Digital twin engineering requires models, data, services, and gateways to interact in a meaningful way to monitor, analyze and optimize its physical counterpart. Especially the connection between models and data, also referred to as model hybridization, requires developing new methods for describing and analyzing such relations and supporting software engineers to understand and actively work with these connections. In the ANR/DFG project "Model-Based DevOps" (https://mbdo.github.io/), software architectures, tools and methods for digital twins are conceived to enable the systematic creation, composition, deployment, and operation of digital twins. This meeting discusses current research and challenges in MBDO and how these research insights should reflect into teaching when educating the next generation of software engineers.

Creative Commons BY 4.0

Benoit Combemale, Judith Michael, and Andreas Wortmann