Research led by Nik Lomax, Associate Professor of Data Analytics for Population Research at the University of Leeds and a Fellow at the Alan Turing Institute for data science and artificial intelligence, is using digital twin computer simulations to model social systems.
Created with the hardware funded by DAFNI, the computer simulations model social systems at a high resolution, both in terms of spatial scale and individual level attributes using techniques such as agent based models and microsimulation.
Within a digital twin which represents the social system, the team can investigate hypothetical policy change by running counterfactual experiments and assess how these impact on individuals, groups and spatial areas.
The DAFNI hardware fund enabled the team to develop digital twin models across a variety of applications and to rerun them easily, and for the team to collaborate in a local environment rather than to use cloud based services which can increase costs.
Professor Nik Lomax said, "Within a digital twin which represents the social system, we can investigate hypothetical policy change by running counterfactual experiments and assess how these impact on individuals, groups and spatial areas.
"Building an augmented/ virtual reality world will help policymakers to make more informed decisions. The ability to take our research outside the university, to demonstrate the digital world to policymakers, means we will be able to better visualise scenarios and impacts.”
The research team create individual level models in a wide range of research contexts and are utilising the DAFNI hardware due to the requirement for high computational power to develop and run these models.
One application of this research focuses on infrastructure development. In collaboration with a transport consultancy, different scenarios of transport infrastructure development are being assessed. Individual level models are being built and run on the DAFNI hardware which produce high resolution population and household estimates and projections which are then used as input to infrastructure demand models.
You can read the original article with Professor Nik Lomax on the DAFNI website.