Semantic Business Process Management

Abstract

The objective of this chapter is to describe and evaluate an approach for the automated analysis of business process models. It is described why an automated way of process analysis is necessary and why it is beneficial to use our approach. As business process models are moving in the center of decision making, it is important for the corresponding decision makers to get transparent, fast, and comprehensive results of process analysis. Dealing with huge amount of data this is only possible with automated support. Based on a comprehensive literature study, we identified different deviations and conflicts that usually arise in business process modeling projects. The class of semantic building block-based languages which combines structural modeling elements with corresponding domain semantics can help avoiding these conflicts. Beside the conceptual development of the language class we conducted an empirical evaluation of PICTURE, a business process modeling language that is an instantiation of semantic building block-based languages. Our results show that (a) our derived language class is applicable, (b) modeling conflicts significantly can be reduced, and (c) modeled data can be analyzed automatically.