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Dr. John Siddorn

National Oceanography Centre, UK

About the speaker:

Dr. John Siddorn is Chief Scientist and Director of Data, Science & Technology at the National Oceanography Centre (NOC), UK. Since joining NOC in 2020 as Associate Director of Digital Ocean; John has championed the embedding of digital approaches to furthering science.

Prior to joining NOC, John held positions at the Met Office where he was Head of the Ocean Forecasting R&D Department (OFRD) group and Co-chair of the National Partnership for Ocean Prediction (NPOP). His research was on developing ocean models with a focus on interactions between the ocean and atmosphere, and understanding how those interactions underpin predictability for climate and high-impact events. He led the Newton Programme’s India project, coordinating work in the Met Office and UK academia with that at the Ministry of Earth Science in India.

John led the ocean model developments based on NEMO for applications across the Met Office for a number of years before becoming Head of Ocean Forecasting in 2014.

Dr. Siddorn’s Webpage: https://noc.ac.uk/n/John+Siddorn

About keynote speech:
Digital Twins for Ocean Science and for Science Impact
Abstract:

The term digital twin is increasingly being used but often with a patchy understanding of what digital twins are in the context of ocean science, or what they might offer to us and the decision makers we support. Components of a digital twin are described, and the model versus digital twin trope is considered. An effort is made to provide illumination around how to define digital twins in the environmental context, noting that the value of digital tools is the important thing and working towards digital twins (however you define them) could provide value. Digital twins are not a replacement for the tools we already have but are better seen as a framework for adding value to them. We will still need the fundamentals of ocean science – collecting, quality controlling and contextualising complex ocean observations through modelling, data science and expert knowledge. But, if successful, digital twins will allow that process to happen more quickly, and be more easily integrated with other data, knowledge and systems to ensure that our science becomes actionable knowledge, available to, and used by, a wider community of decision makers. This will transform the way we do ocean science and the impact we have. But there is a real danger that impact is never realised if the foundational work is not done to collect the necessary observations and democratise the data derived from them.

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