able to offer, and what outcomes could this result in? 

Defining digital markets where businesses are particularly held back by poor data access is again hard to define.

In the context of this consultation – and to delineate this work from the UK Government’s existing work on Smart Data in more clearly defined, regulated markets such as energy and finance – the following can be seen as examples of business-to-business digital markets:

• Operating systems (such as Microsoft Windows, MacOS, Linux, Android and iOS).
• Cloud and compute (such as Amazon Web Services, Microsoft Azure, and Google Cloud).
• Virtual workspaces (such as Microsoft 365 and Google Workspace).
• Project management and productivity (such as Asana, monday.com and Notion).
• Instant messaging and video conferencing (such as Zoom and Slack).
• Large language models and interfaces to them (such as GPT-4, Chat-GPT, Copilot, Gemini, Claude and Perplexity).
• Financial management and accounting (such as QuickBooks, Sage and Xero).
• Customer relationship management (such as Salesforce, Hubspot and Mailchimp).
• Data science and reporting (such as Databricks and Microsoft BI).
• Content production and editing (such as Adobe, Canva and Figma).
• Social media (such as Facebook, Twitter, TikTok, Instagram, Threads and Bluesky).
• Recruitment (such as LinkedIn, Indeed and Adzuna).
• Online marketplaces and retailers (such as Amazon, Temu, Shein, eBay, Gumtree, Etsy and Depop).
• Logistics and distribution (such as SAP, Oracle and EasyShip).
• Online advertising (such as Meta Ads and Google Adsense).
• Payment and transaction (such as Shopify, Klarna, Visa, PayPal and Stripe).
• Web publishing and content management (such as WordPress, Wix and Squarespace).
• Content distribution (such as YouTube and Substack).
• Ticketing (such as Viagogo, StubHub and EventBrite).

This list is far from exhaustive; there are many further domain-specific digital markets.

At IB1, our focus is to drive the development of schemes around tightly-focused challenges or use cases related to net zero. Our flagship programme, Perseus, enables small-and-medium sized businesses to share granular emissions data from their smart meter systems with banks and other lenders. By providing lenders with the accurate and assurable data they need, the Perseus enables participating businesses to access loans and other finance to help reduce their emissions.

We urge DSIT to explore opportunities for Smart Data schemes to drive the sharing of similar energy consumption and emissions data related to these digital markets. The cloud and compute services market, for example, is responsible for a significant and increasing share of global greenhouse gas emissions. The data centers it uses consume close to 3% of the world’s electricity and global greenhouse gas emissions comparable to the airline industry. This could be achieved efficiently by developing or adapting Perseus.

3. What types of data and data holders would need to be in scope of a scheme in order to support any business models and address data access issues and use cases you have identified above? 

Data and data holders to target will depend entirely on the purpose of any Smart Data scheme. 

We believe it will be more difficult for the UK Government to establish a ‘contained’ scope for a Smart Data scheme here than in more clearly defined, regulated markets such as energy and finance. With digital markets, services are often entwined – for example, Facebook is both a social media platform and a marketplace for goods.

Open Banking was delivered through clear identification of a problem in the consumer banking market, supported by evidence. Any smart data scheme for digital markets will need a similarly thorough analysis of the market dynamics that require improved data access and intervention. 

In determining what data holders should be within scope of a Smart Data scheme for digital markets, DSIT could adopt a similar approach to the UK’s Online Safety Act and the EU’s Digital Market Act. Although imperfect – see discussion around Wikipedia’s classification under the OSA – these interventions target organisations with the power to act as gatekeepers to particular markets, primarily based on their user numbers and market position.

In determining the scope of any Smart Data scheme for digital markets, we urge DSIT to:

• Identify a very clear use case. Without this, data sharing doesn’t work. A clearly defined use case ensures there is no ambiguity around the purpose of the scheme and what it must achieve.
• Arrive at use cases and data sharing rules collaboratively. Our approach, Icebreaking, involves scheme co-creation with regulators, consumer organisations and civil society as well as industry.

4. What are your views on the feasibility to deliver a digital Smart Data scheme? Please consider any current or planned industry developments or changes that might affect delivery and highlight any key challenges.

Delivering a Smart Data scheme for digital markets is eminently feasible, even accounting for the difficulties described above. Perseus is proof of this, with banks starting to use the data to inform real loan-making.

5. Do you have an initial or provisional view on the likely impacts (positive and negative) on:

• Existing and future customers
• Data holders
• Small and micro businesses

We encourage the identification and definition of clear use cases with defined users (as mentioned in question 3) to be able to comment on likely impacts.

6. Do you have an initial or provisional view on the likely impacts (positive and negative) on:

• Innovation in the supply or provision of goods, services and digital content whether directly affected by a scheme or otherwise
• Competition in markets for goods, services and digital content affected by the regulations or other markets
• Business investment in the UK
• Economic growth

We encourage the identification and definition of clear use cases with defined users (as mentioned in question 3) to be able to comment on likely impacts.

7. What challenges and risks should we consider when developing a digital markets smart data scheme and how can we mitigate these? This might include (but is not limited to): competition; customer exclusion; data quality or data misuse; ethical, operational or technical readiness.

We see the following risks to successful delivery: 

• Developing a centralised solution. 
  • Mitigation: embrace a decentralised model, which aligns with the approach taken by Open Banking, and the architectural principles of the Data Sharing Infrastructure for ease of access and protection (ensures alignment with national strategy, Open Banking has been endorsed by the Competition and Markets Authority (CMA) and the Financial Conduct Authority (FCA)).
• Not codifying the relationship and responsibilities of the smart data scheme to be in support of the UK’s net zero and climate targets. This is essential to meeting the UK’s net zero and industrial strategy goals.
  • Mitigation: Codify the relationship between a digital market smart data scheme and existing net zero goals.
• Not following a use case driven approach. The risk is trying to do too much at one time, and the programme becomes overwhelmed without a core focus point.
  • Mitigation: follow a use case driven approach 
• A chosen use case does not have a clear business impact case. If there is no financial incentive, there will be no movement.
  • Mitigation: an advisory group articulates their business case for the chosen use case. 
• Failure to implement governance from the start, and governance failure to address broader user needs, technical implementation, legal, communication / engagement and policy impacts.
  • Mitigation: robust governance from the outset. 
• Lack of cross sector collaboration. Risk of non-interoperability and not taking the learnings from other sectors.
  • Mitigation: actively engage with stakeholders from the start.
• Too much emphasis on a technical solution  – must equally address governance, user needs, business, social, legal, engagement and communications to be successfully implemented and ensure a scheme is fit for purpose
  • Mitigation: understand the holistic approach required – user needs, legal, policy, and communications. https://ib1.org/sops/governance-schemes/ 
• Cultural change and industry readiness 
  • Mitigation: interact with the current data sharing culture within the energy companies, and consumers must be engaged to understand their value proposition. 
• Stakeholder engagement for collective agreement across the sector
  • Mitigation: engage early, often, and formally through governance.
• A scheme is seen as a technical solution rather than a holistic solution.
  • Mitigation: a trust framework incorporates technical, communications, engagement, legal and ongoing governance arrangements.
• Unequal access to smart services if we do not address the challenges known to exist in digital markets or known barriers to access, and any other infrastructure collecting the data which will be used in the scheme. This unequal access will be baked into any smart services offered and may unintentionally miss out key beneficiaries.
  •  Mitigation: robust governance experience to reduce unintended impacts.
• Creating unintended monopolies, negative incentives, corporate capture, and data misuse
  • Mitigation: robust governance, embracing and building upon open source solutions. 

8. What are the potential implementation costs to industry of introducing a digital markets Smart Data scheme? What aspects of a scheme might be most expensive to implement?

Open Banking is a case study for engagement for Smart Data. It has over 15 million users and over 29 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. 

Since 2013, it has cost Open Banking £millions to achieve this success. Building on the foundations of Open Banking, the Smart Data schemes Open Energy and Perseus have been able to be in pilot phases for £3.5m. With these foundations laid, costs for smart data schemes should be reduced over time as we build on the existing investments and lessons learned through implementation.  

As a key learning from the success of Open Banking is to follow a use case driven approach, it is vital to note that identifying the user(s), their needs and developing use cases requires time, effort and resources. This can be a challenging aspect of a scheme to define but it is a core element as everything is built around the user needs. 

Another key learning from Open Banking, Open Energy, and Perseus is the importance of incorporating robust governance from the outset. Implementation costs will include secretariat functions for a governance body, relevant company time for stakeholder engagement and scoping requirements, and technical implementation. This will include team members from across an organisation, which may include innovation, technical, data, research, legal, communications/PR, and policy compliance teams. 

9. How can we build and maintain customer trust in a digital markets Smart Data scheme? For example, what responsibilities need to be considered for data owners and ATPs?

Obtaining consumer consent and customer trust is key for a digital market smart data scheme. It is important to note that the current methods for obtaining consent from a consumer may be ineffective or inefficient as laid out in our response to question 2. 

As mentioned in IB1’s Developing an energy smart data scheme: call for evidence response, please find our recommendations to build and maintain trust with core principles below:

• Governance mechanism is built to function flexibly: As digitalisation of the wider economy accelerates it is essential that governance adapts with 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. 
• Simple and Low Friction: IB1 recommends a simple and low friction option 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), to ensure an energy smart data scheme is aligned with national strategy.
• Interoperable IB1 strongly recommends taking a joined up approach which is interoperable with initiatives across the economy. IB1 suggests the solution defines relationships with cross-sector bodies to enable cross-sector interoperability.
• Agile, Flexible, and Scalable: IB1 suggests introducing a clear process for change management in this principle. As governance needs will likely change with time. This may include indication of how the list of permitted data use purposes will be maintained with additions and removals
• Transparent and Informative: IB1 strongly recommends that documentation is published openly, along with any accompanying processes, methodologies, financial, legal, operations and governance processes, as also suggested in our DSI consultation response. 
  • 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. 
• Inclusive by Design: IB1 urges the defined user journeys, messaging, terms, and customer support to be easy to use, transparent, and explained in a way that someone with a low technical reading comprehension can engage with. IB1 recommends building on open source, if not incorporated, there is a risk of inadvertently creating a monopoly.

• Secure by Design: IB1 encourages working with the National Protective Security Authority (NPSA) and National Cyber Security Centre (NCSC). IB1 would also recommend an adversarial analysis to be performed to see where security gaps may occur, and may affect the proposed architecture. A Smart Data scheme must avoid creating large targets for hackers where a compromise affects many consumers. 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. 
• IB1 recommends a focus on data rights: the same data will be used for many purposes. This means there will be multiple rights, based on purpose, carrying different legal, liability and related conditions. 

10. What common principles are needed to support the development of a digital markets smart data scheme and why?

We have recently introduced NOVA. A ‘NOVA-compliant’ solution embodies a coordinated structure of interoperable rules, governance, and infrastructure that connects actors across sectors while ensuring data flows are lawful, rights-based, and fit-for-purpose. NOVA stands for:

Networked

Data infrastructure must support modular, federated and interoperable participation across organisations, sectors, and jurisdictions.

• Modular: embody what is needed in a repeatable, cohesive and scalable manner
• Federated: support the coexistence of multiple platforms, protocols, and providers
• Interoperable: systems (not just technical, but also legal and operational) must be able to interact with low cost and friction, with harmonised approaches

Open

Data infrastructure must be grounded in open standards, API-enabled access, and transparent governance.

• Open standards: standards which are openly accessible and usable by anyone
• Open APIs: a web-addressable interface that enables machine-enabled data exchange
• Transparent governance: clear, accurate, and timely disclosure of policies, decisions, performance and impact

Verifiable

Data infrastructure and data access, usage, and governance must be assurable, rights-based and permissioned.

• Assurable: that the process of joining as a member, and of enabling data transfer and use can be audited, tracked and held to account
• Rights-based: data sharing is based on legal and related rights, codified in a contract, and enabled between assured members
• Permissioned: where relevant, or required by law, that permission or consent is given from the business or consumer, or that pre-authorised permission is determined by contract

Architecture

Data infrastructure must optimise for market access while enabling adaptive governance, whether market participants are data providers or data users, to ensure an open market.

• Market access: enable any Verifiable actor to enter the market
• Adaptive governance: define, iterate at market-relevant pace, enable, and facilitate scalable enforcement of, the rules
• Open market: ensure private sector, public-benefit, and national interests are addressed

11. Are there any tensions, overlaps, gaps or other features of the regulatory landscape in digital markets that the government should take into consideration?

As noted in IB1’s response to the Department for Science, Innovation, and Technology’s Technology Adoption Review, IB1 notes a key barrier to digital market and 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.

As the data sharing economy develops in a manner which is increasingly fluid and cross-sector there is an ongoing need for policy and regulatory development which horizon-scans, assesses, and defines responsibility for addressing different aspects of the regulatory landscape. Providing this form of policy and regulatory join-up presents essential support to the incentivising and de-risking of investment in strategic sectors. 

Additionally, it is essential to have consistency within sectors and to consider cross-sector interactions of digital market Smart Data schemes, especially across the pinchpoints where sectors meet and/or markets are increasingly ‘coupled’ (i.e. energy and transport; energy and water; energy and manufacturing). It is essential that a smart data scheme promotes interoperability and consistency across sectors, promoting a whole-system approach to digitalisation and net zero.

12. What data sharing initiatives already exist in digital markets that the government should be aware of when evaluating a Smart Data scheme in digital markets?

Open Banking

The Open Banking Standard, which is now implemented in over 95 jurisdictions and a £20B open market, placing the UK at the forefront of data sharing innovation. It uses financial-grade APIs within a strong, neutral governance framework to address data policy, licensing, privacy, liability and technical standards. 

Perseus

Icebreaker One’s Perseus Scheme (the ‘rule book’ defining how data is governed) is aiming to facilitate trusted, standardised, permissioned and secure data sharing across sectors. It addresses key challenges in data interoperability and trust by linking data systems through a cohesive Trust Framework, streamlining the process of collecting and reporting emissions data. By enabling interoperability between members, it enables SMEs to minimise their manual effort in measuring and reporting their GHG footprint, and matching their profile to green finance. 

It is being developed by a group including commercial businesses (incumbents and challengers), non-profits, public bodies and trade associations, with support from the UK Government.

Open Energy

Icebreaker One’s (IB1) UKRI Modernising Energy Data Access competition-winning programme Open Energy has identified and articulated the need to make it straightforward to find, access and share energy data. IB1 established an energy sector data sharing programme through sector engagement (convening 100s of organisations and 500+ public webinar attendees) and governance processes (80+ Steering and Advisory Groups members) to develop operational services for search and access control. These are are now live and market-facing through the Energy Sector Trust Framework and Schemes, IB1 created, designed and developed Open Energy https://ib1.org/energy/ to provide three services:

1. Community: an expert network of professionals – the IB1 Constellation
2. Governance: co-design of data sharing Schemes using our Icebreaking process
3. Trust Services: An Energy Sector Trust Framework for Scheme implementation, covering Open Data, commercial Shared Data with pre-authorised access controls, and commercial Shared Data where access requires end-user permission/consent. In addition, Trust Services deliver search and assurability services. 

Our approach helps drive the design, implementation and adoption of open standards to create assurable data flows between organisations. This enables assurable Open Data and pre-authorised Shared Data and ultimately builds confidence across the ecosystem.

As noted in IB1’s Developing an energy smart data scheme: call for evidence response,international examples of data sharing initiatives include (not all smart data schemes):

• India: https://indiastack.org/
• Government scale (not energy system) Taiwan – https://digi.taiwan.gov.tw/ MyData – https://www.ndc.gov.tw/en/nc_8455_34364 
• COVID tracking – data governance: https://academic.oup.com/policyandsociety/article/41/1/129/6513795
• See for examples of data ecosystems and learnings: https://cris.vtt.fi/en/publications/guidebook-data-ecosystems-for-smart-sustainable-cities 

13. What lessons should we bear in mind from Open Banking that would be helpful to consider when developing a digital markets Smart Data scheme?

It is essential that Open Banking is viewed holistically – an entity incorporating technical, communications, engagement, legal and ongoing governance arrangements – rather than a technical solution.

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 list service providers are available
• Providing member services 

As mentioned above, a key learning from the success of Open Banking is to follow a use case driven approach.

General lessons from national and international data sharing initiatives: 

• Incorporate governance at the outset. It is difficult to retroactively implement robust governance.
• Ensure governance is robust, participatory and responsive. It will be required to adapt to a full spectrum of social and environmental considerations shaping the operational landscape. A governance model must reflect the socio-technical nature of the energy sector, not just the technical side.
• Avoid putting too much emphasis on a technical solution  – An energy smart data scheme must equally address governance, user needs, business, social, legal, engagement and communications to be successfully implemented and ensure the solution is fit for purpose.
• Complexity and collective agreement across the industry – an initiative must recognise the complexity and changing nature of the energy industry.
• Cultural change and industry readiness – must understand and interact with the current data sharing culture within the energy companies, and consumers must be engaged to understand their value proposition. 
• Appropriately defining and governing the roles and responsibilities.
• Appropriate legal support and resourcing – a mechanism must develop the applicable data licences, and needs to be appropriately resourced to be able to do so. 

14. What lessons should the government bear in mind from the EU DMA and other Smart Data schemes in other jurisdictions including the establishment of Open Banking schemes around the world?

Icebreaker One Founder & CEO, Gavin Starks, co-chaired the development of the Open Banking Standard, co-chaired the UK Smart Data Council, and was founding CEO of the Open Data Institute. Since then Gavin has advised New Zealand and Canada on their implementation of Open Banking in their jurisdictions. 

In New Zealand in particular, the initial implementation of Open Banking was sector-led by Payments NZ. In 2017 and 2019, former Ministers of Commerce and Consumer Affairs wrote to New Zealand’s banks to encourage them to advance sector-led initiatives for open banking. From 29 August to 10 October 2024, the Ministry of Business, Innovation, and Employment consulted on policy settings for banking regulations under the Customer and Product Data Act, the regulations for which were then drafted in 2025. This shows the importance of both industry collaboration and regulatory mandate to drive sector-wide adoption.

15. Do you have any additional comments on any aspect of developing a digital markets Smart Data scheme that has not been covered elsewhere in this call for evidence?

None.

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. We have omitted questions which we did not answer.

Consultation response:

Icebreaker One (IB1) is a public-benefit non-profit working on data sharing and sustainability, convening organisations and governments to design market-scale solutions to make data work harder to deliver Net Zero. It creates and runs programmes to reduce barriers and costs to finding, accessing, using, and sharing data, which will ultimately reduce costs for consumers. Through the UKRI Modernising Energy Data Access competition, in collaboration with over 400 industry stakeholders, IB1 developed Open Energy which identified and articulated the need to make it straightforward to find, access and share energy data. Given IB1’s focus, we have responded to a number of the questions in the consultation. 

IB1 supports RIIO-ED3’s goals of moving away from gas infrastructure, toward renewables, and a more resilient grid. It is essential to have a joined-up approach and cross-sector thinking to achieve the size of impact outlined in the Industrial Strategy and The Clean Power 2030 Action Plan and unlock the widest range of potential benefits.

OVQ36. Do you agree with our position of not changing the Digitalisation licence condition?

IB1 supports digitalisation as key for energy sector decarbonisation, and required for the investment in flex services and the coordination between sectors who rely on energy to meet their decarbonisation targets (water, transportation, built environment, industry).

IB1 supports sector-wide convening and governance to ensure digitalisation happens in a coordinated manner and can enable ‘whole system solutions,’ as promoted in RIIO-ED2 and realise the subsequent cost savings. IB1 supports Ofgem to continue to promote and finance whole system digitalisation coordination in RIIO-ED3.

As there are many ongoing data sharing and data governance initiatives e.g. consumer consent solution, flexibility services, Data Sharing Infrastructure (DSI), which are currently in progress at different stages of development (definition, prototype, or pilot). Ofgem should not expect these programmes and underlying challenges the projects aim to solve to be resolved by the end of RIIO-ED3 (2031). Data sharing and data governance needs and subsequent solutions will evolve over time as we continue to electrify and connect the UK’s grid. As mentioned above, Ofgem needs to ensure ongoing governance and sector collaboration on data and digitalisation – reinforcement of this would be welcomed in addition to specific plans to expand/evolve data governance initiatives.

