Business & Technology
Public sector urged to put data provenance at AI core
Butterfly Data has urged public sector organisations to put data provenance at the centre of AI development, arguing that the issue goes beyond conventional data quality work.
Maja Strawinska, a data scientist at Butterfly Data, said teams often assume cleaner data will resolve concerns about fairness, accuracy and governance. But even a well-structured dataset may be unsuitable for AI if organisations cannot explain where it came from, why it was collected, and whether it can lawfully and appropriately be reused.
She drew a distinction between clean data and trustworthy data, particularly in the public sector, where automated systems can affect access to services and care. In that context, the history of a dataset matters as much as its format or completeness.
At the centre of her argument was a simple question: can organisations explain the origin of the information they use? That means knowing who collected it, under what conditions, for what purpose, and whether those circumstances create risks for its current use.
Source matters
To illustrate the point, Strawinska compared data provenance with the farm-to-table approach in food. In both cases, trust depends not only on the end product, but on a clear account of the supply chain behind it.
This carries particular weight in the public sector, where many datasets have built up over time through legacy systems and older processes. Data may later be migrated, standardised and corrected, but those technical improvements do not answer questions about the original basis for its collection or the terms under which it may now be used.
“The important question we need to ask is simple: where did this data actually come from?” Strawinska said.
The issue also extends to compliance and oversight. Provenance, she argued, should not be treated as a narrow technical matter, but as a core part of responsible AI, with direct relevance to data protection obligations and growing scrutiny from regulators and oversight bodies.
Her comments reflect a wider shift in AI governance, especially in government and public services, where organisations are increasingly expected to explain not just what a model does, but the foundations on which it was built. In that context, a data audit trail becomes part of the case for deploying an AI system at all.
Limits of cleaning
Strawinska said standard data quality work has clear value, from removing duplicates to standardising formats, but it cannot solve every problem. Data collected without valid consent, or for a different purpose, does not become appropriate for a new use simply because it has been cleaned and validated.
She used the analogy of food grown in contaminated soil to make that point. A vegetable can be washed and prepared, she said, but still remain unsafe because of what happened at source. The same logic applies to datasets whose origins create legal, ethical or representational problems.
This may be especially acute for public bodies managing information gathered over decades. Some data was collected before current data protection standards took shape, creating a challenge for organisations seeking to apply modern AI methods to old records.
Bias earlier
Strawinska also raised concerns about the point at which bias enters a system. Debate about AI bias often focuses on model outputs and fairness testing, but distortions may begin much earlier, during the collection and assembly of training data.
If a dataset over-represents certain demographics, regions or periods, the resulting model may reflect those imbalances. She cited examples such as systems trained mainly on urban data that may perform poorly in rural settings, or systems built on data from an unusual period of demand that may fail when conditions return to normal.
For public services, she argued, these limitations should be identified before deployment rather than after the fact. Provenance helps organisations assess how representative a dataset really is and where its gaps may lie.
Audit trail
The challenge grows as AI systems become larger and draw on more sources. The more data that is used, Strawinska said, the harder it becomes to maintain a clear account of who handled it, how it changed, and whether those changes introduced distortions.
She argued that organisations that build provenance tracking into projects from the outset will be better placed when they face auditors, oversight committees and public scrutiny. In the public sector, the ability to explain those decisions is closely tied to trust in how AI is used.
“Data provenance – the ability to trace where data came from, who handled it and how it has changed – is often seen as a niche technical topic. It isn’t. It is at the heart of what responsible AI requires,” Strawinska said.
New store DartSmart set up shop in unit 14 of Templars Square Shopping Centre, Cowley, with a grand opening event on Saturday, August 1.
The small, family-run business has been launched by Dwaine Jackson, an avid player who wanted to create Oxfordshire’s ‘new home of darts’.
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He is supported by his wife, Jay, who helped setting up the store while on maternity leave with their nine-month-old son, from her job as a personal assistant.
Mr Jackson said: “I have a passion for darts and I play regularly in the local Oxford leagues, but I noticed I needed to travel out of Oxford for accessories, or order online with delivery costs and longer wait times.
“So, I wanted to bring an accessible darts shop central to Oxford and surrounding towns to fulfil the needs of the local dart players.”
DartSmart sells premium equipment and accessories for all levels, for beginners to professionals, stocking major brands.
It also offers a trade discount for pubs, clubs and league venues, to support the sport the owner loves so much, and has two dedicated oches so customers can try before they buy.
