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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https://www.win.tue.nl/bpi/, Accessed: 12/02/2019.
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References
Ailenei, I., Rozinat, A., Eckert, A., van der Aalst, W.M.P.: Definition and validation of process mining use cases. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) BPM 2011. LNBIP, vol. 99, pp. 75–86. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28108-2_7
Augusto, A., Conforti, R., Dumas, M., La Rosa, M.: Split miner: discovering accurate and simple business process models from event logs. In: ICDM, pp. 1–10 (2017)
Bozkaya, M., Gabriels, J., van der Werf, J.: Process diagnostics: a method based on process mining. In: eKNOW, pp. 22–27 (2009)
Dumas, M., La Rosa, M., Mendling, J., Reijers, H.: Fundamentals of Business Process Management. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-33143-5
García-Bañuelos, L., van Beest, N., Dumas, M., La Rosa, M., Mertens, W.: Complete and interpretable conformance checking of business processes. IEEE Trans. Softw. Eng. 44, 262–290 (2017)
Isenberg, P., Zuk, T., Collins, C., Carpendale, S.: Grounded evaluation of information visualizations. In: Workshop on Beyond Time and Errors: Novel Evaluation Methods for Information Visualization, pp. 6:1–6:8 (2008)
Keim, D., Andrienko, G., Fekete, J.-D., Görg, C., Kohlhammer, J., Melançon, G.: Visual analytics: definition, process, and challenges. In: Kerren, A., Stasko, J.T., Fekete, J.-D., North, C. (eds.) Information Visualization. LNCS, vol. 4950, pp. 154–175. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-70956-5_7
Krippendorff, K.: Content Analysis: An Introduction to Its Methodology, 2nd edn. Sage Publications, Thousand Oaks (2004)
Leemans, S., Fahland, D., van der Aalst, W.: Discovering block-structured process models from event logs - a constructive approach. In: Petri Nets, pp. 311–329 (2013)
Martens, J., Verheul, P.: Social performance review of 5 Dutch municipalities: future fit cases for outsourcing? In: BPI (2015)
Mayring, P.: Qualitative content analysis. Forum Qual. Soc. Res. 1(2) (2000). Article no. 20
Meyer, M., Sedlmair, M., Munzner, T.: The four-level nested model revisited: blocks and guidelines. In: BELIV, pp. 11:1–11:6 (2012)
Munzner, T.: A nested model for visualization design and validation. IEEE Trans. Vis. Comput. Graph. 15(6), 921–928 (2009)
Munzner, T.: Visualization Analysis and Design. CRC Press, Boca Raton (2014)
Nguyen, H., Dumas, M., La Rosa, M., ter Hofstede, A.H.M.: Multi-perspective comparison of business process variants based on event logs. In: Trujillo, J.C., et al. (eds.) ER 2018. LNCS, vol. 11157, pp. 449–459. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00847-5_32
Recker, J.: Scientific Research in Information Systems: A Beginner’s Guide. Springer, Berlin (2013). https://doi.org/10.1007/978-3-642-30048-6
Rozinat, A., van der Aalst, W.: Conformance checking of processes based on monitoring real behavior. Inf. Syst 33(1), 64–95 (2008)
Song, M., van der Aalst, W.: Supporting process mining by showing events at a glance. In: WITS 2007, pp. 139–145 (2007)
Spence, R.: Information Visualization - An Introduction. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07341-5
van der Aalst, W.: Business process management: a comprehensive survey. ISRN Softw. Eng. 2013 (2013). Article no. 507984
van der Aalst, W.: Process Mining: Data Science in Action. Springer, Berlin (2016). https://doi.org/10.1007/978-3-662-49851-4
van der Aalst, W., de Leoni, M., ter Hofstede, A.: Process mining and visual analytics: breathing life into business process models. BPM reports, BPMcenter.org (2011)
van Eck, M.L., Lu, X., Leemans, S.J.J., van der Aalst, W.M.P.: PM\(^2\): a process mining project methodology. In: Zdravkovic, J., Kirikova, M., Johannesson, P. (eds.) CAiSE 2015. LNCS, vol. 9097, pp. 297–313. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19069-3_19
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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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