Model‐Driven Engineering for Digital Twins: Opportunities and Challenges

Judith Michael; Loek Cleophas; Steffen Zschaler; Tony Clark; Benoit Combemale; Thomas Godfrey; Djamel Eddine Khelladi; Vinay Kulkarni; Daniel Lehner; Bernhard Rumpe; Manuel Wimmer; Andreas Wortmann; Shaukat Ali; Balbir Barn; Ion Barosan; Nelly Bencomo; Francis Bordeleau; Georg Grossmann; Gabor Karsai; Oliver Kopp; Bernhard Mitschang; Paula Munoz Ariza; Alfonso Pierantonio; Fiona Polack; Matthias Riebisch; Holger Schlingloff; Markus Stumptner; Antonio Vallecillo; Mark van den Brand; Hans Vangheluwe

doi:10.1002/sys.21815

Model‐Driven Engineering for Digital Twins: Opportunities and Challenges

Judith Michael^*, Loek Cleophas, Steffen Zschaler, Tony Clark, Benoit Combemale, Thomas Godfrey, Djamel Eddine Khelladi, Vinay Kulkarni, Daniel Lehner, Bernhard Rumpe, Manuel Wimmer, Andreas Wortmann, Shaukat Ali, Balbir Barn, Ion Barosan, Nelly Bencomo, Francis Bordeleau, Georg Grossmann, Gabor Karsai, Oliver KoppBernhard Mitschang, Paula Munoz Ariza, Alfonso Pierantonio, Fiona Polack, Matthias Riebisch, Holger Schlingloff, Markus Stumptner, Antonio Vallecillo, Mark van den Brand, Hans Vangheluwe

^*Corresponding author for this work

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Abstract

Digital twins are increasingly used across a wide range of industries. Modeling is a key to digital twin development—both when considering the models which a digital twin maintains of its real-world complement (“models in digital twin”) and when considering models of the digital twin as a complex (software) system itself. Thus, systematic development and maintenance of these models is a key factor in effective and efficient digital twin development, maintenance, and use. We argue that model-driven engineering (MDE), a field with almost three decades of research, will be essential for improving the efficiency and reliability of future digital twin development. To do so, we present an overview of the digital twin life cycle, identifying the different types of models that should be used and re-used at different life cycle stages (including systems engineering models of the actual system, domain-specific simulation models, models of data processing pipelines, etc.). We highlight some approaches in MDE that can help create and manage these models and present a roadmap for research towards MDE of digital twins.

Original language	English
Journal	Systems Engineering Journal
DOIs	https://doi.org/10.1002/sys.21815
Publication status	Published - 2 Apr 2025

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Dagstuhl_Paper__Model_Driven_Engineering_of_Digital_Twins__INCOSE_Systems_Engineering_Accepted author manuscript, 0.98 MB

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Michael, J., Cleophas, L., Zschaler, S., Clark, T., Combemale, B., Godfrey, T., Khelladi, D. E., Kulkarni, V., Lehner, D., Rumpe, B., Wimmer, M., Wortmann, A., Ali, S., Barn, B., Barosan, I., Bencomo, N., Bordeleau, F., Grossmann, G., Karsai, G., ... Vangheluwe, H. (2025). Model‐Driven Engineering for Digital Twins: Opportunities and Challenges. Systems Engineering Journal. https://doi.org/10.1002/sys.21815

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title = "Model‐Driven Engineering for Digital Twins: Opportunities and Challenges",

abstract = "Digital twins are increasingly used across a wide range of industries. Modeling is a key to digital twin development—both when considering the models which a digital twin maintains of its real-world complement (“models in digital twin”) and when considering models of the digital twin as a complex (software) system itself. Thus, systematic development and maintenance of these models is a key factor in effective and efficient digital twin development, maintenance, and use. We argue that model-driven engineering (MDE), a field with almost three decades of research, will be essential for improving the efficiency and reliability of future digital twin development. To do so, we present an overview of the digital twin life cycle, identifying the different types of models that should be used and re-used at different life cycle stages (including systems engineering models of the actual system, domain-specific simulation models, models of data processing pipelines, etc.). We highlight some approaches in MDE that can help create and manage these models and present a roadmap for research towards MDE of digital twins.",