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A spokesperson for Templars Square Shopping Centre said: “Whether you’re inspired by world-class players like Luke Littler or picking up your first set of darts, DartSmart has everything you need to enjoy the game, from darts and dartboards to flights, shafts and cases.
“Pop in and give them a warm Templars Square welcome.”
DartSmart is open from Tuesday to Saturday, 10am to 6pm, and until 4pm on Sundays.
SOFIAH NICHOLE SALIVIO
News Editor
OneAdvanced has signed a Memorandum of Understanding with Cosine to join the Lumen Sovereign Coalition, which is working on what the companies describe as Britain’s first fully sovereign frontier AI model.
The agreement brings OneAdvanced into a group of companies and institutions helping to shape the model for regulated and essential service sectors. Its role will include contributing use cases, operational requirements, testing scenarios and deployment feedback from industries where its software is already in use.
Those sectors include healthcare, government, justice, education, care and business services. OneAdvanced will use that experience to help define how the model should operate in settings where security, governance and operational rules can limit the use of foreign-hosted AI systems.
Cosine, a London-based AI laboratory, is developing the Lumen Sovereign model with support from a wider industry coalition. Other members include BAE Systems, Babcock International Group, BT, HSBC, Lloyds Banking Group, LSEG, NatWest Group, PwC, The Alan Turing Institute and Vodafone.
The project is backed by the UK Government’s Sovereign AI Programme, which has committed GBP £500 million. The model is due to be trained using the Isambard supercomputer in Bristol.
OneAdvanced’s involvement follows its work on a healthcare large language model developed with NVIDIA and trained on NHS primary care data. That system was designed to improve primary care triage, and the company is positioning it as evidence of its experience in applying AI to sector-specific operational needs.
In healthcare, OneAdvanced says its software supports more than 40 million NHS patients across NHS 111, GP practices and trusts. It also works across local government, education, legal services, transport and supply chains.
Sector input
The tie-up reflects a broader push in the UK technology sector to develop AI systems that can be hosted, trained and audited within the country. For organisations operating in heavily regulated environments, questions about where a model runs, what data it is trained on and who can review its operation have become increasingly important in procurement and deployment decisions.
Cosine says the coalition is intended to ensure the model is shaped by organisations that will use it in real operating environments, rather than by technical teams alone. That means feeding in practical constraints from sectors such as healthcare, local government and legal services.
Cosine framed that goal around control and auditability.
“We’re building Lumen Sovereign because we think the UK needs frontier AI it can actually control: where the model runs, what data trained it, who can audit it. That only works if we build it alongside the organisations running the country’s real, regulated infrastructure. OneAdvanced helps us achieve that goal. Their experience with the NHS, local government, education, and thousands of legal practices means they bring insights into the operational constraints a sovereign model needs to actually be useful,” said Alistair Pullen, Co-founder & Chief Executive Officer of Cosine.
Practical focus
For OneAdvanced, the move also underlines its argument that the next stage of AI adoption in critical services will depend less on general model performance claims and more on whether systems can fit existing workflows, governance standards and data-handling requirements.
The company has been advocating for AI systems designed around UK data residency and domestic control over infrastructure. Its software footprint in public and regulated services gives it a route into organisations that may be cautious about deploying overseas-hosted models in sensitive settings.
Simon Walsh set out that position in his remarks on the coalition agreement.
“We have long advocated sovereign AI as the safest and most secure way for UK organisations to leverage the transformative power of AI in their flow of work. Through our work with NVIDIA to develop the UK’s first sovereign healthcare large language model, trained on NHS primary care data to improve patient triage outcomes, we have seen first-hand the importance of combining advanced technology with deep sector knowledge, robust governance and a clear understanding of the workflows organisations rely on every day. That is why we are delighted to join the Lumen Sovereign coalition.
“Organisations in the UK’s highly regulated and essential service sectors need AI that is not only powerful, but secure, trusted and designed around the realities of the environments in which it will operate. We look forward to working with Cosine and the wider coalition to help turn that ambition into practical capability,” said Walsh.
The club will continue working with AWBS, which will remain as the club’s Official Substitution Sponsor until the end of the 2027/28 season.
Lee Barton, head of revenue at Oxford United, said: “We’re thrilled to announce this enhanced multi-year agreement that will see AWBS continue as our Official Substitution Sponsor.
“We look forward to developing the relationship further during the 2026/27 season.”
AWBS is one of the largest suppliers of building and landscaping materials in Oxfordshire and Wiltshire, with three branches.
The company also has extensive showrooms, a fleet of delivery vehicles, and a dedicated landscape installation service.
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