Cognitive Effects of Visualization Techniques for Inconsistency Metrics on Monitoring Data-Intensive Processes

ABSTRACT

Due to the increasing amounts of process data, monitoring company processes is currently evolving into a data-intensive analytics problem. In this report, we present the results of an experiment analyzing the cognitive effects of different visualization techniques for inconsistency metrics in the scope of monitoring data-intensive processes. Our results indicate that a ranked overview of metrics is associated with better understanding efficiency and less mental effort compared to other visualization techniques.

KEYWORDS:

• Data-intensive processes
• inconsistency measurement
• cognitive model
• metrics visualization

Acknowledgments

We thank Wei Wang, Marta Indulska, Shazia Sadiq and Barbara Weber for insights and inspiration to our research design.

Disclaimer

An earlier version of this paper was published in the Proceedings of the 53rd HICSS conference.

Notes

1. https://zln.do/31wcTqz.

2. https://www.omg.org/spec/BPMN/2.0/.

3. https://www.omg.org/spec/DMN/.

4. The experiment can be downloaded from https://bit.ly/2KfsBAU.

5. https://www.eyevido.de.

6. Levene’s test is used to analyze the variance for a variable measured for at least two groups.

7. The Wilcoxon-Mann-Whitney test is used to compare the distribution data from two samples.

8. The Wilcoxon signed-ranked test is used for dependent samples.

Additional information

Funding

This work was supported by the Deutsche Forschungsgemeinschaft [DE1983/9-1].

Notes on contributors

Sabine Nagel

Sabine Nagel received her B.Sc. in Computer Science and her M.Sc. in Information Systems from the University of Koblenz-Landau in 2017 and 2019, respectively. Since 2019 she has been working as a research assistant and Ph.D. candidate at the Institute for Information Systems Research at the University of Koblenz-Landau. Her current research interests include Business Process Management and in particular Business Rules Management, as well as Business Intelligence.

Carl Corea

Carl Corea is a research assistant and Ph.D. candidate at the Institute for Information Systems Research at the University of Koblenz-Landau. He received his bachelor’s degree in Information Management and master’s degree in Web Science, both at the University of Koblenz-Landau. His research interest is in the intersection of Business Informatics (especially Business Process Management) and Theoretical Computer Science.

Patrick Delfmann

From 1995 to 2001, Patrick Delfmann studied Information Systems at the University of Münster. After receiving his Diploma, he worked as a research assistant at the Chair of Information Systems and Information Management, where he finished his Ph.D. in 2006 and his post-doctoral degree (habilitation) in 2011. He received a call to the Chair of Corporate Communication Systems at the University of Koblenz-Landau, which he heads as a full professor since 2017. His research interests are Business Process Management, Conceptual Modeling, Process Mining, Predictive Process Analytics, and Natural Language Processing.