With the progress of the Data Sharing Infrastructure (DSI) programme, IB1 anticipates ‘Shared Data’ sharing will evolve and will inform the evolution of data best practice (DBP) guidance. In particular, as data sharing scales, the need to standardise and harmonise legal and technical approaches will become more pressing in order not to slow innovation and add unnecessary cost. IB1 recommends that DBP should include guidance around Shared Data within the triage processes and licensing decisions, highlighting the role of Shared Data Schemes (see OVQ37) to provide definitions that aid interoperability and maximise impact.  

OVQ37. Do you agree with our proposed approach to the DSI licence condition?

IB1 welcomes the energy industry collaborating and agreeing on data sharing. Through IB1’s Open Energy programme, we have co-designed the Energy Sector Trust Framework with sector stakeholders, including DNOs. Members are currently in the process of assuring their open data publication using the Assured Open Data Scheme governed by Open Energy. IB1 will continue to bring Open Energy learnings into the DSI development process. 

We encourage more clarity on what DSI ‘participation’ entails, including anticipated associated costs and funding. As mentioned in IB1’s response to DESNZ energy smart data scheme call for evidence, it is essential that a Trust Framework is viewed holistically – an entity incorporating technical, communications, engagement, legal and ongoing governance arrangements – rather than a technical solution. IB1 would recommend ‘participation’ in DSI is defined as being broader than operating data sharing nodes, including:

• In collaboration with stakeholders within and outside the energy sector:
  • Identifying and developing use cases
  • Designing technically- and legally- interoperable schemes
  • Agreeing, implementing and governing operational policies
  • Keeping in step with emerging trusted data approaches in other sectors of the economy, at home and abroad
• Articulating the amount of technical and non-technical work required for a Trust Framework 
• Articulating the role of consent and permissioning aligned with the 2025 Data (Use and Access) Act.
• Setting out the expected amount of resourcing including external and internal communications, executive support, legal resource, and skilled involvement in data governance and technical implementation

Our experience is based on establishing an energy sector data sharing programme through sector engagement (convening 100s of organisations and 500+ public webinar attendees) and governance processes (80+ Steering and Advisory Groups members) to develop operational services for search and access control. These are are now live and market-facing through the Energy Sector Trust Framework and Schemes, IB1 created, designed and developed Open Energy https://ib1.org/energy/ to provide three services:

1. Community: an expert network of professionals – the IB1 Constellation

2. Governance: co-design of data sharing Schemes using our Icebreaking process

3. Trust Services: An Energy Sector Trust Framework for Scheme implementation, covering Open Data, commercial Shared Data with pre-authorised access controls, and commercial Shared Data where access requires end-user permission/consent. In addition, Trust Services deliver search and assurability services. 

We recommend drawing upon this experience to both clearly and tightly define expectations for the DSI licence condition, and the roles of actors in the ecosystem (e.g. what is within the remit of regulators and code bodies, what could/should be precompetitive and what is open to commercial market competition).

• The scheme agreement [pdf, Google Doc for comment]
• The assurance levels:
  • Organisation assurance [specification]
  • Dataset assurance [specification]
  • Both specifications are also available in a Google Doc for comment

Please comment directly on the Google Docs if you are able, or email feedback to openenergy@ib1.org. Comments received before June 2 2025 will be considered for inclusion in the initial scheme implementation.

Background

Open Energy is proposing to add an Assured Open Data scheme to the Energy Sector Trust Framework (ESTF). The scheme has these main aims:

• Provide assurance to consumers of Open Data published by Members
• Enhance the quality, consistency, and reliability of published data
• Ensure Members comply with relevant data protection, privacy, and security regulations (e.g. members don’t publish any data subject to data protection regulations such as GDPR as Open Data under the scheme)
• Promote transparency and accountability within the data-sharing ecosystem.

The scheme incorporates updated organisational and dataset assurance levels based on feedback on the original levels that Icebreaker One announced in September 2023. These levels are already being used, for example by Open Energy members SSEN-D on their data portal.

Joining the scheme will be free to ESTF members. In order to assert the assurance levels members must execute the scheme agreement that sets out their commitments, and liabilities should they fail to meet them.

If you have any questions about our submission or require clarifications please do not hesitate to contact us via policy@ib1.org. We have omitted questions which we did not answer.

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:

1. 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.
2. 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).
3. 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/ 

If you have any questions about our submission, please contact us at policy@ib1.org. We have omitted questions which we did not answer.

Call for feedback response:

1. What areas of focus can be accelerated by Digitalisation to support a clean power system? 

Icebreaker One (IB1) is a non-profit working on data sharing and sustainability, convening organisations and governments to design market-scale solutions to make data work harder to deliver Net Zero. We create and run programmes to reduce barriers and costs to finding, accessing, using, and sharing data, which will ultimately reduce costs for consumers.

As noted in IB1’s response to DBT’s Invest 2035 consultation, achieving net zero and delivering the British Energy Security Strategy means addressing all aspects of the energy trilemma: affordability, security, and sustainability. The latest CBI Economics report found the “net zero economy is a powerhouse of job creation and economic expansion with 10.1% growth in the total economic value supported by the net zero economy since 2023”. We need to deliver a flexible, decentralised, and digitalised energy system that is critical to Net Zero. 

Energy data is currently hard to access (it is not ‘digital ready’ and requires multiple bilateral requests and contracts). It is disconnected from related sectors. An open standards-based, transparent, market-wide framework can allow rapid scalability of secure access to data. A framework for trusted data sharing will unlock the increasing variety, veracity and volume of energy data to system participants to adapt, evolve and create services that enable better network management, and respond to rapidly changing patterns of energy supply and demand.

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 milestones, negative incentives, corporate capture, unintended monopoly positions, and data misuse.

We recommend digitalisation and data sharing builds upon prior art – simple and low friction options which build 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), and taking a joined up approach to be interoperable with initiatives across the economy.

See our Open Energy use cases for examples of the benefits and barriers to data sharing with the energy sector https://ib1.org/energy/reports/ 

2. What specific activities are needed in each of the five capability areas to achieve our clean power? 

Governance and operating model

Addressing governance, user needs, business, social, legal, engagement and communications is critical to ensure any solutions are fit for purpose, and can be adopted by the market. We observe that technical-led programmes tend to fail to gain traction or deliver against material user needs. See IB1 governance standard operating procedures here: https://ib1.org/sops/governance-schemes/ 

Governance must address five pillars 

1. User needs & impact: Identify user needs, explore / prioritise use cases, and mapping the data value chain
2. Technical: Agree data and metadata standards, operational technical systems
3. Licensing & Legal: standard legal data licences, apply data sensitivity classes to datasets identified
4. Engagement & Communications: Address user needs, experiences, and create awareness and engagement for the programme
5. Policy: Identify potential policy implications, blockers, or interventions

IB1 encourages cross-sector collaboration and learning wherever possible. We recommend engaging with cross sector stakeholders (i.e. water, transportation, local authorities, etc) and working with citizen advocacy groups to learn from best practices, ensure guidance is consistent for cross sector use cases (hydrogen, electric vehicles, electrifying public transport, etc), and understands the impact of digitalisation on different socio-economic stakeholder groups.

As noted in IB1’s response to Ofgem’s DSI governance consultation, IB1 suggests there is clear guidance as to how rules are established, overseen, enforced, and changed. These must be explicit and transparently codified roles of the governance body and must also detail under what circumstances any of these roles can be delegated and/or subcontracted to specialists.

Accordingly, we recommend that the roles include definition of processes and/or rules for the establishment, oversight, enforcement, and change of:

• Stakeholder mapping, engagement and representation
• Goal setting
• Defining success criteria (across technical, socio-economic, and environmental domains)
• Monitoring, reporting, and verification (MRV)
• Change management
• Communications
• Dispute resolution
• Liability and redress
• Any formal responsibilities towards meeting cross-economy policy goals such as:
  • Net zero
  • Industrial strategy
  • Social policy

We further recommend that roles are included to oversee – where not already covered by another body in the broader environment – the definition of processes and/or rules for the establishment, oversight, enforcement, and change of:

• Data rights
• Adjacent agreements (e.g. membership contracts / terms of use)
• Guidelines (e.g. antitrust, fairness, transparency, publishing)

Finally, we suggest that the governance body should have an active and transparent role in defining formal and informal relationships with adjacent bodies in the energy sector and beyond. This role may include jointly establishing and maintaining:

• Channels of communication 
• Obligations on reporting or information sharing
• Formal processes and roles for engagement (e.g. assignation of ‘observer status’ in certain governance fora)
• Approaches to sharing and/or allocating roles when approaching shared issues 
• Appropriate accountability structures
• Approaches to reduce forum proliferation (and ensuring associated fair access to governance fora for smaller organisations with less resource)
• Approaches to contributing or responding to cross-sectoral policy and regulatory developments in a joined up manner.

The suggested roles above imply a set of associated responsibilities which are outlined in the sub-bullets. Many of these responsibilities are likely to constitute oversight rather than design/delivery, allowing for subcontracting arrangements to take place where required. We suggest that a governance body also holds responsibilities for the oversight of:

• User needs identification, testing, and convening
• Assessing and measuring impact across socio-economic, environmental, and technical domains
• Where impacts are undesirable, performing impact mitigation 
• Ensuring cohesion (of procedural, legal, technical approaches)

Weaving through all our suggestions is the principle that key roles and responsibilities explicitly include reference to the wider socio-technical landscape. We suggest that codifying these responsibilities would provide an improved balance between technical, social, and operational elements of governance. While not all areas of responsibility need to be undertaken directly by a proposed governance body (e.g. it may be possible to subcontract an appropriate body to support stakeholder engagement) we strongly suggest that the following (non-exhaustive) points would benefit from more formalised oversight, governance integration, and appropriate resourcing : 

• Data rights and surrounding legal structures governing the exchange of data and associated intellectual property
• Stakeholder engagement and communications
• Cross-sector, policy and regulatory input/coordination (including social, economic, and environmental factors)

Applications

Applications must be designed with governability as a requirement. The data governance in play will affect or even mandate the way functions such as access control, permissions, licensing, data catalogue publication, metadata provision, record-keeping and logging are implemented. These requirements can be fundamental to systems architecture choices, making them  much harder to retrofit than to design in from the outset. 

The technical infrastructure advisory group exists to collaboratively define, agree on and publish the requirements for applications under governance

Integration

Regarding data sharing, we recommend considering:

• Taking an open standards-based, transparent, market-wide framework approach to allow for the rapid scalability of secure access to data
  • Trust Framework: identity management, contracting, adoption and operation of Schemes, common principles (see more https://ib1.org/definitions/trust-framework/)
  • Scheme: rulebook for specific use cases (technical, legal, policy, operational) (see  https://ib1.org/definitions/scheme/)
• Mandating specific technical security standards. These must be agile to respond to changing security requirements and threats.
  • An example is FAPI, which mandates specific security choices with sufficient implementation flexibility to be practical in most environments.
  • Open ID
  • OAuth

• Using available web standards developers are familiar with to build 
• Making APIs explainable to machines (i.e. Open API spec when describing an API being registered on the registry – this can generate the code in most languages)
• Data access. There can be an assumption that the data holder controls data access, and while technically they do, in a scheme they sign up to rules that may require them to release the data. They therefore cannot make ad hoc decisions that give access to a data user (company 1) but not give access to another data user (company 2) who fit the same criteria within the scheme. 
• Describing data access rules as part of specification for data sharing. Therefore participants can understand on what terms they get the data. IB1 recommends the governance function provides oversight to ensure it is not abused (e.g. anticompetitive practices)
• Mandatory access control, which should be applied equally (unless otherwise noted)

• Defining data standards that align with common requirements across schemes, such as for data catalogues, licence representations, permission, assurance or provenance. 
• Defining metadata standards – and publishing them openly. As mentioned in IB1’s response to Ofgem’s Updates to data best practice guidance, we supported requiring the use of Dublin Core as a Core Standard. We agreed with Ofgem’s recommendation for publishing metadata using the Dublin Core standard, but we also suggested further refining it to specify the Dublin Core-based Data Catalog Vocabulary (DCAT), which is supported by the main data catalogue platforms and is the metadata standard adopted for all EU public sector data publication.
• Considering how an interoperable identity mechanism may be possible across different schemes. We think this should not be a centralised identity, but a mechanism which can enable cross scheme identity verification. 
• Building on the work around machine readable licensing terms
• Developing standards on monitoring, auditing, logging (tools which can look across schemes make sure data is not leaking out of them)
• Starting with conceptual alignment for interoperability (i.e. data field and protocol alignment) and then moving on to technical alignment

Physical components 

We note there is a risk of unequal access to the benefits of digitalisation and potential smart services if we do not fully understand and address the challenges known to exist in the physical infrastructure within the energy system including smart meters. Smart metering reporting can be inaccurate, offline, and in 2024 Energy UK confirmed there is a regional divide because of the way meters send usage data back to suppliers. Acknowledging and addressing this will reduce the risk of baking in non-equal access to the benefits of digitalisation and smart services, and may unintentionally miss out key beneficiaries. 

3. How can we ensure effective governance and collaboration across the sector to leverage benefits of digitalisation? 

Open Energy is an example of an energy sector data sharing programme with a governance process and sector engagement. Through IB1’s UKRI Modernising Energy Data Access competition-winning programme Open Energy, we identified and articulated the need to make it straightforward to find, access and share energy data. Through three phases, we convened 100s of organisations, 500+ public webinar attendees, and over 80 Steering and Advisory Group members to develop operational services for search and access control that are now live and market-facing, and have set the foundations for an Energy Trust Framework. 

Open Energy makes it easy to search (via https://openenergy.org.uk), discover, access and securely share energy data using a Trust Framework and any Schemes which are built within the Trust Framework context. It covers Open Data, commercial Shared Data with pre-authorised access controls, and commercial Shared Data where access requires end-user permission/consent.

As mentioned in our response to Ofgem’s consultation on DSI governance we suggested that Open Energy be formally considered as a vehicle for the governance of the Trust Framework node. Open Energy was funded by public money and has been specifically developed for this purpose using a combination of radically transparent methods of open working, extensive consultation with stakeholders, and the input of specific domain expertise from energy industry, academic, and Open Banking specialists. IB1 has already been involved in the DSI as the governance advisory partner, and is involved in the MVP through inputting into the pilot development, and use case exploration. It already has DNO and energy sector members. 

4. Are there any key areas of consideration missing from the capability requirements? 

Key areas of consideration:

• Drafting design principles which can be aligned around – and consistent with DSI and the energy smart data scheme (DESNZ) proposed principles
• Legal and licensing – including standard legal data licences, and applying data sensitivity classes to datasets identified
• Policy: Identifying potential policy implications, blockers, or interventions
• Interoperability: IB1 strongly recommends taking a joined up approach which is interoperable with initiatives across the economy. We suggest the solution define relationships with adjacent bodies in the energy sector and beyond to enable cross sector interoperability.
• An avenue to engage with security stakeholders – we recommend working closely with NPSA and NCSC to ensure their feedback is incorporated.
• Openly published documentation – financial, legal, operational to ensure it is clear what is required to become a scheme participant.
• Clear area where strategy and direction are discussed and implemented. Currently the use of data for strategic direction is not explicit. See top layer of the ArchiMate specification (fundamental to DSI design approach)

5. What existing projects and activities are supporting, or acting contrary to delivering these capabilities? 

Current existing projects supporting the above capabilities:

Open Energy is an example of an energy sector data sharing programme with a governance process and sector engagement (detailed in question 3)

Data Sharing Infrastructure

A DSI is a collection of open-source software packages that enables data sharing. As an open-source solution, the burden of take-up and use of the DSI for sector participants is lessened compared to use of proprietary technologies. However, the end design (once established) of a DSI may incorporate commonly used and generally available proprietary software.

Credo+

A digital twin platform for climate change adaptation that improves system-wide resilience across infrastructure networks.

6. Are there any digitalisation related activities or initiatives needed to support the transition to clean power that you think are strategically important? 

Open Energy https://ib1.org/energy/ provides three services:

1. Community: an expert network of professionals – the IB1 Constellation

2. Governance: co-design of data sharing Schemes using our Icebreaking process

3. Trust Services: Search services and Energy Sector Trust Framework for Scheme implementation

Trust in data is essential to investment and use. Our approach helps drive the design, implementation and adoption of open standards to create assurable data flows between organisations. This enables verifiable Open Data and pre-authorised Shared Data (including smart data where consent/permission is required).

As the data sharing economy develops in a manner which is increasingly fluid and cross-sector there is an ongoing need for policy and regulatory development which horizon-scans, assesses, and defines responsibility for addressing different aspects of the regulatory landscape. Providing this form of policy and regulatory join-up presents essential support to the incentivising and de-risking of investment in strategic sectors. 

Other initiatives to be aware of include:

• See evolving smart energy data scheme work (run by the Department of Energy Security & Net Zero – consultation closes 10 March)
• Department for Energy Security & Net Zero’s “Mission Control” unit
• The Data (Use and Access) bill
• Other smart data schemes across the economy, including Perseus which is  a cross-sector Scheme that aims to help unlock access to finance to reduce emissions faster by automating sustainability reporting for every SME business in the UK. The Perseus Pilot launched in November 2024 https://ib1.org/perseus/ 
• Project IRENES – which includes information on renewable electricity generation potentials and a wide variety of land use or environmental factors that are relevant to siting decisions.
• ESC local energy planning method for translating national Net Zero targets into local energy system action with plans that are collaborative, data-driven and cost-effective.
• LF (Linux Foundation) Energy – Open Source for the digital energy transition
• Invest 2035: the UK’s modern industrial strategy

7. Of the activities or initiatives provided in answer to question six, what outcome and capability does that relate to?

Open Energy primarily relates to governance and operating model, but as detailed above has an impact on all of the outcomes and capabilities.

If you have any questions please do not hesitate to contact us via policy@ib1.org.

Call for evidence response:

1. What are your views on the benefits of an energy smart data scheme? This might include (but is not limited to) benefits to customers, decarbonisation, the economy and wider society

Icebreaker One (IB1) is a non-profit working on data sharing and sustainability, convening organisations and governments to design market-scale solutions to make data work harder to deliver Net Zero. IB1 creates and runs programmes to reduce barriers and costs to finding, accessing, using, and sharing data, which will ultimately reduce costs for consumers.

Supporting a Net Zero economy

The economic case for improved data sharing is compelling. Research demonstrates significant return on investment:

• Research from the Open Data Institute showed open data (either fully open or shared) delivers overall economic growth
• Across the EU, re-use of open data to create new services and products was valued at €22bn in the public sector alone in 2020, with €1.7bn in cost savings (€262m in the UK). 

The Clean Power Plan supports the growth mission set out in the Industrial Strategy to deliver economic growth in every part of the country and improve the lives of Britain’s workforce. Clean energy industries represent a substantial potential growth area, with 90% of global GDP covered by net zero targets. The latest CBI Economics report found the “net zero economy is a powerhouse of job creation and economic expansion with 10.1% growth in the total economic value supported by the net zero economy since 2023”.

The shift to a clean power system by 2030 forms the backbone of the transition to net zero and there is measurable importance in having a joined up approach to unlock the widest range of potential benefits during this shift. Cross-sector thinking is required to achieve the size of impact that the Industrial Strategy and The Clean Power Plan have outlined.  

Meeting the UK’s Net Zero goals

Achieving net zero and delivering the British Energy Security Strategy means addressing all aspects of the energy trilemma: affordability, security, and sustainability. The financial, energy and transport sectors are critical first priorities as the UK transitions to a decentralised, green energy future that can be reliably supported by the financial sector. Unlocking access to data through Smart Data schemes will serve to enable, and derisk, these priorities. The UK’s Net Zero goals require continuous information flows throughout project lifecycles, and achieving this will require data-sharing at a scale for decision making and incentivising ‘green’ investment. 

A transition away from fossil fuels to a clean energy system will provide investment, employment opportunities, and help meet the UK’s climate and nature targets. Rebuilding natural infrastructure whilst simultaneously building the new energy infrastructure needed, this could come in the form of creating new wildlife corridors alongside or underneath linear energy infrastructure. 

