interTwin: Advancing Scientific Digital Twins through AI, Federated Computing and Data

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Authors: Andrea Manzi, Raul Bardaji, Ivan Rodero A, Germán Moltó, Sandro Fiore, Isabel Campos, Donatello Elia, F. Sarandrea, Alexander Paul Millar, Daniele Spiga, Matteo Bunino, Gabriele Accarino
+21 more L. Asprea, Samuel Bernardo, Miguel Caballer, Charis Chatzikyriakou, Diego Ciangottini, Michele Claus, Andrea Cristofori, Davide Donno, Emanuele Donno,  Iacopo Federico Ferrario, Massimiliano Fronza, Alexander W. Jacob, Javad Komijani, Marina Krstić Marinković, Federica Legger, Ivan Palomo, Estíbaliz Parcero, Rakesh Sarma, Gaurav Ray, Sara Vallero,  J Zvolensky
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Abstract

The EU project interTwin, co-designed and implemented the prototype of an interdisciplinary Digital Twin Engine (DTE), an open-source platform that provides generic and domain-specific software components for modelling and simulation to integrate application-specific Digital Twins (DTs). The DTE is built upon a co-designed conceptual model - the DTE blueprint architecture - guided by open standards and interoperability principles. The ambition is to develop a unified approach to the implementation of DTs that is applicable across diverse scientific disciplines to foster collaborations and facilitate developments. Co-design involved DT use cases from high-energy physics, radio astronomy, astroparticle physics, climate research, and environmental monitoring, which drove advancements in modelling and simulation by leveraging heterogeneous distributed digital infrastructures, enabling dynamic workflow composition, real-time data management and processing, quality and uncertainty tracing of models, and multi-source data fusion.

Fields of Study & Subjects

Scientific Computing and Data Management Digital Transformation in Industry Distributed and Parallel Computing Systems

Publication details

Journal / source
Future Generation Computer Systems
Publication date
1 January 2026
Language
EN