Navigating in complex process model collections
FacultiesFakultät für Ingenieurwissenschaften und Informatik
The increasing adoption of process-aware information systems (PAIS) has led to the emergence of large process model collections. In the automotive and healthcare domains, for example, such collections may comprise hundreds or thousands of process models, each consisting of numerous process elements (e.g., tasks). In existing modeling environments, process models are presented to users in a rather static manner. As process participants have different needs and thus require specific presentations of available process information, such static approaches are usually not sufficient to assist them in their daily work. For example, a business manager only requires an abstract overview of a process model collection, whereas a knowledge worker needs detailed information on specific process tasks. In general, a more flexible navigation and visualization approach is needed, which allows process participants to flexibly interact with process model collections in order to navigate from a default visualization of a process model collection to a context-specific one. With the Process Navigation and Visualization (ProNaVis) framework, this thesis provides such a flexible navigation approach for large and complex process model collections. Specifically, ProNaVis enables the flexible navigation within process model collections along three navigation dimensions. First, the geographic dimension allows zooming in and out of the process models. Second, the semantic dimension may be utilized to increase or decrease the level of detail. Third, the view dimension allows switching between different visualizations. All three navigation dimensions have been addressed in an isolated fashion in existing navigation approaches so far, but only ProNaVis provides an integrated support for all three dimensions. Experimental as well as empirical results have provided evidence that ProNaVis will enable a much more flexible navigation in process model repositories compared to existing approaches.
Subject HeadingsProzessmodell [GND]
Information visualization [LCSH]