Federation of data and models to define digital twins

Context

Digital twins are virtual representations of real-world products, systems, or processes, enabling simulation, integration, testing, monitoring, and maintenance. They play a pivotal role in optimizing complex systems across a wide range of domains, from industrial manufacturing and energy to environmental monitoring and healthcare.

The Engineering Digital Twin EDT program, funded by the France 2030 investment plan, is a national initiative aimed at advancing the foundations of digital twin engineering in France and Europe. By bringing together leading academic and industrial partners, EDT seeks to strengthen the bases for the design, use, and deployment of digital twins, addressing key open challenges in model hybridization, composability, development methodologies, digital coupling, and human–twin interaction.

The construction of digital twins applies to many fields: industry for process or product control, territories to aid decision-making, but also medicine and archaeology, for example. Many digital twins are currently being built, often on an ad hoc basis, i.e. with a short-term operational objective.

In the long term, digital twins should be able to exist for the entire lifetime of their reference system (a factory, a product, a territory, etc.). Digital twins must therefore be designed and built to be easily maintainable, scalable, and interoperable, based on existing information and to collect all future information.

To this end, we see the digital twin as a repository of knowledge that must be modeled (in order to describe and use it) and built from highly heterogeneous sources of information. This heterogeneity has several sources: the nature of the information (observed values, 3D or behavioral models, physics or biology equations, documents, etc.) but also its temporality (real time, future, future in another configuration, past, past with other models). The aim of this thesis is to overcome this obstacle of heterogeneity.

Thesis Objectives

This PhD project aims to develop an information federation approach to design and maintain digital twins over the long term. Particular attention will be paid to the concept of a “timeline” to structure modeling and enable navigation in a multidimensional space of time, variants, and levels of granularity.

Two main questions arise:

• What organizational abstractions are necessary to ensure a long-term vision of digital twins, and

• How can model federation provide some answers?

To answer these questions, key scientific challenges include:

• Identify and classify models: descriptive—describes what is (to be maintained), prescriptive—describes what is interpreted as a constraint (to be validated or adjusted), predictive—describes what could be (to be validated)

• identify and classify descriptive data - source of truth (= reference), prescriptive - source of truth (= designer - to be validated or adjusted), predictive - source of truth (= predictor)

• describe the life cycles of these models and data in terms of their validity and traceability in order to navigate and compare developments in the past, present, and future of digital twins

• study ways of identifying descriptive elements (prescriptive, descriptive, or predictive) (data or model) and what they apply to; propose and define a vocabulary (ontology)

The results of this thesis will directly contribute to the Artemis platform, an open-source framework set to become a benchmark in the field.

Work Environment

The PhD candidate will be co-supervised by Antoine Beugnard, P4S/IMT-Atlantique and Jean-Marc Jézéquel, DiverSE/IRISA within LabSTICC/PS4.

The candidate will benefit from a stimulating scientific and industrial environment of the highest level, with access to a national network of leading research institutions and industry partners, regular interactions with the broader EDT community through workshops, seminars, and joint demonstrators, and the opportunity to contribute to Artemis, the program’s open software platform.

These two teams have been contributing for several years to research on digital twins, and in particular on the need to apply software engineering (SE) and model-based systems engineering (MBSE) principles to such systems.

It is part of the EDT program and will interact with other theses on related topics such as:

• TwinDevOps (PC3 TwinOps)

• Aggregation of digital twins as SoS (PC2 DTCompose)

• Variability (PC2 DTCompose)

What You Will Gain from This PhD

This PhD offers the opportunity to:

• Develop highly sought-after skills in system modeling, real-time data processing, and collaborative innovation.

• Collaborate with leading partners (Inria, CEA, CNRS, etc.) and validate your research on real-world industrial use cases.

• Join a network of PhD candidates within the EDT program, fostering collaboration, peer support, and interdisciplinary exchanges.

• Contribute to an open-source platform (Artemis) and publish in international conferences and journals.

• Gain recognition in a rapidly growing field, with career prospects in academic research, industrial R&D, or entrepreneurship.

Upon completion, you will be positioned as a recognized expert in a key domain for industry and research, with diverse professional opportunities in France and internationally.

References

• Benoît Combemale, Pascale Vicat-Blanc, Arnaud Blouin, Hind Bril El Haouzi, Jean-Michel Bruel, et al.. Engineering Digital Twins: A Research Roadmap. EDTconf 2025 - 2nd International Conference on Engineering Digital Twins, Oct 2025, Grand Rapids, Michigan, United States. pp.1-7. ⟨hal-05223776⟩

• Model Federation

  • Jean-Christophe Bach, Antoine Beugnard, Joel Champeau, Fabien Dagnat, Sylvain Guérin, and Salvador Martínez. 10 Years of Model Federation with OpenFlexo: Challenges and Lessons Learned. In International Conference on Model Driven Engineering Languages and Systems (MoDELS), 2024

  • Sylvain Guérin FML: A Model Federation Language For Semantic Interoperability of Heterogeneous Information Sources. Ph. D. Dissertation, 2023, École Nationale Supérieure de Techniques Avancées de Bretagne.

  • Sylvain Guérin, Joel Champeau, Jean-Christophe Bach, Antoine Beugnard, Fabien Dagnat, and Salvador Martínez. Multi-level modeling with Openflexo/FML : A contribution to the multi-level process challenge. Enterprise Modelling and Information Systems Architectures (EMISAJ), 17 :9–1, 2022.

  • Fahad Rafique Golra, Fabien Dagnat, Jeanine Souquières, Imen Sayar, and Sylvain Guérin. Bridging the gap between informal requirements and formal specifications using model federation. In Einar Broch Johnsen and Ina Schaefer, editors, Software Engineering and Formal Methods, pages 54–69, Cham, 2018. Springer International Publishing.

• Digital Twin

  • Gwendal Beaumont, Antoine Beugnard, Salvador Martínez, Christelle Urtado, Sylvain Vauttier, Towards Automating the Life Cycle Management of Digital Twins ER2025 - 44th International Conference on Conceptual Modeling, Oct 2025, Poitiers, France. pp.412-430, ⟨10.1007/978-3-032-08623-5_22⟩

  • Antoine Beugnard, A software engineering perspective on digital twin: many candidates, none elected, SWC 2023: IEEE Smart World Congress, IEEE Smart World Congress, Aug 2023, Portsmouth, United Kingdom. ⟨10.1109/SWC57546.2023.10448955⟩

  • Judith Michael, Loek Cleophas, Steffen Zschaler, Tony Clark, Benoît Combemale , et al., Model‐Driven Engineering for Digital Twins: Opportunities and Challenges Systems Engineering, 2025, 28 (5), pp.659-670. ⟨10.1002/sys.21815⟩

• Advanced data representation and manipulation

  • Hartmann, T., Fouquet, F., Moawad, A., Rouvoy, R. and Le Traon, Y., 2019. GreyCat: Efficient what-if analytics for data in motion at scale. Information Systems, 83, pp.101-117.

  • Gu, Z., Corcoglioniti, F., Lanti, D., Mosca, A., Xiao, G., Xiong, J., & Calvanese, D. (2024). A systematic overview of data federation systems. Semantic Web, 15(1), 107-165.