Integrating systems data 

An energy smart data scheme needs to address broader systems data to deliver a flexible, decentralised, and digitalised energy system that is critical to Net Zero. The UK’s energy system will be increasingly challenged by a growing renewable mix, shifting and unpredictable demand on the grid, and the emergence of widely distributed prosumer and demand response energy resources. For example, currently energy is being wasted due to there not being enough capacity to transport or store electricity produced by wind and solar farms. An energy smart data scheme allows for space for thinking between the UK’s industrial strategy, and net zero goals, and growth areas. 

The Seventh Carbon Budget (2038-2042) highlights the role of surface transport and energy supply in achieving the UK’s emissions reductions targets, which will require a 23.2% reduction in energy sector emissions and a 26.5% reduction in transport emissions over the period 2023 – 2037.  To meet these goals, an energy smart data scheme must facilitate the decarbonisation of transport through electrification and demand-side flexibility in energy supply. Smart meter insights can optimise grid integration for EVs, improve energy efficiency in buildings, and accelerate the transition to decentralised, low-carbon power systems, ensuring a resilient and cost-effective net-zero pathway.

A framework for trusted data sharing will unlock the increasing variety, veracity and volume of energy data to system participants to adapt, evolve and create services that enable better network management, and respond to rapidly changing patterns of energy supply and demand.

Cross sector collaboration

It is essential there is cross-sector collaboration, joined up thinking between the UK’s industrial strategy, approach and net zero goals, and growth areas to enable shared best practices. This requires not only better data sharing for the purposes of planning, but also better cross-sector communication, including between departments, regulators, agencies, industry bodies, and industry. 

Specific customer impact and benefits will vary depending on the identified and prioritised use case. IB1 delivers business-driven use cases that can scale efficiently and securely. 

Benefits of taking use case driven approach:

Through IB1 programmes and years of expertise, 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:

1. 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.
2. 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).
3. 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. IB1 suggests defining relationships with adjacent bodies in the energy sector and beyond to enable cross sector interoperability.

Examples: energy data sharing schemes 

Example: Energy Sector Data Sharing Programme – Open Energy

Through Icebreaker One’s (IB1) UKRI Modernising Energy Data Access competition-winning programme Open Energy, IB1 identified and articulated the need to make it straightforward to find, access and share energy data. Through three phases, IB1 convened 100s of organisations, 500+ public webinar attendees, and over 80 Steering and Advisory Group members to develop operational services for search and access control that are now live and market-facing, and have set the foundations for an Energy Trust Framework. 

Open Energy makes it easy to search (via https://openenergy.org.uk), discover, access and securely share energy data using a Trust Framework and any Schemes which are built within the Trust Framework context. It covers Open Data, commercial Shared Data with pre-authorised access controls, and commercial Shared Data where access requires end-user permission/consent.

See relevant energy use cases in question 14.

Example: Cross-sector data sharing programme – Perseus 

Icebreaker One convenes the cross-sector Perseus Scheme (ib1.org/perseus) to enable automated carbon emissions reporting for every SME in the UK. It creates the rules and processes that make automated reporting possible to enable products and services such as accounting platforms, emissions calculators, and reporting software to be developed that deliver higher-quality emissions data at scale. Perseus convenes hundreds of cross-sector organisations to ensure user needs and barriers from across the supply chains are captured and incorporated into the Scheme. 

2. What can we learn from Open Banking that would be helpful to consider when developing an energy smart data scheme? This might include (but is not limited to): phasing, structure, funding, participation, growth, implementation or governance.

Open Banking is a case study for engagement for Smart Data. 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 – an entity incorporating technical, communications, engagement, legal and ongoing governance arrangements – rather than a technical solution.

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 list service providers are available
• Providing member services 

A key learning from the success of Open Banking is to follow a use case driven approach (see question 1 for benefits). See more information on the development of UK Open Banking here: https://dgen.net/0/2018/04/04/report-development-of-uk-open-banking/ 

3. What can we learn from international examples of Smart Data schemes for our approach in the energy sector? 

International examples of data sharing initiatives (not all smart data schemes)

• India: https://indiastack.org/
• Government scale (not energy system) Taiwan – https://digi.taiwan.gov.tw/ MyData – https://www.ndc.gov.tw/en/nc_8455_34364 
• COVID tracking – data governance: https://academic.oup.com/policyandsociety/article/41/1/129/6513795
• See for examples of data ecosystems and learnings: https://cris.vtt.fi/en/publications/guidebook-data-ecosystems-for-smart-sustainable-cities 

General lessons from national and international data sharing initiatives: 

• Incorporate governance at the outset. It is difficult to retroactively implement robust governance.
• Ensure governance is robust, participatory and responsive. It will be required to adapt to a full spectrum of social and environmental considerations shaping the operational landscape. A governance model must reflect the socio-technical nature of the energy sector, not just the technical side.
  • IB1 have created scheme governance standard operating procedures: https://ib1.org/sops/governance-schemes/ 
• Avoid putting too much emphasis on a technical solution  – An energy smart data scheme must equally address governance, user needs, business, social, legal, engagement and communications to be successfully implemented and ensure the solution is fit for purpose.
• Complexity and collective agreement across the industry – an initiative must recognise the complexity and changing nature of the energy industry.
• Cultural change and industry readiness – must understand and interact with the current data sharing culture within the energy companies, and consumers must be engaged to understand their value proposition. 
• Appropriately defining and governing the roles and responsibilities.
• Appropriate legal support and resourcing – a mechanism must develop the applicable data licences, and needs to be appropriately resourced to be able to do so. 

4. What additional value could an energy smart data scheme deliver alongside existing data sharing initiatives? Please include your views on how an energy smart data scheme might support or hinder existing data sharing and digitalisation initiatives.

Energy data is currently hard to access (it is not ‘digital ready’ and requires multiple bilateral requests and contracts). It is disconnected from related sectors. An open standards-based, transparent, market-wide framework can allow rapid scalability of secure access to data. 

As mentioned in IB1’s response to the Department for Business and Trade’s Invest 2035 consultation, it is essential to have consistency within sectors and across the pinchpoints where sectors meet and/or markets are increasingly ‘coupled’ (i.e. energy and transport; energy and water; energy and manufacturing). It is essential that an energy smart data scheme promotes interoperability and consistency across sectors, promoting a whole-system approach to digitalisation and net zero.

In 2021, IB1 was commissioned by BEIS (DESNZ) to report on How Smart Data can help unlock a Green Economy. It explored a representative cross-section of use cases, and prioritised where impact (environmental and economic) meets achievability (lower level of regulatory and technical complexity). Key learnings include:

Smart Data becomes effective when it is connected

In terms of prioritisation of sector, use cases requiring cross-sector interoperability and cohesion offer the greatest immediate ability to create impact, with a manageable degree of complexity involved in rollout. These use cases support private sector growth and require achievable government intervention, allowing green growth and environmental goals to be met.

Cross-sector engagement is essential

Every sector has something to offer – and cross-sector engagement is necessary in order to achieve policy aims. 

5. What energy customer needs could potentially be addressed by an energy smart data scheme? 

As mentioned in question 1 and 2, user and customer needs should be identified through a robust governance process which can understand, process, and define use cases with relevant stakeholders. In IB1’s Scheme governance (standard operating procedures), IB1 emphasises the importance of having a user needs & impact advisory group which explores, prioritises, and works through use cases (including identifying users, their needs, and mapping data value chains). This process allows for the development of business, value, and impact cases and their impact on policy, businesses, and financial instruments. 

As mentioned in question 1 and 14, IB1 has identified and documented a wide range of use cases and benefits associated with trusted energy data sharing.

As noted in the Clean Power 2030 Action Plan, central to delivering decarbonisation in the energy system is ensuring it benefits consumers and businesses. The UK needs to protect and empower consumers, provide stability for businesses and ensure confidence for investors. 

6. Which customer groups might benefit most from an energy smart data scheme and why? 

While all consumers should benefit from having a lower cost, efficient energy system which is resilient to geopolitical shocks due to an energy smart data scheme and improved data sharing. Those who will benefit the most from the system efficiencies and energy price cost reduction will be low-income households who are unable to make ‘green’ investment on their own due to the upfront costs (i.e. solar panels / heat pumps / charging / EV ownership). 

7. What specific challenges or barriers to participation might be faced by particular customer groups?

As noted in IB1’s response to the Department for Science, Innovation, and Technology’s Technology Adoption Review, 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. 

A robust governance includes having representatives from consumer advocacy/rights groups is essential to ensure any work identifies and collaboratively works through any barriers. IB1 has suggested addressing the following comments on inclusivity in our response to Ofgem’s Consumer Consent Consultation: 

• Recommend support for other languages (Welsh, other languages used in the UK)
• Strongly suggest considering how the any solution leads to digital exclusion, and compound exclusion
• Encourage a measurement of diversity which will be considered with design, including disabilities, excluded from the Equalities Act like dyslexia, or options for text dictation.

8. How can we build and maintain customer trust in an energy smart data scheme? 

Trust and Assurance gives confidence both to people inside companies that they are allowed to share data externally, as well as those externally knowing that they have permission and confidence in what is being supplied.

IB1 supports a robust governance process for the energy sector which is essential to  develop own customer-facing values and business propositions and get them out into the market, anchored on principles of data rights, of machine interoperability and of fair value exchange: reciprocity is at the heart of all of this work. 

In response to Ofgem’s Consumer Consent Solution, IB1 suggested including an element of trust to the design principles. As mentioned in the Data Sharing in a Digital Future consultation, there is a lack of trust in energy companies by consumers. Trust is key for obtaining consent. There may already be ‘trust’ in an entity if there is already an existing contractual relationship with suppliers (rather than introducing a new body).

9. What measures should be considered to ensure customers are protected?

IB1 recommends following the design principles in question 19, and considering how an Open Banking decentralised approach increases reliability through the use of an inherently scalable and resilient technical architecture, and security by eliminating a single big target, which would be attractive for hackers.

Example:

In our response to Ofgem’s Consumer Consent Solution, IB1 proposed how a solution could be modelled on Open Banking:

Each Supplier would provide a consent hub within their existing App and account management website. The implementation of this consent hub would be chosen by the supplier, who are free to develop their own, collaborate on an open source implementation, or buy in a solution managed by one of many software vendors.

When a consumer is asked to provide meter data and consent, the service uses a centrally maintained list of Suppliers, and asks the user to choose their Supplier. Then, using standard protocols in a technical solution using the architectural principles from Open Banking, the service asks the user to authenticate with their Supplier. After the user gives consent, the Supplier returns a token to the service to access meter data. Meter data can be fetched via the Supplier’s service, or direct from Smart DCC using the token created by the Supplier.

When a consumer changes Supplier, a list of consents would be passed to the winning Supplier, who would then give the user the opportunity to give the same consents to maintain their connections to the services they use.

10. What are the potential incentives and barriers for established energy market actors to provide access to customer data (e.g. operational, commercial, legal)? What interventions might be necessary? 

As mentioned in question 1, 2, and 5, incentives, barriers, and benefits should be identified through a robust governance process which can understand, process, and define use cases with relevant stakeholders including incentives and barriers.

As mentioned in IB1’s response to Ofgem’s Consumer Consent consultation, the current methods for obtaining consent and permission from a consumer may be ineffective or inefficient due to:

• Lack of transparency in obtaining consent – e.g. overly legalistic wording, items hidden in small print, lack of clarity around the full range of partners data will be shared with and/or for what purpose(s).
• Individual/household dilemma – consent for data sharing pertaining to a multi-occupancy or shared household of people is obtained from a single individual (there may also be a gender bias here if the account holders tend to be male) who may or may not actually live at that address (eg landlord who pays bills) – there is no mechanism to ensure household members are consulted.
• Revoking or changing consent – it is often easy to give consent (e.g. automatic pop-up) but much harder to change or revoke consent (e.g. requires a log in, hidden in a long settings menu, not available by non-digital means) – this requires much more transparency and an easy process.
• Lack of trust – as mentioned in the consultation, trust is key for obtaining consent. 
• Linked services – Lack of understanding about the impacts of giving, changing, or revoking consent for services that may be linked (e.g. reliant on data flows) but potentially operated by different companies. For example, consumers may not understand the impact of rejecting access to 30 minute consumption data on access to smart products and services.

IB1 recommends:

• A decentralised model, which aligns with the approach taken by Open Banking, and the architectural principles of the Data Sharing Infrastructure for ease of access and protection 
• A robust governance which allows for collective agreement on standards and legal agreements 
• Working closely with NPSA and NCSC to ensure their feedback is incorporated.
• Designing for integration and interoperability with cross-sector data sharing

11. What are the barriers currently faced by third parties in accessing customer data? What potential barriers might be faced by authorised third parties in offering increased or improved services to customers through a Smart Data scheme?

See question 10 for listed barriers and recommendations. 

12. What customer groups should be included in an energy smart data scheme and why? 

No comment. 

13. What aspects of the GB energy mix should be included in an energy smart data scheme and why?

IB1 would also like to understand why any aspects of the GB energy mix may be excluded from an energy smart data scheme. IB1 would recommend this be explored through potential use cases and understanding what is trying to be achieved before excluding any part of the system in the design phase. 

14. What are the potential use cases for an energy smart data scheme? Where relevant, please identify target customer groups or geographic region they would cover.

As mentioned in question 1 and 5, IB1 has identified and documented a wide range of use cases and benefits associated with trusted energy data sharing. Many of them highlight the data sources identified on page 23 of the call for evidence.

Identifying, expanding upon, and prioritising use cases can meet a wider opportunity to transform the energy sector. From IB1’s research, IB1 sees the biggest opportunity for energy data is for strategic planning at national and local level to advance the UK’s industrial and net zero strategies. As part of our research, IB1 have found the need for more granular data, which is very useful for capacity management on the network, load modelling, and flexibility.Choosing the right collaboratively defined key use case can be an opportunity for new jobs and increased system efficiency and resilience.

Identified use cases by data sources (pg 23)

Generation:

A major barrier is around timely and easy data sharing to facilitate predictable planning, understanding current, planned, and required headroom capacity, and to clear the backlog of planning requests to approve more net zero energy sources. 

This includes the need for a trusted way to securely share data, and ensure national infrastructure security. IB1 partnered with SSEN-Transmission, Olsights, Mapstand, SGN, and National Grid on a Strategic Innovation Fund programme REACT to address current planning and future planning for generation siting. See the Discovery Phase report, and the Alpha Phase report.

Data sharing can also be used to better understand how to maintain the assets already in place. IB1, SSEN-Transmission, IBM, and Palantir on a Strategic Innovation Fund programme, NIMBUS, which focussed on granular weather data and network innovation to build for sustainability. See the Discovery Phase report and the Alpha Phase report.

Suppliers:

Through Open Energy IB1 worked with suppliers, a few key barriers identified are understood to be challenges faced by many suppliers, including:

• Inconsistency of data format, structure and storage 
• Poor data flow between departments 
• Data/model duplication because of limited cross-sector collaboration
• Reluctance to publish incomplete or imperfect data.

Small scale assets:

In our Open Energy Future of heating –  Residential Property Developer use case, IB1 focussed on supporting residential property developers, or consultants operating on their behalf, by facilitating and streamlining access to essential data. For small scale assets, data sharing is needed between DNOs, suppliers, smart meters to understand the demand on headroom capacity 

Properties:

In previous research which touched on individual household properties, IB1 would recommend considering if a selected use case could be solvable through the use of aggregated data rather than individual. The electricity network has physical infrastructure in the Low Voltage feeder (LV feeder) that can be used to aggregate data down to a few households, and provide a simple way to provide highly granular but anonymised data (this is not the case with the gas network, but the gas network can use the same aggregation point when gas and electricity meters are connected together).

IB1 note that smart meters can be found in non-domestic and domestic properties, and Perseus is addressing how a smart data scheme could be implemented to connect green financial loans for SMEs. 

Vehicles

As part of our Open Energy work IB1 have identified, prioritised, and documented two EV use cases. A key aspect is that at least 33% of households do not have a garage or private drive where they could easily charge their own vehicle. This affects lower income households disproportionately, as on-street charging generally has a higher cost than household tariffs, particularly households who also have access to time-in-use (static or dynamic) tariffs that are most suited to EV charging. 

• Electric Vehicles (EV) On-Street Charge Points
• Electric Vehicles (EV) DNO Demand Management

People and communities:

As mentioned in properties, IB1 would recommend considering if a selected use case could be solvable through the use of aggregated data rather than individual.

Local authorities:

As part of our Open Energy programme, it was surfaced that a common challenging issue for Local Authorities implementing their Local Energy Plans is to be able to understand whether or not plans to install these new Low Carbon Technologies would be achievable without Distribution Network reinforcement build being required. See our Local Authority LCT decision making use case (also applicable in vehicle category).

Financial services:

IB1’s flagship programme Perseus will automate access to assurable SME electricity data, so they will be able to see the emissions from their energy use and share it, via reporting solutions, to their banks to unlock green finance (2023 report). This will result in a viable connection between the financial economy and real economy to enable net zero impact in a scalable and assurable manner. When investors have trusted assurable data they are empowered to prioritise investment where needed for maximum net zero impact. 

This has crossover with financing energy efficiency, use of renewable energy,  renewable generation, flexibility services (i.e. solar panel batteries). 

As noted in question 18, there is a risk of unequal access to smart services if we do not address the challenges known to exist in smart meters, known barriers to access, and any other infrastructure collecting the data which will be used in the scheme.

For example, smart metering reporting can be inaccurate, offline, and in 2024 Energy UK confirmed there is a regional divide because of the way meters send usage data back to suppliers. Acknowledging and addressing this will reduce the risk of baking in non-equal access to smart services which arise from a smart data scheme. 

IB1 recognises the focus is on energy data, however, there is a growing potential for a number of use cases with the water industry such as leakage identification and resilience planning. This is also key to understanding the country’s resources, and can aid planning for a number of reasons (hydrogen, CCS, local authority, housing development) and fits into existing regulation and regeneration policies. IB1 recommends working with key regulators such as DEFRA, the Environment Agency, Ofwat, and Ofgem to share existing knowledge and develop best practices. 

15. What datasets should be included in an energy smart data scheme and why? Please consider all types of energy data (e.g. electricity, gas), including which data should be a minimum requirement for any Smart Data use case and which data might be challenging to include.

Part of the use case identification process should include identifying datasets, as seen in our use cases documented in question 14. IB1 strongly recommends following a use case driven approach rather than starting with identified datasets to be released to ensure organisational interest and incentives. IB1 encourages cross-sector collaboration and working on cross-sector use cases (hydrogen, electric vehicles, electrifying public transport, etc). 

16. What opportunities might there be to take advantage of AI and machine learning solutions in an energy smart data scheme? Please consider any additional governance and protections required to mitigate any risks.

As noted in IB1’s response to Ofgem’s AI in the energy sector guidance consultation: 

IB1 encourages cross-sector collaboration and learning wherever possible. IB1 recommends engaging with cross sector (i.e. water, transportation, local authorities, etc) and working with citizen advocacy groups to learn from best practices, ensure guidance is consistent for cross sector use cases (hydrogen, electric vehicles, electrifying public transport, etc), and understands the impact of AI guidance on different socio-economic stakeholder groups.

AI must be designed to mitigate bias and discrimination, ensuring fair access to economic opportunities, financial services, and public resources. IB1 advocates strongly for:

1. AI governance to integrate with developments in data governance, both within the energy sector and in the cross-economic space (e.g. Smart Data Roadmap, approaches to consent or permission). 

IB1 believes it is important for data governance to establish principles, structures, roles and responsibilities, agreed upon by market participants, that enable auditable, accurate and timely data sharing at a market-wide scale. As mentioned in the IB1’s May 2024 AI consultation response, IB1 recommends that the data ecosystem, and integration with the data governance landscape be acknowledged.

2. Codifying the relationship and responsibilities of the AI governance landscape in support of the UK’s net zero and climate targets.

IB1 recommends that the developing AI governance landscape codifies a requirement for AI use in the energy sector to demonstrably contribute to the UK’s net zero targets and for this requirement to be open to monitoring and audit. Without codification of this principle there is a risk that AI systems are established to optimise non-environmental goals, while creating negative environmental impacts. 

IB1 acknowledges the risk of AI systems generating increases in energy and water demand. Both the impacts and the demand profile of AI use across the energy system should be subject to scrutiny and appropriately governed to ensure they contribute meaningfully to the UK’s net zero targets.

