Semantic based Modeling, Selfcomposition, and Selfconfiguration of Reference Processes (SEMPRO)

In our competitive world, companies need to be able to adapt their processes quickly in order to react for instance to changing customer demands or legal regulations. Process models are an appropriate means to support both the process setup and the management. But currently, the creation or adaption of new process models is a time-consuming, widely used manual task. Therefore, methods of “traditional” process modeling and process optimization seem to be inadequate or even inapplicable.

To alleviate this drawback, we propose a higher degree of automation, i.e. a (semi)automated creation and adaption of process models that are able to be executed by web services. To empower such a (semi)automated planning of process models, we need semantically specified actions as atomic building blocks that are composed to create the required process models.

As main part of the research project, we design a planning algorithm (SEMPA – SEMantic-based Planning of Activities) that, given a problem to be solved by a process, is able to compose process actions to executable process models.