Natural Language-based Visualization and Modeling for Updatable Process Views

Nowadays, an understanding of its own business processes is crucial for companies, to ensure an efficient and quick changing work flow. While several tools exists using graphical annotations, e.g. Business Process Model and Annotation (BPMN), an untrained staff member may not be able to understand business processes described in these annotations, resulting in additional investments into staff member training. Furthermore, some structures used in graphical annotations may not seem native to untrained users, causing misinterpretations of business process models. Fostering this issue, natural language-based process descriptions may used. These descriptions are automatic-generated from process models. Another problem of modern business process modeling is the communication between process modelers and domain experts. A thought of a domain expert can be misinterpreted by the process modeler. The results are discrepancies in business process models. Avoiding this problem, modeling mechanics for natural language-based process descriptions may used. Therefore, the thesis introduces fundamentals of the proView project as well as the generation and editing of natural language-based process descriptions. Subsequently, integration steps of natural language into the proView project, divided into two parts, are shown. The first part contains integration of a process model to natural language text converter. The second part discusses problems and solutions of natural language-based modeling. Further, the second part shows the integration of natural language-based modeling into the proView project. Finally, further steps in the future are discussed.