IB1 notes that in training a model it is highly likely that training datasets will contain sensitive data (it is also possible to use only anonymised data within a training dataset to retain privacy in the model itself), but it is possible to implement techniques where sensitive data is significantly better protected in the training of the model such as aggregation, pseudo-anonymising personal data. A good example of this that has been accepted by Ofgem as appropriate for maintaining privacy is the creation of datasets in energy that aggregate data down to a few households based on which properties are on different Low Voltage Feeders. If there are clear controls on the training data which datasets can and cannot be used to train AI models, then we can expect the produced AI model to be privacy preserving. If you implement data protections after an AI model has already been trained, it is harder to control. If a model has used training datasets with potentially identifiable data within them, the model may provide outputs using this data and can end up linking datasets together to make it personally identifiable. 

17. How should we prioritise different energy use cases? Please consider aspects such as phasing, complexity, data accessibility and participation. 

Use case prioritisation should occur within a governance process with representatives from across the market, therefore, when the data sharing rules are co-designed participants understand the value of engagement, their business case, and the benefit case for sharing data. 

IB1 would recommend starting with use cases focussing around main blockers to transitioning to a net zero energy system. Delivering CP2030 will require reforms to the overarching structures that underpin delivery and operation of the energy system, to ensure they do not act as blockers to deployment of clean power projects. 

As mentioned in question 1, IB1 supports a robust governance process which centres user needs, and makes a business case for the effort of data sharing.

18. What unique or specific features of the energy market (and/or energy data) should we consider when developing a Smart Data scheme?

As noted in IB1’s response to DSIT’s Technology Adoption Review as the data sharing economy develops in a manner which is increasingly fluid and cross-sector, there is an ongoing need for policy and regulatory development which horizon-scans, assesses, and defines responsibility for addressing different aspects of the regulatory landscape. Providing this form of policy and regulatory join-up presents essential support to the incentivising and de-risking of investment in strategic sectors. 

Energy specific features to consider include:

• The outsized impact electrification has on reaching our net zero goals. 

The Climate Change Committee estimate in the Sixth Carbon Budget report is that transitioning to a clean power system will nearly eliminate the emissions relating to electricity generation by 2050. 

The way the UK generates electricity is increasingly complex and no longer linear. Electricity is being generated across more sites, such as wind and solar farms, as well as by electricity customers generating their own energy such as solar panels on rooftops. Electric vehicle batteries themselves are also a potential place for the storage and re-supply of energy back to the grid, although this does affect battery life.  This means the job of balancing our national grid is increasingly complicated. At the same time, the UK is working towards electrifying  the heating of homes and our transport system (buses, trains, fleet vehicles as well as cars and vans), so not only millions of homes and businesses will use electricity but millions of vehicles too. 

Data sharing is essential to plan for this electricity transition, which involves a lot of work with a wide variety of organisations, in addition to building systems that can continuously automate balancing supply and demand once data sharing is common place. 

• Complexity and collective agreement across the sector – the energy industry and the organisations who may need energy data is complex and rapidly changing. It can be difficult to meaningfully engage. Cross sector data sharing will bring in more complexities – stressing the importance of robust stakeholder engagement.
• Cultural change and industry readiness – must interact with the current data sharing culture within the energy companies, and consumers must be engaged to understand their value proposition. 
• Consumer smart meters: There is a risk of unequal access to smart services if we do not address the challenges known to exist in smart meters. Smart metering reporting can be inaccurate, offline, and in 2024 Energy UK confirmed there is a regional divide because of the way meters send usage data back to suppliers. Acknowledging and addressing this will reduce the risk of baking in non-equal access to smart services which arise from a smart data scheme. 
• Physical hardware: The energy system consists of long lived physical infrastructure with firmware. As our understanding of security and cybersecurity accelerates over time, we must be aware that not all security concerns can be addressed by downstream software and there are some baked in challenges in using the existing infrastructure. This is a key place where appropriate governance can understand any challenges and collaboratively determine solutions for scheme development.
• Energy is essential infrastructure: Energy is a fundamental utility and has unique national security considerations. Appropriate engagement with the National Protective Security Agency, and National Cyber Security Centre is required. 

19. What common principles are needed to support the development of an energy smart data scheme and why?

IB1 supports the design principles put forward by the Competition and Markets Authority (CMA) for an effective Smart Data scheme and the Centre for Data Ethics and Innovation (CDEI) suggested key considerations. 

• IB1 would inquire for more clarity on mandated participation – who does this include? Licensed operators? Third party providers who use energy data? The energy system is complex with many licensed and non-licensed operators and clarity would be appreciated.

Please note IB1’s response to Ofgem’s Governing of a Data Sharing Infrastructure (DSI) Consultation and response to Ofgem’s Consumer Consent Solution.  IB1 urges the alignment of the design principles and governance principles between the Data Sharing Infrastructure (DSI), the consumer consent solution, and an energy smart data scheme. Please find our recommendations to build and maintain trust with core principles below:

• Governance mechanism is built to function flexibly

As digitalisation of the energy sector, and the wider economy, accelerates it is essential that governance adapts with 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. 

• Simple and Low Friction 

IB1 recommends a simple and low friction option 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), to ensure an energy smart data scheme is aligned with national strategy.

• Interoperable 

IB1 strongly recommends taking a joined up approach which is interoperable with initiatives across the economy. IB1 suggests the solution defines relationships with adjacent bodies in the energy sector and beyond to enable cross sector interoperability.

• Agile, Flexible, and Scalable

IB1 suggests introducing a clear process for change management in this principle. As governance needs will likely change with time. This may include indication of how the list of permitted data use purposes will be maintained with additions and removals

• Transparent and Informative

IB1 strongly recommends that documentation is published openly, along with any accompanying processes, methodologies, financial, legal, operations and governance processes, as also suggested in our DSI consultation response. 

• 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. 
• Inclusive by Design 

The solution intends to protect vulnerable consumers, which can be at odds with requiring technical checks (MFA or similar). IB1 urges the defined user journeys, messaging, terms, and customer support to be easy to use, transparent, and explained in a way that someone with a low technical reading comprehension can engage with. IB1 recommends building on open source, if not incorporated, there is a risk of inadvertently creating a monopoly.

• Secure by Design

IB1 encourages working with the National Protective Security Authority (NPSA) and National Cyber Security Centre (NCSC). IB1 would also recommend an adversarial analysis to be performed to see where security gaps may occur, and may affect the proposed architecture. The solution must avoid creating large targets for hackers where a compromise affects many consumers. 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. 

• IB1 recommends a focus on data rights: the same data will be used for many purposes. This means there will be multiple rights, based on purpose, carrying different legal, liability and related conditions. 

IB1 scheme governance is based on five pillars, each of which are essential to development and operation of the scheme:

1. User needs, materiality, and impact
2. Technical infrastructure
3. Data licensing and legal
4. Engagement and communications
5. Policy

See more information at https://ib1.org/sops/governance-schemes/ 

20. What are the specific technical considerations for developing an energy smart data scheme? (E.g. data standards, data access, use of APIs, authentication). You are welcome to include visual aids or diagrams to support your response. 

IB1 recommends an energy smart data scheme include the following technical considerations:

• Taking an open standards-based, transparent, market-wide framework approach to allow for the rapid scalability of secure access to data
  • Trust Framework: identity management, contracting, adoption and operation of Schemes, common principles (see more https://ib1.org/definitions/trust-framework/)
  • Scheme: rulebook for specific use cases (technical, legal, policy, operational) (see https://ib1.org/definitions/scheme/)
• Reiterating the importance of having governance oversight to avoid anticompetitive practices, and to guard against cartels to ensure it is a fair place to do business
• Mandating specific technical security standards. These must be agile to respond to changing security requirements and threats.
  • An example is FAPI, which mandates specific security choices with sufficient implementation flexibility to be practical in most environments.
  • Open ID
  • OAuth
• Using available web standards developers are familiar with to build 
• Making APIs explainable to machines (i.e. Open API spec when describing an API being registered on the registry – this can generate the code in most languages)
• Data access. There can be an assumption that the data holder controls data access, and while technically they do, in a scheme they sign up to rules that may require them to release the data. They therefore cannot make ad hoc decisions that give access to a data user (company 1) but not give access to another data user (company 2) who fit the same criteria within the scheme. 
• Describing data access rules as part of specification for data sharing. Therefore participants can understand on what terms they get the data. IB1 recommends the governance function provides oversight to ensure it is not abused (e.g. anticompetitive practices)
• Mandatory access control, which should be applied equally (unless otherwise noted)
• Defining data standards that align with common requirements across schemes, such as for data catalogues, licence representations, permission, assurance or provenance. 
• Defining metadata standards – and publishing them openly. As mentioned in IB1’s response to Ofgem’s Updates to data best practice guidance, IB1 supported requiring the use of Dublin Core as a Core Standard. IB1 agreed with Ofgem’s recommendation for publishing metadata using the Dublin Core standard, but IB1 also suggested further refining it to specify the Dublin Core-based Data Catalog Vocabulary (DCAT), which is supported by the main data catalogue platforms and is the metadata standard adopted for all EU public sector data publication.
• Considering how an interoperable identity mechanism may be possible across different schemes. IB1 think this should not be a centralised identity, but a mechanism which can enable cross scheme identity verification. 
• Building on the work around machine readable licensing terms
• Developing standards on monitoring, auditing, logging (tools which can look across schemes make sure data is not leaking out of them)
• Starting with conceptual alignment for interoperability (i.e. data field and protocol alignment) and then moving on to technical alignment

21. What specific privacy and security issues should be considered when developing an energy smart data scheme and how might these issues be addressed?

IB1 recommends the governance process must engage with by SEC, RECCo, Ofgem, NPSA, ICO, NCSC to ensure issues are raised and collaboratively discussed. 

It is essential to consider communications, legal redress, branding, clear use of data, and clarity of permissions. These are just as important as technical security and privacy protection.

Further privacy and security issues to consider:

• Alignment with personal data protection

In the 2023 Perseus report the technical advisory group preferred to use the word ‘permission’ to ‘consent’. This is because ‘consent’ has a potentially more narrow definition in personal data protection than is necessary for SME data protection. IB1 aligned Perseus as much as possible to the mechanisms required by GDPR and similar data protection legislation.

• Identifying and agreeing on licensing terms required
• Data limitation
• Clarity on what the data is being used for to ensure there is no out of scheme use (minimum sufficient purpose) 
• A decentralised model, which aligns with the approach taken by Open Banking, and the architectural principles of the Data Sharing Infrastructure for ease of access and protection
• Clear signalling of membership of a scheme to avoid fraudulent actors 
• Level of trust in consumer visibility – how it is maintained, and they are kept informed of risk
• Scheme positions should be auditable and traceable 

22. Which body (or bodies) should be responsible for scheme design and implementation? Which body should be responsible for regulating the scheme? Please include consideration of the most appropriate role for government. 

In collaboration with industry, code bodies and regulators, IB1 has modelled, designed and tested a framework to design and implement Smart Data Schemes using a Trust Framework approach.   

Schemes are co-designed by market participants and implemented using Trust Services. Neither touch the underlying data or anything about the end users.  Trust Frameworks verify that rules have been agreed and can enable their enforcement.

Our approach has three elements:

1. A mandate to act: the governing body for a sector, whether formal (regulated) or informal (voluntary) acts as the convener to create a mandate to deliver a scheme and implement it. This body can comprise only statutory bodies (e.g. in Open Banking, the FCA and CMA), only commercial bodies (e.g. STREAM), or a blend (e.g. Perseus). 
2. Co-design of Schemes: a collaborative process to discover and co-design the rules. This includes five areas: purpose, technical, legal, communications and policy. Once rules are established, processes for change and ongoing governance are codified and maintained. 
3. Scheme implementation using Trust Framework: this is done in a machine-compatible and enforceable manner

In assessing where governance is approached separately/collectively, IB1 proposes a governance body (and any subcontracted entities), would find it helpful to consider the following (non-exhaustive) factors such as:

• Goals/aims: How are goals defined and set? Who is involved? How is the balance of goals assessed across technical, socio-economic, and environmental domains? Is there potential for goal conflict across the different nodes and, if so, how will this be managed?
• Coordination: how will the governing body coordinate with developments within and beyond the energy sector? How will this feed into goals, design choices, and definition of technical/architectural parameters? How might this need to evolve over time?
• Roles and responsibilities: How are roles and responsibilities defined? Do these differ across each node or are the same roles/responsibilities universal? 
• Change management: How will change management processes work across the schemes? Are there different stakeholder or technical requirements for separate processes? Are different stakeholders (i.e. with different roles or areas of expertise) required to co-construct and/or sign off changes to different parts? 
• Communications: If different stakeholders are involved how are these stakeholders engaged and communicated with? Do they have different communication needs that must be built into governance processes or cadences?

As mentioned in our response to Ofgem’s DSI governance consultation, IB1 suggests that Open Energy be formally considered as a vehicle for the governance and implementation of the Trust Framework. Open Energy, funded by public money and coordinated by the non-profit body Icebreaker One, has been specifically developed for this purpose using a combination of radically transparent methods of open working, extensive consultation with stakeholders, and the input of specific domain expertise from energy industry, academic, and Smart Data specialists. IB1 has been involved in the DSI as the governance advisory partner, and is involved in the MVP through inputting into the pilot development, and use case exploration.

Our work to date provides strong justification that the structural model of Trust Frameworks and Schemes initially developed through Open Energy and subsequently advanced through IB1’s programmes such as Perseus and Stream. 

23. What are the required roles and responsibilities for the ongoing operation of an energy smart data scheme? This might include (but is not limited to): accreditation, accountability, oversight, enhancement and liability. 

As noted in IB1’s response to Ofgem’s DSI governance consultation, IB1 suggests there is clear guidance as to how rules are established, overseen, enforced, and changed. These must be explicit and transparently codified roles of the governance body and must also detail under what circumstances any of these roles can be delegated and/or subcontracted to specialists. 

Accordingly, IB1 recommends that the roles include definition of processes and/or rules for the establishment, oversight, enforcement, and change of: Stakeholder mapping, engagement and representation, goal setting, defining success criteria (across technical, socio-economic, and environmental domains), monitoring, reporting, and verification (MRV), change management, communications, dispute resolution, liability and redress, any formal responsibilities towards meeting cross-economy policy goals such as: Net zero, Industrial strategy, social policy.

IB1 further recommends that roles are included to oversee – where not already covered by another body in the broader environment – the definition of processes and/or rules for the establishment, oversight, enforcement, and change of: data rights, adjacent agreements (e.g. membership contracts / terms of use), guidelines (e.g. antitrust, fairness, transparency, publishing).

Finally, IB1 suggests that the governance body should have an active and transparent role in defining formal and informal relationships with adjacent bodies in the energy sector and beyond. This role may include jointly establishing and maintaining:

• Channels of communication 
• Obligations on reporting or information sharing
• Formal processes and roles for engagement (e.g. assignation of ‘observer status’ in certain governance fora)
• Approaches to sharing and/or allocating roles when approaching shared issues 
• Appropriate accountability structures
• Approaches to reduce forum proliferation (and ensuring associated fair access to governance fora for smaller organisations with less resource)
• Approaches to contributing or responding to cross-sectoral policy and regulatory developments in a joined up manner.

The suggested role changes above imply a set of associated responsibilities which are outlined in the sub-bullets. Many of these responsibilities are likely to constitute oversight rather than design/delivery, allowing for subcontracting arrangements to take place where required. IB1 suggest that a governance body holds responsibilities for the oversight of:

• User needs identification, testing, and convening
• Assessing and measuring impact across socio-economic, environmental, and technical domains
• Where impacts are undesirable, performing impact mitigation 
• Ensuring cohesion (of procedural, legal, technical approaches)

Implicit across all our suggestions is the principle that key roles and responsibilities explicitly include reference to the wider socio-technical landscape. IB1 suggests that codifying these responsibilities would provide an improved balance between technical, social, and operational elements of governance. While not all areas of responsibility need to be undertaken directly by the proposed governance body (e.g. it may be possible to subcontract an appropriate body to support stakeholder engagement) IB1 strongly suggest that the following (non-exhaustive) points would benefit from more formalised oversight, governance integration, and appropriate resourcing : 

• Data rights and surrounding legal structures governing the exchange of data and associated intellectual property
• Stakeholder engagement and communications
• Cross-sector, policy and regulatory input/coordination (including social, economic, and environmental factors)

24. What common functions and responsibilities should be centralised to enable interoperability with other markets outside the energy sector?

A core centralised capability must be the design principles. Additionally, IB1 recommends governance as a centralised space to identify and discuss considerations and adoptions.  

The governance process should collaboratively agree upon:

• Licence compatibility 
• The intent to work toward interoperability and working in widely understood formats. 
• Adoption of common web standards as the default (unless insufficient) to allow for widest possible number of technologists understand 
• The use of consistent tooling which is well understood by stakeholders.
• Choosing security standards 
• The use of open source
• Conceptual alignment on what metadata means (better yet  – technical compatibility), and aligning around standards. 

To enable interoperability, IB1 recommends considering how an interoperable identity mechanism may be possible across different schemes. IB1 think this should not be a centralised identity, but a mechanism which can enable cross scheme identity verification. This is a key area of research with further needed around how a federated identity system may work. 

25. What are your views on the feasibility to deliver an energy smart data scheme? Please consider any current or planned industry developments or changes that might affect delivery and highlight any key challenges.

Perseus

It is feasible to deliver an energy smart data scheme, IB1 are running the Perseus programme (https://ib1.org/perseus/) with a core use case focusing on the sharing of 30-minute electricity consumption data, which is combined with corresponding 30-minute local grid carbon intensity readings to calculate assurable monthly greenhouse gas emissions. 

As mentioned above, IB1 are following a robust governance process https://ib1.org/sops/governance-schemes/ and have brought together over 150+ organisations to co-design the programme (see 2024 report here: https://ib1.org/perseus/2024-report/). Perseus is now in its pilot phase,  involving real data sharing and real loan-making. 

It has been designed to scale internationally: 

• With global members that already do business with millions of SMEs, including Lloyds, Barclays, NatWest, Tide, Sage, Xero and Intuit
• With a Scheme agreement that is extensible to other domains, adaptable to different legal jurisdictions and sectoral data regimes, and compatible with GDPR

Our core recommendation to ensure an energy smart data scheme is feasible is to ensure governance is up and running from the start. 

26. What challenges and risks should we consider when developing an energy smart data scheme and how can we mitigate these? This might include (but is not limited to): competition; customer exclusion; data quality or data misuse; ethical, operational or technical concerns

As mentioned throughout the consultation, a non-exhaustive list of challenges and risks include:

• Developing a centralised solution. 
  • Mitigation: embrace a decentralised model, which aligns with the approach taken by Open Banking, and the architectural principles of the Data Sharing Infrastructure for ease of access and protection (ensures alignment with national strategy, Open Banking has been endorsed by the Competition and Markets Authority (CMA) and the Financial Conduct Authority (FCA))
• Not codifying the relationship and responsibilities of the energy smart data scheme to be in support of the UK’s net zero and climate targets. This is essential to meeting the UK’s net zero and industrial strategy goals.
  • Mitigation: Codify the relationship between an energy smart data scheme and existing net zero goals
• Not following a use case driven approach. The risk is trying to do too much at one time, and the programme becomes overwhelmed without a core focus point.
  • Mitigation: follow a use case driven approach – see question 1 for benefits of taking a use case driven approach. 
• A chosen use case does not have a clear business impact case. If there is no financial incentive, there will be no movement.
  • Mitigation: an advisory group articulates their business case for the chosen use case. 
• Failure to implement governance from the start, and governance failure to address broader user needs, technical implementation, legal, communication / engagement and policy impacts.
  • Mitigation: robust governance from the outset. 
• Lack of cross sector collaboration. Risk of non-interoperability and not taking the learnings from other sectors.
  • Mitigation: actively engage with stakeholders from the start
• Too much emphasis on a technical solution  – must equally address governance, user needs, business, social, legal, engagement and communications to be successfully implemented and ensure a scheme is fit for purpose
  • Mitigation: understand the holistic approach required – user needs, legal, policy, and communications
• Cultural change and industry readiness 
  • Mitigation: interact with the current data sharing culture within the energy companies, and consumers must be engaged to understand their value proposition. 
• Stakeholder engagement for collective agreement across the sector
  • Mitigation: engage early, often, and formally through governance
• A scheme is seen as a technical solution rather than a holistic solution.
  • Mitigation: a trust framework incorporates technical, communications, engagement, legal and ongoing governance arrangements.
• Unequal access to smart services if we do not address the challenges known to exist in smart meters, known barriers to access, and any other infrastructure collecting the data which will be used in the scheme. This unequal access will be baked into any smart services offered and may unintentionally miss out key beneficiaries.
  •  Mitigation: robust governance experience to reduce unintended impacts
• Creating unintended monopolies, negative incentives, corporate capture, and data misuse
  • Mitigation: robust governance, embracing and building upon open source solutions. 

