Towards a hybrid theory: Derivation of a view concept between Model-based Systems Engineering and Data Analytics

As modern systems become increasingly complex due to the integration of digital technologies and the rapid pace of change in industry and research, the need for new engineering approaches emerges. The concept of Data-Driven Model-Based Systems Engineering (DDMBSE) represents a novel approach that integrates model-based systems engineering (MBSE) with data analytics (DA). Given its novel status, research is still in its early stages and requires a more in-depth understanding of its fundamental elements, their respective roles, and the ways in which they interact with one another. An exploratory interview study was conducted to derive the essential skills and traits that a (model-based) systems engineer and a data analyst must possess in order to successfully complete a common task within DDMBSE. Furthermore, their concerns related to data and system models were identified and categorized. Based on these findings, a conceptual framework was developed to integrate MBSE and DA, encompassing a system view, data view, and task view. The results provide a foundation for future use cases, processes, methods, and tools for DDMBSE.