J. Michael, L. Cleophas, S. Zschaler, T. Clark, B. Combemale, T. Godfrey, D. Khelladi, E. Djamel V. Kulkarni, D. Lehner, B. Rumpe, M. Wimmer, A. Wortmann, S. Ali, B. Barn, I. Barosan, N. Bencomo, F. Bordeleau, G. Grossmann,G. Karsai, O. Kopp, B. Mitschang, P. A. Muñoz; A. Pierantonio, F. A. C. Polak, M. Riebisch, H. Schlingloff, M. Stumptner, A. Vallecillo, M. van den Brand, H. Vangheluwe: About Opportunities and Challenges in Model-Driven Engineering for Digital Twins - (Extended Abstract), Modellierung Conference 2026, Bayreuth, Deutschland, March 9-12, 2026, P-378, pages 155-156, Publisher Gesellschaft für Informatik e.V., Doi: 10.18420/modellierung2026-15
Modelling is essential in the engineering of digital twins: A digital twin includes models and data representing the real-world entity (models in digital twins) and models describing and operating the digital twin as a software system (models of digital twins). Consequently, we need to systematically develop and manage these different kinds of models over time. Model-driven Engineering (MDE) offers methods to address these challenges. Here, we provide an overview of the article ‘Model-Driven Engineering for Digital Twins: Opportunities and Challenges’, published in the INCOSE Systems Engineering journal. It summarizes outcomes from the Dagstuhl Seminar 22362 ‘Model-Driven Engineering of Digital Twins’ and provides insights into the digital twin life cycle, the use and re-use of different model kinds across life cycle stages, and a research roadmap covering six key aspects of digital twin research using MDE.