27. What are the potential implementation costs to industry of introducing an energy smart data scheme? What aspects of a scheme might be most challenging to implement? 

Implementation costs will include secretariat functions for a governance body, energy company time for stakeholder engagement and scoping requirements, and technical implementation. This will include team members from across an organisation, which may include innovation, technical, data, research, legal, communications/PR, and policy compliance teams. 

Identifying the user(s), their needs and developing use cases requires time, effort and resource. This can be a challenging aspect of a scheme to define but it is a core element as everything is built around the user needs. 

28. How might implementation and ongoing management costs of a scheme be distributed across industry participants in an energy smart data scheme? 

IB1 is co-funded using a blended membership and grant model, which helps accelerate market development, adoption and carry out  neutral research. This is based on the  success of Open Banking and the Open Data Institute. 

In Phase 3 of Open Energy, IB1 formed an advisory group focussed on Membership. The group settled on a membership model to be a financially independent service that will not require government funding in the long-term and will support the needs of both industry and government policy. Membership was categorised by aggregate turnover or non-profit status. User needs for data sharing in the energy sector tend to differ by type of organisation. Our analysis identified common user needs across our five membership categories: 

• Strategic partners – regulated entities with an obligation to share data
• Enterprises – companies with aggregate annual turnover of at least £36m
• SMEs – companies with aggregate annual turnovers between £1.7m – £36m
• Micro-businesses – companies with aggregate annual turnovers under £1.7m
• Non-profits – including trade bodies, public sector, universities, charities, community energy etc. where specific rules and features apply

29. Do you have any additional comments on any aspect of developing an energy smart data scheme that has not been covered elsewhere in this call for evidence?

Of concern is that there is material referring to “domestic consumers” when the Data Bill addresses both business and consumers as users. There is also an over-emphasis on consumption data and not broader whole-systems data (e.g. that will support flex, demand response, etc ), and care should be taken over language (e.g. ‘consent’ vs ‘permission’).

IB1 notes a few key aspects not covered in the call for evidence:

• Recognition of the legal agreements, liabilities, redress, and assurance.
• We strongly advocate for adding in a requirement for work around stakeholder engagement and communications to convey why stakeholders should trust in the process, system, and data sharing in addition to why people should be engaged with it or not.
• More detail about monitoring, delivery oversight, complaints, and how this scheme would engage with policy would be appreciated. 
• More detail on the review process for involving national infrastructure departments
• Our data infrastructure incorporates many categories of data that have varied levels of sensitivity. In order to handle this complexity, and to ensure data is appropriately protected IB1 have developed a system of data sensitivity classifications https://ib1.org/data-sensitivity-classes/ 

See all referenced IB1 response documents here:

• IB1 response to DSIT’s Technology Adoption Review https://ib1.org/2025/02/20/ib1s-response-to-dsits-technology-adoption-review-call-for-evidence/ 
• IB1 response to Ofgem’s Consumer Consent consultation https://ib1.org/2024/10/16/ib1-response-to-ofgems-consumer-consent-solution-consultation/
• IB1 response to Ofgem’s DSI governance consultation https://ib1.org/2024/09/24/ib1-response-to-ofgems-governance-of-a-data-sharing-infrastructure-dsi-consultation/ 
• IB1 response to DBT’s Invest 2035 Industrial Strategy https://ib1.org/2024/12/19/ib1s-response-to-dbts-invest-2035-industrial-strategy-consultation/ 
• IB1 response to Ofgem’s AI in the energy sector consultation https://ib1.org/2025/02/20/ib1s-response-to-ofgems-ai-in-the-energy-sector-guidance-consultation/ 
• IB1 response to Ofgem’s AI in the energy sector consultation https://ib1.org/2024/05/20/ib1-response-to-ofgems-call-for-input-on-the-use-of-ai-in-the-energy-sector/ 
• IB1 response to Ofgem’s updates to Data Best Practices

Please note that throughout this consultation, Icebreaker One uses the terms Open, Shared and Closed data as defined here.

If you have any questions or require clarifications please contact us at policy@ib1.org.

Call for input response (relevant questions):

2. What are the biggest barriers to technology adoption in your sector and/or across sectors? Does business size and geographic location affect how firms are impacted by these barriers?

Icebreaker One (IB1) is a neutral non-profit that works on data sharing and sustainability. We convene organisations (in the energy, water, transport, agriculture, and financial sectors) and governments to design and deliver solutions at market scale.

The financial, energy and transport sectors are critical first priorities as the UK transitions to a decentralised, green energy future that can be reliably supported by the financial sector. Unlocking access to data through Smart Data schemes will serve to enable, and derisk, these priorities.

Data sharing and data access is at the heart of the UK’s identified outcomes in the Industrial Strategy green paper. Through IB1’s cross-sector work we note a key barrier to technology adoption is 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. As stated in IB1’s response to Ofgem’s call for input on the future of distributed flexibility, we acknowledge the benefits of having a clear, concisely stated end state vision. Having a cohesive, consistent vision with clear actions allows for stakeholders to incorporate data sharing and data access at the core of their decisions. The vision provides an opportunity to create the atmosphere for cultural change to occur, placing data sharing and access at the heart of decision making, and becoming business as usual. 

We recommend a consistent and cohesive policy vision should also be able to be changed and iterated upon to allow for the inevitable changes and innovations which will arise with time to ensure it continues to fit the needs of the country, companies, and users. We strongly recommend this process should occur in the open including all processes are appropriately documented, published openly, and available for scrutiny. 

Generally, our research understands that easing the administrative and cost burden for SMEs is key. This includes technical adoption. Ease of use and consistent policy allows SMEs to easily and confidently engage with technology while reducing risk and promoting investment in sustainable business practices. 

Example: IB1’s Perseus Scheme (the ‘rule book’ defining how data is governed) is aiming to facilitate trusted, standardised, permissioned and secure data sharing across sectors. It addresses key challenges in data interoperability and trust by linking data systems through a cohesive Trust Framework, streamlining the process of collecting and reporting emissions data. By enabling interoperability between members, it enables SMEs to minimise their manual effort in measuring and reporting their GHG footprint, and matching their profile to green finance. 

3. What is the evidence for technology adoption across different sizes of businesses?

Through IB1’s experience and learnings from engaging closely with actors in the value chain as part of Perseus, the evidence for technology adoption in emissions reporting and management demonstrates two distinct but interconnected points.

First, at the SME level, businesses are adopting various technology solutions to record and report their emissions. These include dedicated emissions calculators, carbon accounting tools, and extensions for financial accounting software that generate emissions estimates based on spending data. 

The current technological landscape for SMEs is fragmented, with businesses using multiple different methods for recording and sharing emissions data. Most solutions rely heavily on manual data entry, with technical integration generally limited to connections with financial accounting products for spend-based emissions estimates. 

Larger stakeholders with significant Scope 3 emissions – such as corporates with extensive supply chains or banks with substantial loan books – are adopting technology platforms to receive and compile emissions information from their SME stakeholders. However, the effectiveness of these platforms is constrained by inconsistent methodologies and tools used by SMEs to generate their emissions data, and challenges in verifying the accuracy and quality of submitted data.

6. How effectively does the UK support the adoption of new technology? What could be improved in your sector and/or across sectors?

Data sharing and data access is at the heart of meeting the UK’s decarbonisation goals. In our response to Industrial Strategy consultation IB1 encouraged the Industrial Strategy to endorse and build upon the Data (Use and Access) bill and ensure that the work on Smart Data is fully connected and integrated into planning processes. 

IB1 encourages any effort the UK makes toward implementing national data as infrastructure so that it provides consistent control, sharing, and security for data, much like other public infrastructures such as roads and utilities. To make the most of its value, and reduce risks, we need to connect data with those who need it and put in place the right protections for everyone. 

As mentioned in IB1’s response to Ofgem’s The future of distributed flexibility consultation and DBT’s Industry 2035 consultation consistency in vision and decision making  identified as a barrier to investment and expanding cross-sector and sector wide data and digital strategies. 

Additionally, collaboration and cross-sector initiatives are essential to have consistency within sectors and across the pinchpoints where sectors meet and/or markets are increasingly ‘coupled’ (i.e. energy and transport; energy and water; energy and manufacturing). Having a cohesive, consistent vision with clear actions allows for stakeholders to incorporate data sharing and data access at the core of their decision making, and creates the atmosphere for a data sharing cultural change to become business as usual. 

7. What current policies and/or initiatives support technology adoption in your sector and/or across sectors?

As mentioned in in question 6, IB1’s response to DBT’s Industrial Strategy 2035 consultation, the Industrial Strategy should endorse and build upon the Data (Use and Access) bill and ensure that the work on Smart Data is fully connected and integrated into planning processes. 

The UK must implement national data as infrastructure so that it provides consistent control, sharing, and security for data, much like other public infrastructures such as roads and utilities. To make the most of its value, and reduce risks, we need to connect data with those who need it and put in place the right protections for everyone. This supports net-zero investment decisions by connecting assurable real economy & financial economy data between organisations and between sectors.

8. The availability of skilled employees is a significant enabler of technology adoption. What are the main skills needs across the economy/in your sector required to drive technology adoption and where are the most significant gaps?

Enabling technology adoption requires more than technical skills. Catalyst technical innovation needs to understand a use case, legal, licensing, policy implications of technical work. IB1 has developed an Icebreaking process to convene stakeholders around purpose and priority use cases – building on our experience to save time and money. To have well rounded technology development and adoption, we recommend the following skillsets for developing smart data schemes:

Understanding use case, user needs recommended skills and expertise:

• Experience in gathering and analysing user insights to identify if/what technology would need to be developed to solve their challenge
• Ability to identify and prioritise use cases
• Knowledge of UX principles and user-centric design approaches
• Expertise in engaging with stakeholders and understanding their unique technical challenges.
• Skills in synthesising user feedback into actionable recommendations

Technical implementation recommended skills and expertise:

• Knowledge of building or operating financial or similarly secure data processing environments
• Experience leading or advising on the architecture and implementation of at-scale online services
• Experience with standard systems, processes and technologies for integrating online services (for example REST APIs, OAuth, PubSub) 
• Understanding of the implementation of services acting as data suppliers and/or data consumers
• Technical expertise in metadata publishing and maintenance, managing data catalogues, managing data
• Experience with technical policy and compliance
• Ensuring training / upskilling understands and aligns with new and emerging technologies

Legal and licensing recommended skills and expertise:

• Expertise in legal and compliance frameworks related to data governance
• Experience drafting and negotiating data-sharing agreements and licences
• Knowledge of regulatory standards such as GDPR and national data protection laws
• Familiarity with managing data sensitivity classifications and access control policies
• The ability to collaborate across technical, policy, and operational teams
• Skills in stakeholder engagement and facilitating legal onboarding processes.

Policy recommended skills and expertise:

• In-depth knowledge of regulatory frameworks and compliance requirements, including GDPR and financial data regulations
• Experience with aligning organisational policies with international standards
• Expertise in developing internal policy frameworks for data governance and ethical data practices
• Skills in stakeholder engagement and resolving compliance-related challenges.
• Familiarity with monitoring and evaluation mechanisms for policy adherence
• Ability to collaborate effectively with legal, technical, and operational teams to ensure cohesive policy implementation

11. Where is government uniquely placed to drive technology adoption?

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. 

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 convenor 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.
• 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.

12. Where is industry uniquely placed to drive technology adoption in your sector and/or across sectors? Where could industry go further to support the objectives of this review?

As noted in Question 6, consistency in vision and decision making is imperative for increasing investment and the adoption of cross-sector and sector wide data and digital strategies. Industry, where steered by a clear vision and consistent government guidelines, is well placed to drive technology adoption through its ability to drive investment in scalable solutions and integrate new technologies into existing operations. 

Where industries have access to shared data, new technologies can be implemented, tested and refined to improve adoption rates, efficiency and drive further innovation.

IB1 encourages the UK to move toward implementing national data as infrastructure to create incentives for organisations to invest in innovation and technology through various strategic pipelines. Where funding and resources can be made more accessible, industries can remove the financial burden of adopting new technologies, removing risk and fostering innovation. 

13. What opportunities are there for government and industry partnerships to drive technology adoption in your sector and/or across sectors?

IB1 believes there are several opportunities for government and industry partnerships to drive technology adoption in and across sectors. Learning from examples that are already occurring in energy and academia, we recommend:

Co-funding opportunities. These foster collaboration and solutions which help all related and participating businesses. A positive example has been the Strategic Innovation Fund programme which requires solutions to be led by an energy network, collaborative and for solutions and projects to be applicable network-wide (i.e. not to just one of the areas or networks)

Embedding researchers into government and industry partnerships. There are examples of researchers from the academic community being embedded into organisations to build collaboration and ease administrative burdens on commercial and government organisations to facilitate knowledge and data sharing. 

Benefits could include: 

• formation of cross-industry project consortia
• funding co-bidding, which may open new income streams for both research and sectoral organisations (e.g. innovation funds)
• co-working on technology solutions for particular business needs
• testing proofs of concept and/or pilot initiatives in lower risk environments.
  • We recommend providing opportunities and funding for more programmes like this, or considering whether this is appropriate as a condition of certain contracts or funding. 

14. What approach or policies should the government consider to accelerate technology adoption across the economy and/or within sectors?

As mentioned in Question 11, as the data sharing economy develops in a manner which is increasingly fluid and cross-sector there is an ongoing need for policy and regulatory development which horizon-scans, assesses, and defines responsibility for addressing different aspects of the regulatory landscape. Providing this form of policy and regulatory join-up presents essential support to the incentivising and de-risking of investment in strategic sectors. 

It is essential there is cross-sector collaboration and joined up thinking between the UK’s industrial strategy, approach and net zero goals, and growth areas. The economic growth plan set out by the Chancellor of the Exchequer, Rachel Reeves, is focused on growth in the supply-side of the economy to provide opportunities to the businesses, investors and entrepreneurs who drive economic growth with  3 essential elements:

1. Stability in politics, public finances and economy 
2. Reform to make it easier for businesses to trade, raise finance and build
3. Investment 

IB1 suggests that to strengthen these elements it must work with other partnerships between government, business and civil society, such as the Net Zero Council and ensure that growth, innovation, and technology adoption maximises the learnings and builds on the innovations from prior programmes. 

IB1’s response to the Wellcome and the Economic and Social Research Council (ESRC)’s UK National Data Library: Technical White Paper Challenge put forward principles that can be used by the UK Government, as well as companies, when seeking to drive technology innovation and adoption:

1. Clarify the use case and/or problem any proposed technical solution is intended to solve
2. Take inspiration from existing and similar digital  infrastructures, including from other sectors/domains and other countries
3. Ensure the solution adds something new, or improves or replaces what already exists
4. If you must build, build the most simple, decentralised version of the solution as possible
5. Like any complex digital infrastructure, begin with defined users and use cases rather than datasets
6. Be aware that the nature of the funding and staffing of any given solution, as much as its technical architecture, will shape what it can achieve

Please note that throughout this consultation, Icebreaker One uses the terms Open, Shared and Closed data as defined here.

If you have any questions or clarifications contact us at policy@ib1.org.

Consultation questions:

1. Do you agree with our conclusion that the existing regulatory framework is adequate to govern the use of AI, based on current understanding of the technology?

AI presents immense opportunities for driving economic growth, accelerating the transition to net zero, and enhancing financial and regulatory frameworks. However, AI must be deployed responsibly—ensuring trust, transparency, and interoperability across sectors.

IB1 advises adding clear guidance and timeframes as to when Ofgem will be reviewing AI policy determinations in light of AI landscape changing.

Fairness principle

Ofgem references fairness as a principle in their ethical approach, and in an information session suggested that AI governance could adopt definitions of fairness that already exist in energy sector regulation. As mentioned in IB1’s May 2024 AI consultation response, we strongly advocate for the adoption of a broader concept of social sustainability in defining fairness. This must conceptualise people in a manner beyond their economic roles and should also be capable of viewing people in terms of groups. This approach is vital to assessing a more holistic range of AI impacts beyond the individualised economic sphere. The approach can also be actioned in AI governance to ensure that governance is co-designed through processes which are adequately representative of different stakeholders or stakeholder groups, ensuring that the approach is collective rather than ‘done to’ from the top down.

2. Do you agree with the scope of our AI guidance regarding the current and potential stakeholders involved in the deployment of AI in the energy sector?

IB1 encourages cross-sector collaboration and learning wherever possible. We recommend engaging with cross sector (i.e. water, transportation, local authorities, etc) and working with citizen advocacy groups to learn from best practices, ensure guidance is consistent for cross sector use cases (hydrogen, electric vehicles, electrifying public transport, etc), and understands the impact of AI guidance on different socio-economic stakeholder groups.

3. Do you agree that the governance measures and policies we expect stakeholders to have in place across the AI life cycle ensure effective oversight of AI procurement and deployment?

As described in IB1’s AI positioning statement, IB1 supports a hybrid governance model, combining robust oversight with decentralised data sharing, including smart contracts and digital identity solutions. We recommend more guidance/information on how Ofgem will exercise any oversight/review on how AI is used within licensees is inline with the described expectations. This aligns with the UK government’s AI Opportunities Action Plan, which prioritises secure infrastructure, ethical AI adoption, and regulatory assurance​. Decentralised governance models for AI can prevent regulatory capture, ensure transparency, and maintain public trust in AI-enabled services.

4. Do you agree with how we expect stakeholders to identify, evaluate and mitigate the risks associated with the use of AI in the energy sector?

Currently, there is a lack of attention to the data foundations and their transparency and accountability. This is key for use of AI within the energy sector. IB1 would also encourage interoperability to be considered to have confidence in the performance of AI in the broader system. 

5. Do you agree with the competencies we expect stakeholders to have in place, so that AI opportunities can be realised and any associated challenges appropriately understood and mitigated?

IB1 agrees that AI’s potential to unlock financial, energy, and property data must be balanced with privacy, security, and ethical considerations. IB1 advocates for AI models that:

• Respect consumer consent and data sovereignty, using decentralised identity frameworks
• Support open standards to ensure interoperability between AI-driven systems
• Embed transparency and explainability to mitigate AI biases and prevent regulatory fragmentation​

We support organisations having relevant expertise to encompass the above bullet points to ensure organisations’ solutions meet safe, secure, fair and sustainable AI.

6. Ofgem must have due regard to certain equality aims under section 149 of the Equalities Act 2010. Does our guidance raise any adverse equality impact concerns, for example, for vulnerable or digitally excluded consumers?

As stated in question 2, IB1 recommend engaging with cross sector (i.e. water, transportation, local authorities, etc) and working with citizen advocacy groups to learn from best practices, ensure guidance is consistent for cross sector use cases (hydrogen, electric vehicles, electrifying public transport, etc), and understands the impact of AI guidance on different socio-economic stakeholder groups.

AI must be designed to mitigate bias and discrimination, ensuring fair access to economic opportunities, financial services, and public resources. We support governance which is co-designed through processes which are adequately representative of different stakeholders or stakeholder groups, ensuring that the approach is collective rather than ‘done to’ from the top down.

7. Are there any issues that are not covered by our AI guidance document?

IB1 advocates strongly for two additional areas of inclusion. 

1. We suggest Ofgem’s work on AI governance to integrate with developments in data governance, both within the energy sector and in the cross-economic space (e.g. Smart Data Roadmap, approaches to consent or permission). 

We believe it is important for data governance to establish principles, structures, roles and responsibilities, agreed upon by market participants, that enable accurate and timely data sharing at a market-wide scale. As mentioned in the IB1’s May 2024 AI consultation response, we recommend that the data ecosystem, and integration with the data governance landscape be acknowledged.

2. We suggest that Ofgem codifies the relationship and responsibilities of the AI governance landscape in support of the UK’s net zero and climate targets.

