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Interdisciplinary digital twins for modelling and simulating complex phenomena at the service of research infrastructure communities


Actions should develop digital twins that provide advanced modelling, simulation and prediction capabilities to RIs and their research communities through a convergent use of advanced digital technologies such as high performance computing, software, AI methods and big data analytics.

With the advent of big data analytics and supercomputing, AI methods have the potential to allow exploiting the full potential of simulations and observations at significantly enhanced scales and to substantially increase the value, which can be extracted from investments into digital infrastructures and hardware. This fusion of models and real-time data is of crucial importance in many scientific areas, which – due to the complexity of the underlying phenomena – are heavily dependent on converging traditional modelling with the increasing amount of real-time data in order to arrive at more accurate present-state assessments and predictions (e.g. high energy physics, astrophysics, environmental research, security ap