Semantic business process modeling

Due to constantly changing market conditions, customer requirements and new jurisdiction, or resulting from the integration in electronic supply chains, companies need to change or even restructure their processes and the associated software frequently. Often, changes to a software are only possible by developers, who need to adapt the source code of complex applications manually, making it difficult to realize upcoming requirements in short time. Using model-driven software engineering, an additional level of abstraction can be achieved, which facilitates the comprehension and therefore, adaptation of systems. However, different understanding of the used terms in domain models often leads to unnecessary debate between the involved persons. To avoid this, a mechanism is necessary to describe the semantics of terms explicitly. In this thesis we present an approach to automating the design, adaptation and realization of models. Thereby, we focus on business process models as an example for dynamic models. To capture the semantics of the used terms, techniques from the research field semantic web are transferred to the modeling area. More detailed, we show how process models can be semantically annotated.