We acknowledge and appreciate Ofgem’s commitment to encouraging innovation while helping the UK to meet its net zero target and other associated targets. As mentioned in the IB1’s May 2024 AI consultation response, IB1 recommends that the developing AI governance landscape codifies a requirement for AI use in the energy sector to demonstrably contribute to the UK’s net zero targets and for this requirement to be open to monitoring and audit. Without codification of this principle there is a risk that AI systems are established to optimise non-environmental goals, while creating negative environmental impacts. 

IB1 acknowledges the risk of AI systems generating increases in energy and water demand. Both the impacts and the demand profile of AI use should be subject to scrutiny and appropriately governed to ensure they contribute meaningfully to the UK’s net zero targets.

IB1 also offers one more general comment. Both the AI landscape and the underlying data landscape are highly fluid and increasingly driven by cross-sectoral actors, data flows, use cases, value chains, and supply chains. IB1 suggests that the exact scope of AI regulation in the energy sector, and its integration with cross-economic developments in the data and digital governance spheres, requires further discussion which must involve an appropriately broad range of stakeholder engagement. IB1 advises adding clear guidance and timeframes as to when Ofgem will be reviewing AI policy determinations in light of AI landscape changing.

We have created an open document to explore what position we (all of us) should take in the governance of data around ‘ai’ (artificial intelligence, machine-learning, et al).

Click here to contribute to our open-to-comment paper
or Download this Word Doc version and email us research@ib1.org

Artificial intelligence (AI) is rapidly transforming how data is shared, managed, and leveraged across industries, but its impact on societal resilience—our collective ability to adapt, thrive, and safeguard against systemic risks—remains an open question. As AI is integrated into financial systems, energy infrastructure, and regulatory frameworks, ensuring it is ethical, transparent, and aligned with public interest is critical.

We wish to explore how AI can enhance resilience across economic, environmental, regulatory, digital, and social domains, and arrive at key principles that should guide its development. Embedding AI within open, interoperable, and responsible data ecosystems, we can drive sustainable growth, protect critical infrastructure, and empower communities. The question now is: how do we get this right?

“Every government agency, everywhere, is working on a new system that’ll solve all data problems and will be ready to use in 18-24 months… Except it will always be ready in 18-24 months.” – Whong’s Law

In December, we submitted a response to the Wellcome Trust and ESRC’s National Data Library Technical White Paper Challenge.

The Challenge was designed to surface concrete implementation options for the proposed National Data Library (NDL). We responded to:

• Support UK Government to look beyond the abstract ideas and aspirations projected onto the National Data Library thus far. 
• Propose a feasible implementation option, based on how we approach data infrastructure for net zero at Icebreaker One.
• Describe significant challenges to delivery regardless of technical role/architecture, and ways to address them.

We’re delighted that our white paper, Delivering an effective National Data Library, was selected for publication. And, as we present our paper this week, alongside four other submissions, we wanted to publish a summary along with some further thoughts. 

Building from a strong foundation

In our response, we argued that there’s an urgent need for UK Government – as well as the wider pool of organisations seeking to influence its design – to:

• Clarify the technical problem the National Data Library should address. We decided to focus our work on a National Data Library aimed at improving the discovery of government-held data for research. We described the fork in the road between research and pursuing improved operational data access, on the basis that the needs of researchers and operational data users are unlikely to be met by this singular intervention. This feels vindicated, given the release of the UK Government’s blueprint for modern digital government, which commits public sector organisations to do various things to improve the way data is used to deliver public services (including using standard APIs to exchange data). 
• Take inspiration from existing research data infrastructures, rather than the library metaphor. We pointed to 11 types and 39 examples of data infrastructures that already serve researchers’ needs, such as by generating new datasets for research (UK Biobank), unlocking access to data held by the private sector (Smart Data Research UK) and providing access to linked or combined datasets from multiple organisations (ONS Integrated Data Service). The National Data Library won’t exist in isolation and must be built with an understanding that it’ll be one node in a network of research data infrastructures. 
• Ensure the National Data Library adds something new, or improves or replaces what already exists. In addition to these existing research data infrastructures, there are numerous pan-government initiatives working to improve public sector data access. We argued for these initiatives – plus the Library’s intended users – to be engaged early, in order to understand the needs not met by existing efforts.

Our recommendation for the National Data Library

We recommended a simple, decentralised National Data Library to improve discovery of public sector data for research.

In the spirit of the Challenge, we laid out how it could maintain a searchable catalogue (or ‘index’, ‘registry’, ‘portal’; the name doesn’t really matter) of metadata harvested from across many public sector organisations. It wouldn’t copy or store any of the research data those organisations hold, but provide a service to help researchers find relevant datasets wherever they are on the web. It would look similar to Open Net Zero, which we’ve built to make net-zero data discoverable, accessible and usable. Open Net Zero currently indexes metadata on nearly 60,000 datasets from more than 400 organisations.

To do this, this National Data Library would harvest existing metadata from sources like data.gov.uk, gov.uk API Catalogue and Administrative Data Research UK Data Catalogue. It would also collaborate with public sector organisations to make available and harvest new metadata. It would point to datasets that are openly available, as well as datasets that researchers can work with under more restricted technical, legal and commercial conditions. While we described various technical challenges – including varying quality and machine-readability of metadata, and unclear data licensing terms – we think this represents a feasible version of the National Data Library.

There’s also some interesting things happening with metadata and data discovery that the Library could build on. This includes: new metadata formats emerging from the AI community (Croissant); ways to tag datasets with information about restrictions on their use (Data Use Ontology); and new tools that enable users to search across multiple data catalogues and within datasets on them (Open Data Deep Search, HerdingCats).

Data curation must begin with users and use cases

At Icebreaker One, we start with use cases and deliver data infrastructure to enable them. The starting point for Perseus, for example, was to automate high-quality sustainability reporting for every SME in the UK to enable them to access over $100bn of green finance. We’re focusing on unlocking half-hourly emissions data to do this, before we add further use cases and data types.

This is how complex data infrastructures are built. As John Wilbanks of the Astera Institute recently described, “You build a complex data system by answering five questions at a time, using a standards based approach. And then when you’ve answered twenty, you’ll have a functioning complex data system”. We must design data infrastructures for specific primary use and general secondary use.

We recommend the National Data Library takes a similar approach. While original research is needed to clarify its intended users and their needs, we pointed to existing evidence on use cases that the Library could address. This includes: 52 societal challenges hindered by a lack of coordinated data (DARE UK); high level areas of research interest (HM Treasury); and high-value datasets for reuse (European Commission).

The Library can’t be a vehicle for everything

The ambiguous language used around the National Data Library has caused confusion. The UK Government’s AI Opportunities Action Plan has recently described the National Data Library as “an enormous opportunity”. It says that ‘alongside’ the National Data Library, the UK Government should:

• “Run open calls to receive proposals from researchers and industry to propose new data sets”.
• “Rapidly identify at least 5 high-impact public datasets it will seek to make available to AI researchers and innovators”.
• “Establish a copyright-cleared British media asset training data set”.
• “Finance the creation of new high-value datasets that meet public sector, academia and startup needs”.

These could well be useful interventions to make to support the UK’s AI sector. But in order to give the National Data Library a necessary focus, the UK Government should be clear about the wide set of interventions it plans to make for the data economy vs the subset that will be delivered by the Library itself. 

The limits of our recommendation

While it’d help improve data discovery, we’re conscious that our recommended execution of the National Data Library wouldn’t move the dial when it comes to streamlining access to research data drawn/linked from multiple public sector organisations.

We compiled evidence that this is the significant challenge holding researchers back from working with public sector data in the UK, including from Administrative Data Research UK, the Public Administration and Constitutional Affairs Committee and the Office for Statistics Regulation.

It’s a very difficult problem to address. We pointed to Ben Goldacre’s 2022 review of the UK’s health data ecosystem, which identified a wide range of barriers to more effective linkage or combination of data for research in health alone. It described how individual data holders operate in silo, developing their own, bespoke approvals processes that make secure data linkage and access neigh on impossible.

The review made 30 detailed recommendations. We suggested that a similarly broad and deep set of interventions will be required to harmonise access to data for research across the whole of the public sector. We think this work is broader and deeper than is possible for the National Data Library to deliver, and that progress on streamlining access to research data will instead be driven by other actors. At a recent event held by Health Data Research UK, Sir Robert Chote, Chair of the UK Statistics Authority, described progress being made on a number of fronts. This included: the Office for National Statistics’s Integrated Data Service; reexamining the Five Safes framework to consider accrediting Safe Programmes rather than only Safe Projects; and the work of the Pan UK Data Governance Group.

Our view and recommendation has also been shaped by budget considerations. We anticipate that investment in the National Data Library will be modest and less permanent in comparison with other public data infrastructure: the ESRC alone has spent more than £200m in data collection, creation, curation and delivery.

Moving forward

Our recommendations for delivering an effective National Data Library have been shaped by our use-case driven approach to delivering data infrastructure for net zero. As we present our paper this week, we hope the UK Government will consider our suggestions as they develop further plans.

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 openenergy@ib1.org. Thank you for considering our submission.

Sectors

Q4: What are the most important subsectors and technologies that the UK government should focus on and why?

The financial, energy and transport sectors are critical first priorities as the UK transitions to a decentralised, green energy future that can be reliably supported by the financial sector. Unlocking access to data through Smart Data schemes will serve to enable, and derisk, these priorities.

Smart Data scheme as defined in The Smart Data Roadmap (DBT 2024):

Smart Data is the secure sharing of customer (individual or business) data, upon the customer’s request, with Authorised Third-party Providers (ATPs). The ATPs can then enhance the customer data with broader, contextual ‘business’ data, which may be provided directly to ATPs or may have been made ‘open’. A Smart Data Scheme is the implementation of Smart Data in a specific sector or group of sectors. These schemes require:

• A regulatory framework to govern how data is shared.
• Common and open data standards that reflect the dynamics of the market and minimise the risk to competition and consumer. 
• Participation of data holders, third parties and regulators. 
• Effective representation of consumers and other end users. 
• A funding model that reflects consumer interests.
•  Interoperability with other Smart Data schemes. 
•  Interoperability with other Smart Data schemes. 
• A practical framework for the delivery of schemes.

Business Environment

Q7: What are the most significant barriers to investment? Do they vary across the growth-driving sectors? What evidence can you share to illustrate this?

IB1 can comment on the barriers to investment in the ‘Clean Energy Industries’ and ‘Digital and Technologies’ growth-driving sectors as they are most relevant to our work. 

Data sharing and data access is at the heart of meeting the UK’s decarbonisation goals. 

For example, our flagship programme Perseus will automate access to assurable SME electricity data, so they will be able to see the emissions from their energy use and share it, via reporting solutions, to their banks to unlock green finance (Perseus 2023 Report). This will result in a viable connection between the financial economy and real economy to enable net zero impact in a scalable and assurable manner. When investors have trusted assurable data they are empowered to prioritise investment where needed for maximum net zero impact. 

Assurance gives confidence both to people inside companies that they are allowed to share data externally, as well as those externally knowing that they have permission and confidence in what is being supplied.

Throughout IB1’s programmes, a consistent theme of policy uncertainty has been identified as a barrier to investment and expanding cross-sector and sector wide data and digital strategies. As mentioned in IB1’s response to Ofgem’s The future of distributed flexibility consultation consistency in vision and decision making is vital for the decision makers in the organisations and companies which may be involved.

It is essential to have consistency within sectors and across the pinchpoints where sectors meet and/or markets are increasingly ‘coupled’ (i.e. energy and transport; energy and water; energy and manufacturing). Having a cohesive, consistent vision with clear actions allows for stakeholders to incorporate data sharing and data access at the core of their decision making, and creates the atmosphere for a data sharing cultural change to become business as usual. 

Business Environment – Innovation

10: Where you identified barriers in response to Question 7 which relate to RDI and technology adoption and diffusion, what UK Government policy solutions could best address these? 

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. 

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 convenor 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.

Business Environment – Data

Q12: How can the UK government best use data to support the delivery of the Industrial Strategy?

Icebreaker One Founder and CEO Gavin Starks is a co-chair on the Smart Data Council, alongside Minister Madders (and previously Minister Hollinrake). 

The Industrial Strategy should endorse and build upon the Data (Use and Access) bill and ensure that the work on Smart Data is fully connected and integrated into planning processes. 

The UK must implement national data as infrastructure so that it provides consistent control, sharing, and security for data, much like other public infrastructures such as roads and utilities. 

To make the most of its value, and reduce risks, we need to connect data with those who need it and put in place the right protections for everyone. This supports net-zero investment decisions by connecting assurable real economy & financial economy data between organisations and between sectors.

Equally important is to ensure that negative incentives, corporate capture, unintended monopoly positions, and data misuse are addressed through robust data sharing governance processes. As the data sharing economy develops in a manner which is increasingly fluid and cross-sector there is an ongoing need for policy and regulatory development which horizon-scans, assesses, and defines responsibility for addressing different aspects of the regulatory landscape. Providing this form of policy and regulatory join-up presents essential support to the incentivising and de-risking of investment in strategic sectors. 

IB1 supports 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.
  • Example: critical national infrastructure sectors must be particularly mindful of national security
• As digitalisation of the energy sector, and indeed 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. 
• 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.

Q13: What challenges or barriers to sharing or accessing data could the UK government remove to help improve business operations and decision making?

As noted in the IB1 response to Ofgem’s Data Sharing in a Digital Future call for input where we identified the following challenges or barriers for data sharing:

• Too much emphasis on a technical solution – implementing a data sharing infrastructure must not take a technical-led approach. It must address governance, user needs, business, social, legal, engagement and communications to be successfully implemented and ensure the solution is fit for purpose, and can be adopted by the market. We observe that technical-led programmes tend to fail to gain traction or deliver against material user needs.
• Complexity and collective agreement across the industry – the energy industry is complex and rapidly changing. It can be difficult to meaningfully engage. This requires robust industry engagement across any of the growth-driving sectors. 
• Cultural change and industry readiness – it is essential to understand and interact with the current data sharing culture within the organisations and companies, they must be engaged to understand their value proposition. 
• Appropriately defining and governing the roles of Ofgem regulated and non-regulated participants (and similar regulatory bodies across the sectors).
• Appropriate legal support and resourcing – a mechanism must develop the applicable data licences, and needs to be appropriately resourced to be able to do so. 

Business Environment – Infrastructure

Q14: Where you identified barriers in response to Question 7 which relate to planning, infrastructure and transport, what UK government policy solutions could best address these in addition to existing reforms? How can this best support regional growth?

The government role in remove removing challenges and barriers to sharing and accessing data include:

• Working with industry to determine where the lines are drawn between centralised, pre-competitive and competitive areas;
• An open consultation on what the role of regulation is, at what granularity, and the form of regulation (i.e. prescriptive, principles based, other)
• Constructively query the implementation of data sharing initiatives to ensure they serve the needs of human users and an environment where increased machine readability is important. This may include factors such as:
  • Human: language/terminology adoption and interoperability, user needs for supporting documentation (e.g. operational materials, policies, onboarding), interpretability of decision making.  
  • Machine: journey towards machine readability and interoperability of rules regimes
• Ensure those governing, operating and participating can be helped in their assessments of compatibility and interoperability
• Prioritise and create clear (and stable) roadmaps that enable investment to be made
  • In relation to ecosystem evolution – perhaps opportunity to learn across strategic sectors and influence their own regulatory landscapes. E.g. energy sector experimenting with regulated actors having a ‘digital spend envelope’ which is revisited on a slightly more frequent cadence.

Business Environment – Competition

Q19: How can regulatory and competition institutions best drive market dynamism to boost economic activity and growth?

The digital and data economy has a different market pattern than other sectors, as identified in Unlocking digital competition Expert Panel digital markets are subject to ‘tipping’ in which a winner will take most of the market. As mentioned in Question 14 it is essential to split out the precompetitive and competitive elements to establish a clear framework for collaboration and innovation. 

A robust pre-competitive approach to data sharing infrastructure  focusses on providing access to essential infrastructure while allowing competition to occur at higher-value layers. This fosters a balanced environment of innovation within defined frameworks, without undermining fair access to critical resources, and ensuring that negative incentives, corporate capture, unintended monopolies and vendor lock-in is avoided.

Business Environment – Regulation

Q20: Do you have suggestions on where regulation can be reformed or introduced to encourage growth and innovation, including addressing any barriers you identified in Question 7?

The Industrial Strategy should endorse and build upon the Data (Use and Access) bill and ensure that the work on Smart Data is fully connected and integrated into planning processes. 

Partnerships and Institutions

Q31: How should the Industrial Strategy Council interact with key non-government institutions and organisations?  

As a neutral non-profit, IB1 supports the development of solutions and solicits guidance from a wide range of stakeholders – including commercial and non-commercial companies, non-profits, community organisations – to ensure a solution meets a wide range of user needs and is driven by consensus. This advances solution adoption and innovation. 

General remarks:

IB1 emphases the importance of the required data sharing culture change and industry readiness and willingness to share data. It is essential to understand and interact with the current data sharing culture within the organisations and companies, they must be engaged to understand their value proposition. 

Through IB1 programmes and years of expertise, we support following a use case approach to data sharing initiatives. This approach centres user needs, and makes a business case for the effort of data sharing. A use case driven approach allows for:

1. 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 (regardless of central vs decentralised, mandate or not — mandates are also often ignored). Midata was mostly tech-led, Open Banking was use-case led.
2. Removal of friction: Removing transactional friction may seem like something everyone wants, but not if your current business model relies on it. 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).
3. Mandates: if the friction is ‘too high’, regulatory intervention is necessary to mandate participation and move the market. However, if the market can demonstrate self-initiation, then ‘endorsement’ from the government can be sufficient to drive impact. Value creation must be visible in both cases.

Please note that throughout this consultation, Icebreaker One (IB1) uses the terms Open, Shared and Closed data as defined here. Please note IB1’s response to Ofgem’s Governing of a Data Sharing Infrastructure (DSI) Consultation. We urge the alignment of the design principles and governance principles between DSI and the consumer consent solution. 

If you have any questions about our submission or require clarifications please do not hesitate to contact us via openenergy@ib1.org. We have omitted questions which we did not answer.

Consultation response:

Q1. Do you agree with these Design Principles? Would you recommend any additional Design Principles? 

Please note IB1’s response to Ofgem’s Governing of a Data Sharing Infrastructure (DSI) Consultation. We urge the alignment of the design principles and governance principles between the Data Sharing Infrastructure (DSI) and the consumer consent solution. Please find our additional comments on each of the design principles below:

Simple and Low Friction 

We recommend a simple and low friction option 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), to ensure Ofgem is aligned with national strategy.

However, the solution outlined in paragraph 1.6 envisages a centralised system that introduces complexity and friction. The proposal introduces complexity by setting out a single implementation which must meet all requirements across the industry, particularly around integration, security, accessibility, and data synchronisation, while avoiding becoming a bottleneck for performance and availability.

It will add friction by requiring users to interact with (and be prepared to trust) an additional organisation, and maintain another account, password, and MFA method.

Interoperable 

IB1 strongly recommends taking a joined up approach which is interoperable with initiatives across the economy. We suggest the solution define relationships with adjacent bodies in the energy sector and beyond to enable cross sector interoperability.

Example of cross-sector data sharing initiative: 

Icebreaker One convenes the cross-sector Perseus Scheme (ib1.org/perseus) to enable automated carbon emissions reporting for every SME in the UK. It creates the rules and processes that make automated reporting possible to enable products and services such as accounting platforms, emissions calculators, and reporting software to be developed that deliver higher-quality emissions data at scale. Perseus convenes hundreds of cross-sector organisations to ensure user needs and barriers from across the supply chains are captured and incorporated into the Scheme. 

The Scheme includes participants including SmartDCC, Perse, Sage, Visa, Lloyds Banking Group, to ensure strong alignment between the energy and financial sectors around Smart Data governance. It is additive to existing initiatives.

Agile, Flexible, and Scalable

We suggest introducing a clear process for change management in this principle. As governance needs will likely change with time. This may include indication of how the list of permitted data use purposes will be maintained with additions and removals.

Transparent and Informative

IB1 strongly recommends that documentation is published openly, along with any accompanying processes, methodologies, and governance processes, as also suggested in our DSI consultation response. 

