
Within interTwin, we are developing an interdisciplinary Digital Twin Engine (DTE) – an open-source platform packed with versatile software components for modeling and simulation. This time, we're diving deep into the DTE Core modules. Here's what you can expect:🔧 Development of an Open Source Digital Twin Engine (DTE): We'll walk you through the creation of our interdisciplinary DTE, explaining how it provides the building blocks for your Digital Twin projects.🎯 Focus on Core Modules: Get an intro to all the components and a deep dive into:- Event-driven Serverless and Data Processing- Data Fusion- Digital Twins QualityWe'll also show you how these components integrate with the DTE infrastructure and how our user communities are already putting them to use. Agenda💠 Intro to project/DTE Core subsystem : Isabel Campos (CSIC)💠itwinai: AI on Cloud and HPC for Science: Matteo Bunino (CERN) and Rakesh Sarma (FZJ) 💠IM, OSCAR, and DCNiOS: Event Driven serverless computing and data processing flows: Estíbaliz Parcero (UPV) and Miguel Caballer (UPV) 💠Data fusion with OpenEO: Alexander Jacob (EURAC) 💠SQAasS : Platform for quality assessment and awarding of multiple digital objects: Ivan Palomo (CSIC) 💠Q& A
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
