Abstract
Many business process management activities benefit from the investigation of event data. Thus, research, foremost in the field of process mining, has focused on developing appropriate analysis techniques, visual idioms, methodologies, and tools. Despite the enormous effort, the analysis process itself can still be fragmented and inconvenient: analysts often apply various tools and ad-hoc scripts to satisfy information needs. Therefore, our goal is to better understand the specific information needs of process analysts. To this end, we characterize and examine domain problems, data, analysis methods, and visualization techniques associated with visual representations in 71 analysis reports. We focus on the representations, as they are of central importance for understanding and conveying information derived from event data. Our contribution lies in the explication of the current state of practice, enabling the evaluation of existing as well as the creation of new approaches and tools against the background of actual, practical needs.
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Klinkmüller, C., Müller, R., Weber, I. (2019). Mining Process Mining Practices: An Exploratory Characterization of Information Needs in Process Analytics. In: Hildebrandt, T., van Dongen, B., Röglinger, M., Mendling, J. (eds) Business Process Management. BPM 2019. Lecture Notes in Computer Science(), vol 11675. Springer, Cham. https://doi.org/10.1007/978-3-030-26619-6_21
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