Developing a tool that converts a process model into a BPMN data model by mining from multiple perspectives

Process mining is mainly focused on process discovery, and also replay techniques to check conformance and analyze bottlenecks. It is further applied to mine the other process perspectives, such as time, data, and resources, by replaying the events in event logs over the initial process model. When process mining is extended far beyond discovering the control-flow models; roles, bottlenecks, amounts of time passed, guards, and routing probabilities in the process can be identified. Such extensions are considered under the topic of multi-perspective process mining, which makes the discovered process model more understandable. In this study, a framework for applying multi-perspective process mining and creating a BPMN process model as the output is introduced. The framework, which uses a recently developed API for storing the BPMN Data Model in blockchain in a secure and immutable way, has been developed as a plugin to the ProM tool. In doing so, it integrates a number of techniques for multi-perspective process mining in literature, for the perspectives of control-flow, data, and resource; and represents a holistic process model by combining the outputs of these in the BPMN Data Model. In this thesis, we explain technical details of the framework and also demonstrate its usage over a case in medical domain.