Inclusive by Design 

The solution intends to protect vulnerable consumers, which can be at odds with requiring technical checks (MFA or similar). We urge the defined user journeys, messaging, terms, and customer support to be easy to use, transparent, and explained in a way that someone with a low technical reading comprehension can engage with.

Secure by design

We encourage working with the National Protective Security Authority (NPSA) and National Cyber Security Centre (NCSC). We would also recommend an adversarial analysis to be performed to see where security gaps may occur, and may affect the proposed architecture. The solution must avoid creating large targets for hackers where a compromise affects many consumers.

Please find our comments on additional design principles:

• How will different household types be handled in this solution? (i.e. providing consent as an individual versus households) 
• We suggest including an element of trust to the design principles. As mentioned in the Data Sharing in a Digital Future consultation, there is a lack of trust in energy companies by consumers. Trust is key for obtaining consent.
  • There may already be ‘trust’ in an entity if there is already an existing contractual relationship with suppliers (rather than introducing a new body).
• It is essential to view consumer consent mechanisms, such as Open Banking, holistically as a Trust Framework – an entity incorporating technical, communications, engagement, legal and ongoing governance arrangements – rather than a technical solution.
• We suggest providing clearer information about use cases and the approach to defining them. A use case describes a specific situation, or set of circumstances, in which a product or service can be used, not just data types to be targeted. This approach to defining a use case can also assist in defining cross-sectoral use cases. (For example, Perseus uses both smart meter and tariff data to enable calculated emissions to be used in lending decisions by the financial sector).
• We note that ‘Open Source’ is not mentioned throughout the consultation. If not incorporated, there is a risk of inadvertently creating a monopoly.

Q2. Do you have a preference between the centralised, decentralised or hybrid models? Please elaborate.

IB1 has a preference for a decentralised model, which aligns with the approach taken by Open Banking, and the architectural principles of the Data Sharing Infrastructure. The proposed solutions are centralised, with a single database which manages consent across all Suppliers. As stated in IB1’s call for input on Data Sharing in a Digital Future, we suggest a Trust Framework option should be considered. 

An Open Banking style Consumer Consent mechanism should be viewed holistically as a Trust Framework – an entity incorporating technical, communications, engagement, legal and ongoing governance arrangements – rather than solely a technical solution.

What are Trust Frameworks and Schemes?
Working on behalf of its public and private sector members, Icebreaker One operates Trust Frameworks and Schemes across a variety of sector specific and cross-sectoral domains. Trust Frameworks operate at the level of a defined governance domain (e.g. sector or geography) to collaboratively establish and maintain a light layer of identity management, governance, definitions, principles and Open Standards for data sharing. 

Schemes – which operate within a Trust Framework environment – are defined through structured programs to facilitate and govern the sharing of data among participating entities in the context of a specific use case, or set of related use cases. They collaboratively define the rules concerning what data can be shared, why (purpose), by whom (roles), and how (technical requirements, legal structure, etc). They also address the communications requirements of the Scheme and its relationship with the surrounding policy, regulatory, and legislative landscape. The structural operation of Schemes, linked to specific Trust Frameworks, is capable of supporting the progression of multiple data-sharing  initiatives with distinct needs (e.g. security requirements, personal data protection etc), whist ensuring interoperability, conceptual cohesion, open market development, transparency, and good governance principles (e.g. fairness, value-sharing, protection of data rights) across the wider Trust Framework domain.

The development of Trust Frameworks and Schemes by IB1 builds from existing bodies of knowledge and experience established by initiatives such as Open Banking, cross-sector governance initiatives such as the Smart Data Council, and expert knowledge bases within academic and industry research. Icebreaker One’s work to date demonstrates that Trust Frameworks and Schemes provide a robust but flexible approach to the governance of data sharing infrastructure which is adaptable across multiple use cases, sectors, and governance domains. IB1 has worked with use cases and organisations spanning cross-sector spaces as well as energy, water, finance, insurance, transport, and supply chains sectors. It is working with Open Banking Limited on interoperability between Open Energy and Open Banking.

How a solution could be modelled on Open Banking:

Open Banking is decentralised, where suppliers are responsible for managing consent for their customers, using the existing trust and account management in the supplier/consumer relationship.

Each Supplier would provide a consent hub within their existing App and account management website. The implementation of this consent hub would be chosen by the supplier, who are free to develop their own, collaborate on an open source implementation, or buy in a solution managed by one of many software vendors.

When a consumer is asked to provide meter data and consent, the service uses a centrally maintained list of Suppliers, and asks the user to choose their Supplier. Then, using standard protocols in a technical solution using the architectural principles from Open Banking, the service asks the user to authenticate with their Supplier. After the user gives consent, the Supplier returns a token to the service to access meter data.

Meter data can be fetched via the Supplier’s service, or direct from Smart DCC using the token created by the Supplier.

When a consumer changes Supplier, a list of consents would be passed to the winning Supplier, who would then give the user the opportunity to give the same consents to maintain their connections to the services they use.

The advantages of this approach include:

• Matching the mental model of the user, who sees their Supplier as the source of data about their energy use, and therefore:
  • Reuses the login and protections of their online account with their Supplier
  • Minimises friction in the user experience, by identifying the meter through their supplier login, avoiding the need for the user to enter meter numbers and authentication codes from an IHD
  • Eliminates the ability of scammers to impersonate an official body that consumers do not fully understand
• Creation of an agile market of consent providers who can provide for different purposes and compete on functionality and capabilities, including
  • Integration into account management systems
  • Meeting diverse accessibility requirements by avoiding the need to wait for a central provider to solve, for example language provision in Welsh and other languages used in the UK
• Improved acceptance by Suppliers, who have invested in creating brand recognition and building trust with consumers
• Reduced delivery costs.
  • Customer support functions are already provided by Suppliers
  • Suppliers already securely process Smart Meter data
• Increased reliability through the use of an inherently scalable and resilient technical architecture.
• Increased security by eliminating a single big target, which would be attractive for hackers and has the potential to affect all consumers in the UK.

Q3. Do you consider the security measures referenced in this section, including the access control measures, will meet the requirements of a consent solution holding consumer data? Which additional protections would you recommend?

The ISO standard example is appreciated. However, it is also a closed standard which can be prohibitive for some organisations. As such, we suggest Ofgem follow best practice to always additionally reference an open standard to ensure optionality (and lay out an understanding why a standard is considered equivalent or acceptable). We have the following additional comments: 

• In addition to security certifications, such as ISO27001 and Cyber Essentials, we recommend mandating specific technical security standards. These must be agile to respond to changing security requirements and threats. An example is FAPI, which mandates specific security choices with sufficient implementation flexibility to be practical in most environments.
• We believe it is worth noting that where participation in society or consumption of common goods and services requires the occasional interaction with a well-known statutory body, scammers will use this expectation and trust to exploit consumers. Ensuring smart meter owners are well-informed as to the security threats and understand how to recognise and avoid them will be an additional communication and support burden on a centralised consent management body. We suggest awareness of:
  • HMRC has published a list of common methods scammers use to impersonate HMRC.
  • The threat of disconnection of electricity is a powerful motivator to engage with a phishing email.
• The benefits of renewing consent every 12 months may be outweighed by disadvantages and risks. We recommend a risk/benefit analysis to ensure these are balanced, noting:
  • a renewal process gives an opportunity for phishing scams
  • a renewal request which comes from an organisation the user does not know is likely to be ignored, breaking data flows.
• Using MFA for security is good practice, but with a centralised consent hub, it requires a new login and authentication method which introduces friction. This would be unnecessary if the smart meter owner authenticates via an existing Supplier account, which will already have appropriate security measures.
• We encourage working closely with NPSA and NCSC to ensure their feedback is incorporated.
• We suggest performing an adversarial analysis to highlight gaps, and within this, prioritise consideration of vulnerable customers.

Q4. Do you consider these standards are sufficient parameters to ensure inclusivity, accessibility and interoperability for the consent solution? Which standards would you recommend?

IB1 suggest addressing the following comments on inclusivity:

• We recommend support for other languages (Welsh, other languages used in the UK)
• We strongly suggest considering how the consent solution leads to digital exclusion, and compound exclusion
• We encourage a measurement of diversity which will be considered with design, including disabilities, excluded from the Equalities Act like dyslexia, or options for text dictation.

Q5. Do you agree with the options assessment conducted by Ofgem? If not, why? 

We would value more insight as to why the assessment is limited to retail energy sector organisations, and does not include other well established and evidenced successful consumer facing organisations for consideration. We would suggest taking a broader view, and consider other classes of organisation that have regular, secure contact with consumers.

Q6. Do you agree with Ofgem’s minded-to position that RECCo should be selected as the Delivery Body for the consent solution? If not, which of the three proposed organisations should be selected as the Delivery Body for the consent solution, and why? 

We are currently unable to agree with the selection of any Delivery Body due to the following constraints:

• As stated in our response in Q5, we would appreciate more robust evidence as to why other organisations were not considered for this role
• We suggest an opportunity for the three organisations (DCC, RECCo, Electralink) to respond publicly to additional matters raised via this consultation before being able to indicate a fully informed opinion

Q7. Do you hold any views as to how the proposed solution should be funded? Please consider the points regarding fairness raised in paragraphs 4.12–4.14 and Ofgem’s duty to consumers when providing your answer. 

We have no comment on this. 

Q8. Do you agree with our position to make sharing consent data with consumers (via the consent solution) an obligation for licensees? 

We suggest any chosen consent mechanisms are adequately interoperable to be a part of a new obligation. At present we are not confident the suggested solution is adequately interoperable. We suggest the potential for a phased approach.

We also highlight a potential point of confusion for consumers if consent, which has been granted via other mechanisms, is displayed alongside direct consent which they have the authority to withdraw. We suggest clearly articulating to consumers how consent has been granted (if, for example, it has been granted via other means) and therefore what authority they have to withdraw this consent. 

Q9 Do you consider SLC 0 an appropriate route for implementing these changes, or should Ofgem create a bespoke licence condition?

We have no comment on this.

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 openenergy@ib1.org.

Consultation / call for input response:

A1.1 Q1. Do you see potential uses for the DSI within your day-to-day operation in the energy sector? 

Through our UKRI Modernising Energy Data Access competition-winning programme Open Energy, Icebreaker One (IB1) identified and articulated the need to make it straightforward to find, access and share energy data. Through three phases, IB1 convened 100s of organisations, 500+ public webinar attendees, and over 80 Steering and Advisory Group members to develop operational services for search and access control that are now live and market-facing, and have set the foundations for an Energy Trust Framework. Open Energy makes it easy to search for (via https://openenergy.org.uk), discover, access and securely share energy data using a Trust Framework and any Schemes which are built within the Trust Framework context. It covers Open Data, commercial Shared Data with pre-authorised access controls, and commercial Shared Data where access requires end-user permission/consent.

What are Trust Frameworks and Schemes?
Working on behalf of its public and private sector members, Icebreaker One operates Trust Frameworks and Schemes across a variety of sector specific and cross-sectoral domains. Trust Frameworks operate at the level of a defined governance domain (e.g. sector or geography) to collaboratively establish and maintain a light layer of identity management, governance, definitions, principles and Open Standards for data sharing. 

Schemes – which operate within a Trust Framework environment – are defined through structured programs to facilitate and govern the sharing of data among participating entities in the context of a specific use case, or set of related use cases. They collaboratively define the rules concerning what data can be shared, why (purpose), by whom (roles), and how (technical requirements, legal structure, etc). They also address the communications requirements of the Scheme and its relationship with the surrounding policy, regulatory, and legislative landscape. The structural operation of Schemes, linked to specific Trust Frameworks, is capable of supporting the progression of multiple data-sharing  initiatives with distinct needs (e.g. security requirements, personal data protection etc), whist ensuring interoperability, conceptual cohesion, open market development, transparency, and good governance principles (e.g. fairness, value-sharing, protection of data rights) across the wider Trust Framework domain.

The development of Trust Frameworks and Schemes by IB1 builds from existing bodies of knowledge and experience established by initiatives such as Open Banking, cross-sector governance initiatives such as the Smart Data Council, and expert knowledge bases within academic and industry research. Icebreaker One’s work to date demonstrates that Trust Frameworks and Schemes provide a robust but flexible approach to the governance of data sharing infrastructure which is adaptable across multiple use cases, sectors, and governance domains. IB1 has worked with use cases and organisations spanning cross-sector spaces as well as energy, water, finance, insurance, transport, and supply chains sectors. It is working with Open Banking Limited on interoperability between Open Energy and Open Banking.

Relevant energy use cases

IB1 has identified and documented a wide range of use cases and benefits associated with trusted energy data sharing: 

• IB1 is part of the governance design team for the DSI 
• Electric Vehicles (EV) On-Street Charge Points
• Electric Vehicles (EV) DNO Demand Management
• Heating, Residential Property Developer
• Local Authority LCT decision making
• NIMBUS project: Using network innovation and meteorology to build for sustainability
  • Discover Phase report
  • Alpha Phase report
• Rapid Evaluation Areal Connection Tool (REACT) project: to provide users the ability to view electricity grid requests in real-time, using an interactive visualisation map.
  • Discover Phase report
  • Alpha Phase report

Icebreaker One convenes the cross-sector Perseus Scheme (ib1.org/perseus) to enable automated carbon emissions reporting for every SME in the UK. It creates the rules and processes that make automated reporting possible to enable products and services such as accounting platforms, emissions calculators, and reporting software to be developed that deliver higher-quality emissions data at scale. Perseus convenes hundreds of cross-sector organisations to ensure user needs and barriers from across the supply chains are captured and incorporated into the Scheme. 

The Scheme includes participants including SmartDCC, Perse, Sage, Visa, Lloyds Banking Group, to ensure strong alignment between the energy and financial sectors around Smart Data governance. It is additive to existing initiatives.

IB1 co-chairs the Stream initiative to ensure interoperability between the water and energy sectors and has launched a Water Sector Trust Framework to support the sector. 

A1.2 Q2. Do you have any comments on the funding mentioned within this section? 

We welcome the commitment outlined in 2.49 to investigate the long-term business model for the DSI. Early agreement on a sustainable and fair revenue model for the long term will enable commercial considerations to be worked into the technology, legal and governance design while use of the DSI is at a smaller scale and changes can be more easily coordinated with members.

We have seen other data sharing infrastructure initiatives struggle and even fail once government or philanthropic support is withdrawn. Defining a commercial model that balances the cost and value to a wide spectrum of participants as well as to wider society is a complex task. We recommend that a dedicated research stream is funded early in the MVP period to convene stakeholders and undertake discovery and design work to ensure the DSI can be self-sustaining when it reaches the business-as-usual stage.

Q3. Do you have any comments on the timeline shown? 

The proposed timeline does not present clear justification for a 4 year interim governance period nor a clear vision for what a transition to ‘steady state’ from 2028 might look like. We would appreciate if further information could be provided to justify the reasoning for why:

• Four years of interim governance was selected as a specific time period (acknowledging that the consultation outlines some flexibility to move to a longer term solution more quickly under certain conditions)
• A scope of how arrangements are envisaged to change in 2028 (i.e. whether a complete change of responsible organisation would be acceptable or whether this is anticipated to transition to business as usual within a similar structure)
• A general vision of how the change management to steady state might be arranged (e.g. Ofgem mandate or licence change, industry decision-making process, etc)
• The envisaged relationship between the technology assessment and the change to steady state governance, noting that it would not be appropriate for program governance to be determined primarily by technical architecture
• Why Ofgem has proposed an interim coordinator rather than a governance structure which is capable of iterating flexibly over time.

Icebreaker One has substantial experience of setting up and running robust, industry peer- reviewed governance processes for a range of programmes with different constellations of stakeholders, user needs, and technological arrangements. From our experience, the most successful models incorporate governance from a project’s outset in a manner which leaves room/flexibility to iterate over time to suit programme needs. Such models also provide checks and balances from the outset, enabling programs to assess and respond to a wide range of socio-technical considerations rather than being shaped primarily by (changeable) technological factors. 

As digitalisation of the energy sector, and indeed the wider economy, accelerates it is essential that any governance mechanism is built to function flexibly within a shifting technical landscape. It is also essential that any governance mechanism is built to be 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. The Smart Data Bill is anticipated to pass into primary legislation in 2025 and will accelerate the need for robust data sharing governance.

 While transparency and predictability of process is important to any governance mechanism, we would caution that 2028 provides an arbitrary milestone to reach a level of governance permanence that is unlikely to reflect ongoing change within the surrounding social, economic, technical and environmental landscapes. We suggest that existing initiatives, such as Open Energy, are already delivering elements of this solution and could accelerate the implementation of data sharing schemes. 

Q4. Do you agree with our short-term governance structure model where the Interim DSI Coordinator is responsible for leading the short-term governance (2024 – 2028) of the DSI? 

As outlined in the response to Q3, we strongly recommend a model which builds governance into the project from its outset, allowing for iterative development where appropriate using consultative mechanisms. If the points above are clarified it may be that Ofgem’s proposal aligns with these recommendations, however this is not possible to assess without further information. 

Furthermore, we recommend that the proposed governance vehicle is (re)assessed in consideration of the following two points.

Firstly, elements of the consultation are currently phrased in a manner which may risk  data infrastructure governance decisions pushing contingencies onto wider elements of future digital governance (e.g. hardware, software, network infrastructure, cybersecurity, etc). This risk is heightened if the consultation is considered in light of proposals published in parallel by National Grid ESO, illustrating how DSI governance could be subsumed into a proposed ‘Digitalisation Orchestrator’ operated by the National Energy System Operator (NESO). When Ofgem makes its decision regarding DSI governance, it is vital that this decision is limited to the purview of DSI governance only and does not conflate, nor set definitive future expectations or structures for, the locus or type of governance applied to other domains of energy system digitalisation. We strongly suggest, drawing from a growing evidence base in academic research, that digital governance is appropriately atomised, to avoid risk associated with homogenising the needs of different domains. This will help ensure that structures are built to effectively manage factors such as: relevant and balanced stakeholder engagement; vested interests and power dynamics; technological, design, or skills needs; integration with Net Zero and other policy goals; and relationships/interoperability between different digital governance domains within and across particular economic sectors. Further research, and open consultation, is required to achieve this effectively and transparently.

Secondly, relating specifically to governance of the DSI, we suggest that the governance needs of the Trust, Prepare and Share nodes are more transparently assessed prior to overarching decisions being made. This assessment should incorporate where there are clear differences between the needs of individual nodes (e.g. governance of data rights in the ‘Trust’ node is likely to implicate the involvement of legal professionals which may not be required to implement more technical aspects of the ‘Share’ node) and where there is a need for the nodes to act in concert (e.g. technical interoperability or security principles). This suggestion for atomisation is underpinned by the principle of separating the governance of data rights from that of the technology(ies) that will be implemented to enable sharing. While these elements will retain some crossover, it remains important that governance is genuinely sociotechnical and does not become unintentionally led by technological considerations by default.

In assessing where governance is approached separately/collectively, we suggest that Ofgem, or the proposed DSI governance body (and any subcontracted entities), may find it helpful to consider the below (non-exhaustive) factors such as:

• Goals/aims: How are goals defined and set? Who is involved? How is the balance of goals assessed across technical, socio-economic, and environmental domains? Is there potential for goal conflict across the different nodes and, if so, how will this be managed?
• Coordination: how will the DSI coordinate with developments within and beyond the energy sector? How will this feed into goals, design choices, and definition of technical/architectural parameters? How might this need to evolve over time?
• Roles and responsibilities: How are roles and responsibilities defined? Do these differ across each node or are the same roles/responsibilities universal? 
• Change management: How will change management processes work across the DSI and component nodes? Are there different stakeholder or technical requirements for separate processes across different nodes? Are different stakeholders (i.e. with different roles or areas of expertise) required to co-construct and/or sign off changes to different parts of the DSI? (e.g. strategic, commercial or legal input may be needed to sign off changes to the Trust node, while more technical aspects of data preparation may require CTO/CDO input).
• Communications: If different stakeholders are involved in different nodes of the DSI, how are these stakeholders engaged and communicated with? Do they have different communication needs that must be built into governance processes or cadences?

Q5. If not, state your reasons and propose an alternative governance model or improvements to our proposed solution. 

Our contributions are captured jointly within Q4 above. We further suggest that the options presented in Ofgem’s consultation are revisited in light of a more atomised approach to governance, which is potentially overseen by the body proposed in the current consultation. 

