Workflows are an established IT concept to achieve business goals in a reliable and robust manner. However, the dynamic nature of modern information systems, the upcoming Industry 4.0, and the Internet of Things increase the complexity of modeling robust workflows significantly as various kinds of situations, such as the failure of a production system, have to be considered explicitly. Consequently, modeling workflows in a situation-aware manner is a complex challenge that quickly results in big unmanageable workflow models. To overcome these issues, we present an approach that allows workflows to become situation-aware to automatically adapt their behavior according to the situation they are in. The approach is based on aggregated context information, which has been an important research topic in the last decade to capture information about an environment. We introduce a system that derives high-level situations from lower-level context and sensor information. A situation can be used by different situation-aware workflows to adapt to the current situation in their execution environment. SitOPT enables the detection of situations using different situation-recognition systems, exchange of information about detected situations, optimization of the situation recognition, and runtime adaption and optimization of situationaware workflows based on the recognized situations.