Event | Conference

DAFNI Conference 2026

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The conference will bring together leaders from government, industry and academia to explore how digital twins, modelling and data-driven approaches can help address some of the UK’s most pressing infrastructure challenges. 
Date 10 September 2026
Location Rhodes House, University of Oxford
DAFNI (the Data and Analytics Facility for National Infrastructure) is a UK research platform led by UKRI / STFC that brings together data, modelling, computing and collaboration tools to help researchers, policymakers and industry tackle complex national infrastructure challenges. It supports work across areas such as climate resilience, energy, transport, water and digital twins, enabling evidence-based decision-making for a more sustainable and resilient future.
This year’s conference is centred on two key themes:
  • Climate and security resilience
  • Government industrial strategy, with a focus on clean energy

Find out more and book tickets here >>

DAFNI Fellow Dr Tom Mansfield, Data Systems Architect at PML, will be sharing an update regarding the work he is undertaking with his DAFNI Fellowship.

As part of the fellowship, Dr Mansfield is investigating how federated data architecture approaches could improve the way environmental and infrastructure data are connected, accessed, and reused across UK offshore wind programmes.

Offshore wind projects generate vast and highly complex datasets spanning environmental monitoring, engineering performance, ocean conditions, and ecological impacts. However, these datasets are often spread across multiple locations, organisations and systems, creating barriers to collaboration and slowing the delivery of actionable insights.

Tom’s research will explore how federated approaches – where data remain securely within organisations while still being accessible and connected across systems – could improve collaboration and support faster, more coordinated decision-making across industry, government, and research communities.

Find out more about this work: PML’s data architect selected for prestigious national DAFNI Fellowship >>

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