We additionally suggest that Open Energy be formally considered as a vehicle for the governance of the Trust Framework node. Open Energy, funded by public money and coordinated by the non-profit body Icebreaker One, has been specifically developed for this purpose using a combination of radically transparent methods of open working, extensive consultation with stakeholders, and the input of specific domain expertise from energy industry, academic, and Open Banking specialists. Icebreaker One  has already been involved in the DSI as the governance advisory partner, and is involved in the MVP through inputting into the pilot development, and use case exploration. It already has DNO and energy sector members. 

Our work to date provides strong justification that the DSI is compatible with the structural model of Trust Frameworks and Schemes initially developed through Open Energy and subsequently advanced through Icebreaker One’s programmes such as Perseus and Stream. 

Q6. Are there any additional governance roles that are not covered by the proposed governance model? If so, what are these? 

We have identified gaps in how the consultation currently presents the governance body’s roles surrounding how rules are established, overseen, enforced, and changed within the DSI. These must be explicit and transparently codified roles of the governance body and must also detail under what circumstances any of these roles can be delegated and/or subcontracted to specialists.

Accordingly, we recommend that the roles are expanded to include definition of processes and/or rules for the establishment, oversight, enforcement, and change of:

• Stakeholder mapping, engagement and representation
• Goal setting
• Defining success criteria (across technical, socio-economic, and environmental domains)
• Monitoring, reporting, and verification (MRV)
• Change management
• Communications
• Dispute resolution
• Liability and redress
• Any formal responsibilities towards meeting cross-economy policy goals such as:
  • Net zero
  • Industrial strategy
  • Social policy

We further recommend that roles are included to oversee – where not already covered by another body in the broader environment – the definition of processes and/or rules for the establishment, oversight, enforcement, and change of:

• Data rights
• Adjacent agreements (e.g. DSI membership contracts / terms of use)
• Guidelines (e.g. antitrust, fairness, transparency, publishing)

Finally, we suggest that the governance body should have an active and transparent role in defining formal and informal relationships with adjacent bodies in the energy sector and beyond. This role may include jointly establishing and maintaining:

• Channels of communication 
• Obligations on reporting or information sharing
• Formal processes and roles for engagement (e.g. assignation of ‘observer status’ in certain governance fora)
• Approaches to sharing and/or allocating roles when approaching shared issues 
• Appropriate accountability structures
• Approaches to reduce forum proliferation (and ensuring associated fair access to governance fora for smaller organisations with less resource)
• Approaches to contributing or responding to cross-sectoral policy and regulatory developments in a joined up manner.

The suggested role changes above imply a set of associated responsibilities which are outlined in the sub-bullets, some of which exceed the responsibilities stated explicitly within the current consultation. Many of these responsibilities are likely to constitute oversight rather than design/delivery, allowing for subcontracting arrangements to take place where required. In addition to responsibilities outlined above, we suggest that the DSI governance body holds responsibilities for the oversight of:

• User needs identification, testing, and convening
• Assessing and measuring impact across socio-economic, environmental, and technical domains
• Where impacts are undesirable, performing impact mitigation 
• Ensuring cohesion (of procedural, legal, technical approaches)

Implicit across all our suggestions is the principle that key roles and responsibilities of the Interim DSI Coordinator – and indeed any longer term governance body – are expanded to explicitly include reference to the wider socio-technical landscape. We suggest that codifying these responsibilities would provide an improved balance between technical, social, and operational elements of the DSI governance, while also strengthening the mandate of the proposed body. While not all areas of responsibility need to be undertaken directly by the proposed governance body (e.g. it may be possible to subcontract an appropriate body to support stakeholder engagement) we strongly suggest that the following (non-exhaustive) points would benefit from more formalised oversight, governance integration, and appropriate resourcing : 

• Data rights and surrounding legal structures governing the exchange of data and associated intellectual property
• Stakeholder engagement and communications
• Cross-sector, policy and regulatory input/coordination (including social, economic, and environmental factors)

Q7. Do you agree with the responsibilities of the interim DSI Coordinator? Are there any additional responsibilities that it should undertake? 

Our response to Q7 is integrated with the discussion of roles outlined in Q6 above.

Q8. Do the proposed deliverables reflect the outputs that the Interim DSI Coordinator should focus on in the initial DSI stages? Do you suggest any additional deliverables?

IB1 strongly recommends that all deliverables below should be published openly, along with any accompanying processes, and methodologies. We have further comments on specific deliverables outlined below:

• Annual report on existing and future use cases:
  • We request further information as to what the annual report will contain other than information regarding the use cases. This may include:
    • Any reporting on the progress of use case delivery
    • Any assessment of the impacts of delivering a use case (both pre-emptive assessment and measurement over time) 
  • We request further information on:
    • The criteria on how use cases are gathered, defined and assessed
    • The prioritisation and funding criteria to deliver specific use cases
  • We suggest that engagement KPIs are published as part of annual report and alongside applicable knowledge base content (e.g. voting outcomes, issue resolution etc)
• Statement of staffing interim report (2026):
  • We suggest that this report should be transparent about subcontracting fees
  • We suggest the budget which is being worked against should be openly published
  • We suggest that this report should continue to be regularly published through the steady state governance mechanism
• Knowledge base:
  • The time frame for this deliverable is unclear and the baseline expectations for what a knowledge base would constitute, or how it would be managed (e.g. iteration) are not yet transparent.
  • We suggest that the knowledge base must be integrated with stakeholder engagement processes, bringing transparency for example to documentation of meeting minutes, votes, and decisions. 
  • We suggest the evidence base, data, and accompanying processes, and methodologies should be published openly where possible
  • We suggest that the knowledge base must be accompanied by clear processes for change management 
  • We suggest that funding structure and specification of new research should be published openly
  • We recommend that use cases must be findable, accessible, and have clearly articulated value/impacts and actors. This will require good information management.
• Technology assessment (2028)
  • We suggest the assessment should be in relation to the identified use cases, address user needs, and address corresponding socio-technical landscape and fit
  • We suggest that the technology assessment is integrated with an assessment of economic feasibility in the short and longer term (e.g. transparency regarding capital expenditure, expected BAU running costs, and costs associated with expected iteration/adaptation)
  • We suggest that basic definitions/glossary of technologies assessed must be provided
  • We suggest that the landscape of potential technology providers should be assessed transparently, in line with a competitive, open market approach
  • We suggest that the assessment includes more in depth information setting out the DSI’s tender/contracting processes (if this is not published elsewhere)

We also suggest that the DSI should have the following additional deliverables:

• Service desk
  • To assist DSI users with commercial, procedural and technical queries
  • To provide technical support in the case of bugs, security incidents or outages
  • To handle formal complaints and disputes
  • To assist in, or signpost appropriate external support for, legal queries
  • To signpost stakeholders to use cases
  • Potential account management function for high-volume users such as regulated entities
• A defined engagement programme and forum for ongoing DSI stakeholder participation. This may include processes for:
  • Eliciting new use cases
  • Co-designing solutions to selected use cases
  • Iteratively improving solutions to use cases
• Monitoring infrastructure
  • This constitutes a mix of technical and audit-based controls to ensure DSI is correctly operated, and used by members.

Q9. Do you agree with us that the System Operator is the best option as the Interim DSI Coordinator? If no, explain your reasons and justify your proposed option. 

While we do not have in-principle objections to the System Operator (NESO) holding a DSI oversight function, we want to highlight the risk that this consultation requires respondents to make a decision on the basis of incomplete information (particularly pertaining to governance atomisation, roles, responsibilities, and deliverables). We would be happy to reconsider our response once further information has been provided. We also strongly recommend that  Ofgem consider a wider range of delivery bodies for the atomised roles, even if the System Operator is assigned the temporary governance/oversight role, it (or Ofgem) should be able to delegate or subcontract these roles to existing solutions. This is of additional importance when cross-sector governance is being considered. 

Q10. What assessment criteria do you foresee being required when transitioning from short-term governance to an enduring governance model? 

It is difficult to provide feedback on assessment criteria for transitioning to an enduring model before seeing how the interim governance model is working, and the degree to which the governance model will change after the interim governance period. However, we would suggest the following principles for inclusion:

• Ensure the governance model reflects the socio-technical nature of the energy sector, not just the technical side 
• Ensure sector integration, and the importance of working with cross-sector efforts
• Reflect the importance of clearly defined user needs, the enduring governance model must match to these
• Identify a transparent, sustainable and fair financial model

Q11. What suggestions or feedback do you have for refining these governance assessment criteria to better meet the requirements and challenges of digitalisation in the energy sector?

We suggest including considerations of how digitalisation affects:

• Net zero and the wider environment
• Society
• Business models
• Customers

As the digital landscape develops further, we also suggest that assessment criteria may benefit from considering:

• How the DSI interacts with advances in the governance of algorithms, AI, and other emerging technologies
• How use cases are identified, developed, and assessed beyond the interim governance model (this also implicates assessment of how engagement and research are conducted and resourced in the longer term)
• How future resourcing and staffing needs are regularly checked in the longer term
• How tender and contracting relationships are assessed in the longer term

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 openenergy@ib1.org. We have omitted questions which we did not answer.

Call for input response:

1. Do you agree with the overall approach to identify how the five AI principles are captured by the current legislative and regulatory framework that applies to the energy sector?

We are particularly interested in your views around the extent current licence obligations capture either directly or indirectly the five AI principles.

Icebreaker One comments on the five AI principles laid out:

Accountability and governance principle: 

Responsibility does not explicitly mention the data ecosystem used around AI (though data is mentioned separately under auditability and it is tacitly inferred under liability). IB1 recommends that the data ecosystem, and integration with the data governance landscape, is explicitly rather than tacitly acknowledged.

There is no mention of AI, energy and the connection with the UK’s net zero / climate targets. IB1 believes this is a key part of governance and we would encourage codification of this. We recommend that the developing AI governance landscape codifies a requirement for AI use in the energy sector to demonstrably contribute to the UK’s net zero targets and for this requirement to be open to monitoring and audit. Without codification of this principle there is a risk that AI systems are established to optimise non-environmental goals, while creating negative environmental impacts. 

There is also a risk of AI systems generating large – possibly unnecessary – increases in energy demand. Both the impacts and the demand profile of AI use in the energy sector should be subject to scrutiny and appropriately governed to ensure they contribute meaningfully – or at the very minimum do not actively harm – the UK’s net zero targets.

Contestability and redress principle

The role of data governance will also affect this principle. Data governance is complex, and is likely to become even more so with AI. This should be better integrated into the principle to ensure that parallel mechanisms are not created which risk assigning different stakeholders different rights and processes that could overlap or contradict each other.

Fairness principle

Ofgem’s information session suggested that AI governance could adopt definitions of fairness that already exist in energy sector regulation. This is problematic for two main reasons:

1. There are multiple, different, definitions of fairness used in different parts of the sector and energy governance. This holds the potential to create confusion or gaps.
2. Existing regulatory definitions of fairness focus primarily on economic fairness, conceptualising a view of people as primarily individual ‘consumers’. IB1 strongly advocates for the adoption of a broader concept of social sustainability in defining fairness. This must conceptualise people in a manner beyond their economic roles and should also be capable of viewing people in terms of groups. This approach is vital to assessing a more holistic range of AI impacts beyond the individualised economic sphere. The approach can also be actioned in AI governance to ensure that governance is co-designed through processes which are adequately representative of different stakeholders or stakeholder groups, ensuring that the approach is collective rather than ‘done to’ from the top down.

There is a separate risk that fairness and bias become concepts that are conflated, when in fact they are very separate. For example, fairness is a contextual value judgement that can coexist (or indeed encourage) some degree of bias (e.g. positive discrimination) depending on the envisaged end goal. Further work is required here to produce clear and separate definitions of the two concepts.

2. Do you agree with the initial findings around the potential issues or challenges of applying the AI principles in the energy sector?

We are particularly interested in your views around the novel issues we have identified, the multi-regulatory framework and monitoring and enforcement implications.

We recognise this is a standard approach to risk management. However, there is some issue around definitions of ‘some’ or ‘most’ etc which do not leave much scope for identifying risks that are particular to certain groups/parts of the sector (i.e. not a majority, but still important). This has the potential to not account well for potential other single points of failure. 

3. Do you have examples of AI use cases within the energy sector in Great Britain or elsewhere that we have not included?

N/A for IB1

4. Do you agree with the factors we have identified that could inhibit the adoption of AI in the energy sector?

IB1 would include the concept of trust as either an enabler or inhibitor of the adoption of AI in the energy sector. A lack of trusted data flows into AI systems could lead to poor, potentially unaccountable, decisions made or informed by machines and human-machine systems. This increases risk and difficulties in quantifying and investing in the transition to net zero. Better data infrastructure – including licensing, assurance, and security – will make it easier to make net-zero decisions at speed, with confidence and at a global scale. This includes decisions made by machines and human-machine systems.

5. Do you agree with our proposed approach to evaluating the risks associated with the use of AI in the energy sector?

Currently, there is a lack of attention to the data foundations and their transparency and accountability. This is key for use of AI within the energy sector. 

6. Do you agree with how we have approached evaluating risks from a consumer perspective?

We would particularly be interested in your views about the issues of fairness, ethics, transparency and explainability.

No, we would support integration with data governance at both consumer and sector levels. IB1’s approach to data governance is designed to support the long-term, cohesive and sustainable development and delivery of data-sharing programmes. We believe it is important for data governance to establish principles, structures, roles and responsibilities, agreed upon by market participants, that enable accurate and timely data sharing at a market-wide scale.

As previously touched on in question 1, IB1 raises the concept of social sustainability to be included. IB1 supports co-designed data governance, with the voices of stakeholders represented to ensure the approach is collective, rather than ‘done to’ from the top down. We advocate for this approach to also be taken to the development of AI regulation in the energy sector. 

7. Do you agree with how we have approached evaluating risks from a market perspective?

We would particularly welcome your views about the issue of algorithms and collusion, and interoperability with international markets.

IB1 would encourage interoperability with international markets. 

8. Do you agree with how we have approached evaluating risks from a company perspective?

We would particularly welcome your views about the issues of governance, accountability and redress, safety, security and robustness, and cyber.

N/A for IB1

9. Do you agree with how we have outlined the risks from a sustainability perspective and the need for guidance for the energy sector on its sustainable use of AI?

As outlined in question 1 for the accountability/governance principle, there is no mention of AI, energy and the connection with the UK’s net zero / climate targets. This is a key part of the emergent AI governance landscape and we would encourage codification of this accordingly.

10. Do you agree with our proposed recommendations?

Icebreaker One supports collaboration being a core aspect of developing Ofgem’s AI Strategy, and echoes the importance of a cross-industry forum to co-design the strategy. 

11. Are there any issues that are not covered by our recommendations?

As outlined throughout this response, IB1 advocates strongly for two additional areas of inclusion. Firstly, we suggest Ofgem’s work on AI governance to integrate with developments in data governance, both within the energy sector and in the cross-economic space (e.g. Smart Data Roadmap, approaches to consent or permission). Secondly, we suggest that Ofgem codifies the relationship and responsibilities of the AI governance landscape in support of the UK’s net zero and climate targets.

IB1 also offers one more general comment. On reviewing Ofgem’s Call for Input and AI Strategy, it is clear that the boundaries of this regulation are both highly political and yet to be determined. Both the AI landscape and the underlying data landscape are highly fluid and increasingly driven by cross-sectoral actors, data flows, use cases, value chains, and supply chains. IB1 suggests that the exact scope of AI regulation in the energy sector, and its integration with cross-economic developments in the data and digital governance spheres, requires further discussion which must involve an appropriately broad range of stakeholder engagement. Without this process of boundary setting and cross-sector interoperability of rules, there are risks that energy sector regulation could either lack sufficient ‘teeth’ to be effective, or could leave gaps which enable ‘bad actors’ to exist in unregulated but impactful spaces. We note that similar conversations are being had in other sectors – e.g. financial markets – where the use of AI is accelerating and that there would be benefit in coordination in this space. 

12. Should certain recommendations and issues be prioritised over others?

Icebreaker One supports collaboration and sector buy-in being a core aspect of developing Ofgem’s AI Strategy, and echoes the importance of a cross-industry forum to co-design the strategy. 

Background

Icebreaker One, in partnership with SSEN Transmission, IBM and Palantir, is working on the NIMBUS (Network Innovation and Meteorology to BUild for Sustainability) project, which aims to accelerate the transition to net zero by prolonging the life of energy assets through the introduction of granular weather data sources into the asset risk modelling methodologies. The NIMBUS project is funded by the Ofgem Strategic Innovation Fund (SIF), the SIF is delivered in partnership with Innovate UK.

In this consultation we present key findings from NIMBUS regarding the asset data sharing practices in the UK energy sector and the use of granular weather data as part of the CBRM (Condition Based Risk Management) methodology. 

We seek your input to ensure that we capture a wide range of expertise and views that reflect the data sharing landscape relevant to the NIMBUS use case, specifically pertaining to data on energy asset management. The proposals  presented in this consultation draw from prior NIMBUS project work incorporating desk research, Advisory Groups convening various members of TSO and DNO organisations, and stakeholder interviews to evaluate the current landscape of asset data sharing and the approaches to CBRM in the sector.

Important Details about the Consultation below:

• The consultation is open until 5pm on 12 March 2024. 
• Please submit your responses to: julija.hansena@ib1.org
• In your response , please indicate whether you are happy for your response to be published openly, attributed to you and/or your organisation. 
• If confidentiality is requested, your submission will be anonymised when Icebreaker One publishes their response. Please email Julija to discuss if you have specific anonymity requirements. 
• Comments are particularly encouraged from all transmission system operators (TSOs) and distribution network operators (DNOs) in the energy sector, however responses from utilities with similar assets such as water, rail and telecommunications are also welcomed.
  

Proposal

Through analysis of data gathered via Advisory Groups, stakeholder interviews and desk research, we have identified the following approaches to asset data sharing and the use of CBRM in the energy sector:

Statement 1

The sector is generally embracing the concepts of open data and data sharing, especially since the publication of Ofgem’s Data Best Practice Guidance which promotes data sharing and reuse. Many TSOs and DNOs have created their own open data portals (e.g. SSEN-T Open Data Portal, SSEN-D Data Portal), however there is still a noticeable lack of shared data standards, methodologies and tools that govern asset data sharing in this sector.

Questions about Statement 1: 

1. What is your organisation’s experience of sharing asset data?
2. Are there any data standards, methodologies or tools that are used in your organisation to facilitate data sharing and publication of this type of data? 

Statement 2

CBRM is a widely utilised methodology across the energy sector to facilitate asset risk management and reporting. However, asset managers report that it is somewhat limited in its approach and may well benefit from integrating weather data experienced locally by assets into the asset risk modelling process. Project NIMBUS aims to address this by assisting to integrate granular weather data into asset risk assessment methodologies, with the aim of optimising asset inspection schedules and subsequently reducing asset degradation and the associated costs.

Questions about Statement 2: 

3. In your organisation, are weather conditions experienced by assets currently integrated into the asset risk assessment methodologies?
4. If so, have you been able to measure and quantify the impact this has had on your asset inspection and maintenance cycles and the associated costs?

Statement 3

TSOs and DNOs handle large volumes of data of various levels of sensitivities, which need to be handled appropriately. In order to assist with data security, as well as enable data sharing between organisations, a framework like data sensitivity classes can be applied. For the NIMBUS use case, SSEN-T Open Data Portal makes use of a data triage process which is applied to all SSEN-T datasets prior to publication, with the results of the triage processes being published here. The data sensitivity classification framework that forms part of this triage process is closely aligned with IB1’s data sensitivity classes, whilst simultaneously adopting the classes to fit the needs of the business.

Questions about Statement 3: 

5. Are there any existing data triage processes or frameworks that aid in assessing data sensitivity levels of asset data in your organisation? 
6. Are they based on any existing processes or frameworks?

How can you help?

We are seeking responses to the 6 questions listed in the ‘Proposal’ section above. It should take no more than 30 minutes to respond. The consultation is open until 5pm UK on 12 March 2024 and responses are encouraged from all transmission system operators and distribution network operators in the energy sector, as well as adjacent organisations working on matters relevant to the NIMBUS use case.

To submit your responses, or if you have any queries please email: research@ib1.org