Analytics for Digital Earth - Workshop 6

Dates: 11th March 2025

Time: 9.30am

Location: Bridie Library, Glasgow University Union (GUU)

The final Royal Statistical Society Mardia Prize Analytics for Digital Earth event brought together experts from academia and industry to explore the role of digital twins in tackling environmental and infrastructure challenges. The event highlighted cutting-edge applications of digital twin technology in critical infrastructure, coastal ecosystems, agriculture, and subsurface characterisation.

Speakers and Topics:

  • Prof David Flynn (University of Glasgow) – Digital Twinning of Critical National Infrastructure
  • Prof Matthew Palmer (Plymouth Marine Laboratory) – SyncED-Ocean: Towards a Digital Twin Coastal Ocean Ecosystem
  • Prof David Wagg (University of Sheffield & Alan Turing Institute) – AI and Data Science for Digital Twinning: A Research Overview
  • Prof Paul (Harry) Harris (Rothamsted Research) – Perspectives on the Quantification of Uncertainty in Agricultural Digital Twins
  • Dr Roisin Buckley (University of Glasgow) – Towards Intelligent Subsurface Characterisation for Infrastructure Projects

Key Discussions:

The discussion panel explored the evolving role of environmental digital twins, emphasising their potential to transform environmental monitoring and decision-making. Panellists debated the balance between model complexity and efficiency, the challenges of integrating AI and multi-scale processes, and the importance of ensuring transparency, reliability, and accessibility.

Financial and ethical concerns were central to the discussion, with questions raised about cost-effectiveness, data privacy, and the risks of adversarial use. Collaboration emerged as a key theme, highlighting the need for stronger partnerships between governments, academia, industry, and communities to drive research and implementation. Looking ahead, panellists identified major gaps in scalability, standardization, and interoperability, stressing the need for robust uncertainty quantification and data fusion.