Industry is increasingly demanding IT support for large engineering processes, i.e., process structures consisting of hundreds up to thousands of processes. Developing a car, for example, requires the coordination of development processes for hundreds of components. Each of these development processes itself comprises a number of interdependent processes for designing, testing, and releasing the respective component. Typically, the resulting process structure becomes very large and is characterized by a strong relation with the assembly of the product. Such process structures are denoted as
. On the one hand, the strong linkage between data and processes can be utilized for automatically creating process structures. On the other hand, it is useful for (dynamically) adapting process structures at a high level of abstraction. This paper presents new techniques for (dynamically) adapting data-driven process structures. We discuss fundamental correctness criteria needed for (automatically) detecting and disallowing dynamic changes which would lead to an inconsistent runtime situation. Altogether, our COREPRO approach provides a new paradigm for changing data-driven process structures at runtime reducing costs of change significantly.