4D Modeller is a follow-on project from the ERC-funded GlobalMass grant (www.globalmass.eu) that advanced the use of space-time statistical inference to separate global sea level rise into its different sources.
We are now working to generalise this approach into a dedicated software tool, 4D Modeller, capable of solving a wider range of large-scale, space-time (i.e. four-dimensional) problems. Such a tool has the potential to transform many disciplines, not just in Earth and environmental sciences, but also in areas such as public health and national security, and has the potential to attract huge commercial interest, for example in extreme weather risk assessment for insurance and reinsurance.
The 4D Modeller software and a range of tutorials are available at https://4dmodeller.github.io/fdmr/.
Be part of our two-day hackathon, where you will use the 4D-Modeller (fdmr) package to solve the spatio-temporal problems of Svalbard! FDMR tackles spatio-temporal problems at all scales, from local to global, and has already been successfully applied to diverse areas such as COVID-19 transmission, hydropower generation, and global sea-level rise.
Harnessing Bayesian Hierarchical Models, fdmr offers probabilistic inference and scales efficiently for big data challenges. With user-friendly tutorial vignettes, you don’t need to be a statistics expert to leverage its power. Join our hackathon to contribute directly to the development of fdmr and address research questions specific to Svalbard.
Embracing Tutorial Driven Software Development, our approach ensures features align with users’ needs. Work closely with the fdmr development team to create tutorials and implement new features. The hackathon will be held in November 2023 (coinciding with the Svalbard Science Forum meeting) and a second hackathon will occur in Spring 2024.
Don’t miss this opportunity to shape the future of spatio-temporal modeling. Limited spots available. Register now and revolutionize research in Svalbard with FDMR!
📅 Date: November 2-3, 2023 (coinciding with the Svalbard Science Forum meeting)
📍 Location: Oslo, Norway (first hackathon)
⚙️ Domain Focus: Climate science, hydrology, glaciology
🚀 Outcome: Development of case studies and research challenges in spatio-temporal modelling
📝 Participants: 40 researchers (20 per hackathon)
Visit https://4dmodeller.github.io/4DM_Hackathon/ to learn more and secure your spot today! Let’s revolutionize spatio-temporal modeling in Svalbard with fdmr. See you at the hackathon! 👩💻
- Yin X, Aiken JM and Bamber JL, 2023. fdmr: A Comprehensive R Package for Spatio-Temporal Modelling. UC Santa Barbara: Center for Spatial Studies. 10.25436/E27C7F
- Yin X, Aiken JM, Harris R and Bamber JL, 2023. Spatio-temporal spread of COVID-19 and its associations with socioeconomic, demographic and environmental factors in England: A Bayesian hierarchical spatio-temporal model. arXiv:2308.09404.
- Aiken JM, Yin X, Royston S, Ziegler Y and Bamber JL, 2023. From Sea Level Rise to COVID-19: Extending a Bayesian Hierarchical Model to unfamiliar problems with the 4D-Modeller framework, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1680. 10.5194/egusphere-egu23-1680.
This work is supported by UKRI grant EP/X022641/1