In this webinar, our panellist will share their thoughts about data management, which tools to use, what standards to follow and how to get everyone involved. We will touch on the value of good data management, as well as benefits of data reuse.
Webinar 3: Data management
Tuesday November 18th 2025, 3 pm (GMT)
Register for our free webinar here.
Speakers
Jonathan Hirst, Professor of Computational Chemistry, University of Nottingham, UK
Jonathan Hirst is Professor in Computational Chemistry at the University of Nottingham. In 2020, he was awarded a Chair in Emerging Technologies by the Royal Academy of Engineering, focusing on research that will empower the development of next-generation molecules that chemical engineers and chemists make, by using machine learning to augment human decision-making. His tenure as Head of School (2013-2017) saw some significant transformations under his leadership, including the building of the GSK Carbon Neutral Laboratory and a successful bid for an Athena Swan Silver Award.
Talk title: AI4Green: an open-source ELN for collaboration, data management and sustainability chemistry
Kathryn Cowtan, Professor of Chemistry, University of York, UK
Kathryn is an interdisciplinary data scientist working in York Structural Biology Laboratory. She developed software for key steps in the solution of molecular structures from X-ray crystallography data and cryo-electron microscopy. In the last decade Kathryn has also become interested in data analysis problems in climate science. In addition to working with the UK Met Office and other organizations on historical observations and climate model outputs, she has also worked with psychologists and social scientists on understanding and responding to the motivated rejection of climate science. Recently Kathryn has developed a postgraduate taught programme in data science with major emphasis on reducing barriers to participation, especially in the areas of gender and neurodiversity.
Oliver Koepler, Head of Lab Linked Scientific Knowledge, TIB, Germany
Supported by
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