Mining Process Mining Practices: An Exploratory Characterization of Information Needs in Process Analytics

EasyChair Preprint 1111

Abstract

In many phases of the business process management lifecycle, analysts can benefit from insights gained through the investigation of process event data. It is thus hardly surprising that research in recent years, foremost in the field of process mining, has focused on developing appropriate analysis techniques, visual idioms, methodologies, and tools. Yet, despite the enormous effort, the analysis process itself can still be fragmented and inconvenient: analysts often apply various tools and develop ad-hoc scripts in order satisfy their information needs. Therefore, the goal of this research is to better understand the specific information needs that arise during the analysis of process event data. To this end, we exploratively characterize and examine the data, problems 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 that is derived from process event data, thus describing interesting aspects of the respective business process. Our contribution lies in the explication of the current state of practice, which we achieve through a systematic description and investigation of the visual representations. This work enables the evaluation of existing as well as the creation of new approaches and tools against the background of actual, practical needs. Moreover, analysts might draw solution strategies from our description when faced with a particular problem.

Keyphrases: Process Mining, qualitative content analysis, visual analytics

@booklet{EasyChair:1111,
  author    = {Christopher Klinkmüller and Richard Müller and Ingo Weber},
  title     = {Mining Process Mining Practices: An Exploratory Characterization of Information Needs in Process Analytics},
  howpublished = {EasyChair Preprint 1111},
  year      = {EasyChair, 2019}}