Towards a Federated Approach to Complex Digital Twins

In recent years, digital twins have emerged as an advanced data-driven technology for modeling and monitoring complex physical systems to inform actionable decision-making. One area where digital twins can be especially impactful is urgent computing applications, such as natural disasters and hazards, where timely and reliable decision support is needed. However, it is challenging to streamline dynamic data with modeling and simulation methods for urgent computing applications due to the use of heterogeneous multimodal data sources, Internet of Things (IoT) networks, and high-performance computing (HPC) systems to power edge-to-cloud capabilities. In this work, we describe a reference architecture that uses federation and dynamic composability to power digital twins for complex physical systems. We demonstrate the usefulness of our approach with the Firemap architecture on WIFIRE, an end-to-end cyberinfrastructure for real-time and data-driven simulation, prediction, and visualization of wildfire behavior.