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.

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.

interTwin: Advancing Scientific Digital Twins through AI, Federated Computing and Data / Manzi, Andrea; Bardaji, Raul; Rodero, Ivan; Moltó, Germán; Fiore, Sandro; Campos, Isabel; Elia, Donatello; Sarandrea, Francesco; Millar, A. Paul; Spiga, Daniele; Bunino, Matteo; Accarino, Gabriele; Asprea, Lorenzo; Bernardo, Samuel; Caballer, Miguel; Chatzikyriakou, Charis; Ciangottini, Diego; Claus, Michele; Cristofori, Andrea; Donno, Davide; Donno, Emanuele; Ferrario, Iacopo; Fronza, Massimiliano; Jacob, Alexander; Komijani, Javad; Marinkovic, Marina Krstic; Legger, Federica; Palomo, Ivan; Parcero, Estíbaliz; Sarma, Rakesh; Sinha Ray, Gaurav; Vallero, Sara; Zvolensky, Juraj. - In: FUTURE GENERATION COMPUTER SYSTEMS. - ISSN 0167-739X. - 179:108312(2026). [10.1016/j.future.2025.108312]

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

Fiore, Sandro;
2026-01-01

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.
2026
108312
Manzi, Andrea; Bardaji, Raul; Rodero, Ivan; Moltó, Germán; Fiore, Sandro; Campos, Isabel; Elia, Donatello; Sarandrea, Francesco; Millar, A. Paul; Spig...espandi
interTwin: Advancing Scientific Digital Twins through AI, Federated Computing and Data / Manzi, Andrea; Bardaji, Raul; Rodero, Ivan; Moltó, Germán; Fiore, Sandro; Campos, Isabel; Elia, Donatello; Sarandrea, Francesco; Millar, A. Paul; Spiga, Daniele; Bunino, Matteo; Accarino, Gabriele; Asprea, Lorenzo; Bernardo, Samuel; Caballer, Miguel; Chatzikyriakou, Charis; Ciangottini, Diego; Claus, Michele; Cristofori, Andrea; Donno, Davide; Donno, Emanuele; Ferrario, Iacopo; Fronza, Massimiliano; Jacob, Alexander; Komijani, Javad; Marinkovic, Marina Krstic; Legger, Federica; Palomo, Ivan; Parcero, Estíbaliz; Sarma, Rakesh; Sinha Ray, Gaurav; Vallero, Sara; Zvolensky, Juraj. - In: FUTURE GENERATION COMPUTER SYSTEMS. - ISSN 0167-739X. - 179:108312(2026). [10.1016/j.future.2025.108312]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/473830
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