author = "Judith Michael and Loek Cleophas and Steffen Zschaler and Tony Clark and Benoit Combemale and Thomas Godfrey and Khelladi, {Djamel Eddine} and Vinay Kulkarni and Daniel Lehner and Bernhard Rumpe and Manuel Wimmer and Andreas Wortmann and Shaukat Ali and Balbir Barn and Ion Barosan and Nelly Bencomo and Francis Bordeleau and Georg Grossmann and Gabor Karsai and Oliver Kopp and Bernhard Mitschang and {Munoz Ariza}, Paula and Alfonso Pierantonio and Fiona Polack and Matthias Riebisch and Holger Schlingloff and Markus Stumptner and Antonio Vallecillo and {van den Brand}, Mark and Hans Vangheluwe",

note = "Publisher Copyright: {\textcopyright} 2025 The Author(s). Systems Engineering published by Wiley Periodicals LLC.",

year = "2025",

month = apr,

day = "2",

doi = "10.1002/sys.21815",

language = "English",

journal = "Systems Engineering Journal",

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Michael, J, Cleophas, L, Zschaler, S, Clark, T, Combemale, B, Godfrey, T, Khelladi, DE, Kulkarni, V, Lehner, D, Rumpe, B, Wimmer, M, Wortmann, A, Ali, S, Barn, B, Barosan, I, Bencomo, N, Bordeleau, F, Grossmann, G, Karsai, G, Kopp, O, Mitschang, B, Munoz Ariza, P, Pierantonio, A, Polack, F, Riebisch, M, Schlingloff, H, Stumptner, M, Vallecillo, A, van den Brand, M & Vangheluwe, H 2025, 'Model‐Driven Engineering for Digital Twins: Opportunities and Challenges', Systems Engineering Journal. https://doi.org/10.1002/sys.21815

TY - JOUR

T1 - Model‐Driven Engineering for Digital Twins: Opportunities and Challenges

AU - Michael, Judith

AU - Cleophas, Loek

AU - Zschaler, Steffen

AU - Clark, Tony

AU - Combemale, Benoit

AU - Godfrey, Thomas

AU - Khelladi, Djamel Eddine

AU - Kulkarni, Vinay

AU - Lehner, Daniel

AU - Rumpe, Bernhard

AU - Wimmer, Manuel

AU - Wortmann, Andreas

AU - Ali, Shaukat

AU - Barn, Balbir

AU - Barosan, Ion

AU - Bencomo, Nelly

AU - Bordeleau, Francis

AU - Grossmann, Georg

AU - Karsai, Gabor

AU - Kopp, Oliver

AU - Mitschang, Bernhard

AU - Munoz Ariza, Paula

AU - Pierantonio, Alfonso

AU - Polack, Fiona

AU - Riebisch, Matthias

AU - Schlingloff, Holger

AU - Stumptner, Markus

AU - Vallecillo, Antonio

AU - van den Brand, Mark

AU - Vangheluwe, Hans

PY - 2025/4/2

Y1 - 2025/4/2

N2 - Digital twins are increasingly used across a wide range of industries. Modeling is a key to digital twin development—both when considering the models which a digital twin maintains of its real-world complement (“models in digital twin”) and when considering models of the digital twin as a complex (software) system itself. Thus, systematic development and maintenance of these models is a key factor in effective and efficient digital twin development, maintenance, and use. We argue that model-driven engineering (MDE), a field with almost three decades of research, will be essential for improving the efficiency and reliability of future digital twin development. To do so, we present an overview of the digital twin life cycle, identifying the different types of models that should be used and re-used at different life cycle stages (including systems engineering models of the actual system, domain-specific simulation models, models of data processing pipelines, etc.). We highlight some approaches in MDE that can help create and manage these models and present a roadmap for research towards MDE of digital twins.

AB - Digital twins are increasingly used across a wide range of industries. Modeling is a key to digital twin development—both when considering the models which a digital twin maintains of its real-world complement (“models in digital twin”) and when considering models of the digital twin as a complex (software) system itself. Thus, systematic development and maintenance of these models is a key factor in effective and efficient digital twin development, maintenance, and use. We argue that model-driven engineering (MDE), a field with almost three decades of research, will be essential for improving the efficiency and reliability of future digital twin development. To do so, we present an overview of the digital twin life cycle, identifying the different types of models that should be used and re-used at different life cycle stages (including systems engineering models of the actual system, domain-specific simulation models, models of data processing pipelines, etc.). We highlight some approaches in MDE that can help create and manage these models and present a roadmap for research towards MDE of digital twins.

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U2 - 10.1002/sys.21815

DO - 10.1002/sys.21815

M3 - Article

SN - 1098-1241

JO - Systems Engineering Journal

JF - Systems Engineering Journal

ER -

Model‐Driven Engineering for Digital Twins: Opportunities and Challenges

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