Abstract
The Horizon Europe interTwin project is developing a highly generic yet powerful Digital Twin Engine (DTE) to support interdisciplinary Digital Twins. The project brings together infrastructure providers, technology providers, and DT use cases from Climate Research and Environmental Monitoring, High Energy Physics, AstroPhysics, and Radio Astronomy. This group of experts enables the co-design of the DTE Blueprint Architecture and the prototype platform benefiting end users like scientists and policymakers but also DT developers. It achieves this by significantly simplifying the process of creating and managing complex Digital Twins workflows.
There are 6 use cases co-designing and validating the interTwin DTE in Climate Research and Environmental Monitoring. This talk will highlight in more technical detail the implementation of drought early warning DT and the utilized components from the DTE.
To interTwin DTE adopts cutting-edge technologies widely recognized within the Earth Observation (EO) and environmental modeling communities (openEO API and STAC) extended to use containerized workflows implemented using the Common Workflow Language (CWL). The project developed an AI/ML workflow module to allow seamless integration of data driven modelling with physics based workflows. The DT is deployable using standard TOSCA templates and utilizes High-Performance Computing (HPC) instances to accommodate the computational demands of large-scale simulations and data processing. This deployment ensures scalability, enabling the system to handle extensive datasets and support a diverse range of applications. By leveraging distributed computing resources, we aim to create a responsive and adaptive framework capable of addressing dynamic environmental challenges.