Process analysis to improve performance and detect anomalies is important for process management. However, such an analysis requires a global process model that is sometimes hard to get, especially for complex processes involving various teams. This is also an obstacle for BAPE (Bottom-up Artifact-centric Process Environment), an artifact-centric process management environment that allows splitting a process into several fragments which are separately modeled and enacted by different actors. Thus, the knowledge about the whole process is distributed over the involved teams and an overview on the complete process is missing. This paper presents the integration of process mining into BAPE in order to construct the overall process model from the execution data of process fragments.