S. Wolny, A. Mazak, R. Konlechner, M. Wimmer: Towards Continuous Behavior Mining, Poster: 7th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2017), Neuchâtel, Switzerland; 06.-08.12.2017, in Data-driven Process Discovery and Analysis 2017, P. Ceravolo, M. Van Keulen, K. Stoffel (Hrg.), CEUR Workshop Proceedings, Vol-2016 (2017), ISSN: 1613-0073; S. 149 - 150. pdf

With new advances in Cyber-Physical Systems (CPS) and Internet of Things (IoT), more and more discrete software controllers interact with continuous physical systems. Workflow models are a classical approach to define controllers. However, the effect of the associated actions that are activated by executing the workflow may not spontaneously be realized but have to be realized over time. Generally, behavioral model elements such as activities in workflow languages are displayed mostly as black box, meaning that it is not possible to trace variable changes over time in most of the classical modeling approaches. In this paper, we introduce an envisioned architecture to cope with this challenge.

Towards Continuous Behavior Mining