Advertisement

Towards a Multi-parametric Visualisation Approach for Business Process Analytics

  • Stefan Bachhofner
  • Isabella Kis
  • Claudio Di Ciccio
  • Jan Mendling
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 286)

Abstract

Visualisation is an integral part of many scientific areas and is reportedly an important tool for learning and teaching. One reason for this is the picture superior effect. Nevertheless, little research endeavour has been carried out so far to effectively apply visualisation principles to the emerging field of business process analytics. In this paper a novel multi-parametric visualisation approach is proposed in such a context. General visualisation principles are used to create, evaluate, and improve the approach in the design process. They are drawn from a wide range of fields, and are synthesised from theory and empirical evidence.

Keywords

Visualisation Business process analytics Business process management Process mining 

References

  1. 1.
    van der Aalst, W.M.P.: Data scientist: the engineer of the future. In: Mertins, K., Bénaben, F., Poler, R., Bourrières, J.-P. (eds.) Enterprise Interoperability VI. PIC, vol. 7, pp. 13–26. Springer, Cham (2014). doi: 10.1007/978-3-319-04948-9_2 CrossRefGoogle Scholar
  2. 2.
    van der Aalst, W.M.P., van Dongen, B.F., Günther, C.W., Rozinat, A., Verbeek, E., Weijters, T.: Prom: the process mining toolkit. In: BPM (Demos). CEUR Workshop Proceedings, vol. 489. CEUR-WS.org (2009)Google Scholar
  3. 3.
    Bertin, J.: Semiology of Graphics. University of Wisconsin Press, Madison (1983)Google Scholar
  4. 4.
    Borland, D., Taylor, R.M.: Rainbow color map (still) considered harmful. IEEE Comput. Graph. Appl. 27, 14–17 (2007)CrossRefGoogle Scholar
  5. 5.
    Dumas, M., Rosa, M.L., Mendling, J., Reijers, H.A.: Fundamentals of Business Process Management. Springer Publishing Company, Incorporated (2013)CrossRefGoogle Scholar
  6. 6.
    Filonik, D., Rittenbruch, M., Foth, M.: DataChopin - designing interactions for visualisation composition in a co-located, cooperative environment. In: Luo, Y. (ed.) CDVE 2016. LNCS, vol. 9929, pp. 126–133. Springer, Cham (2016). doi: 10.1007/978-3-319-46771-9_17 CrossRefGoogle Scholar
  7. 7.
    Goolkasian, P.: Pictures, words, and sounds: From which format are we best able to reason? J. Gen. Psychol. 127(4), 439–459 (2000)CrossRefGoogle Scholar
  8. 8.
    Kis, I., Bachhofner, S., Di Ciccio, C., Mendling, J.: Towards a data-driven framework for measuring process performance. In: BPMDS (2017)Google Scholar
  9. 9.
    Lamping, J., Rao, R.: The hyperbolic browser: a focus+context technique for visualizing large hierarchies. J. Vis. Lang. Comput. 7(1), 33–55 (1996)CrossRefGoogle Scholar
  10. 10.
    Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Process and deviation exploration with inductive visual miner. In: BPM (Demos), vol. 1295, p. 46 (2014)Google Scholar
  11. 11.
    Lidwell, W., K.H., Butler, J.: Universal principles of Design: A Cross-Disciplinary Reference. Rockport Publishers, Gloucester (2003)Google Scholar
  12. 12.
    Moody, D.: The physics of notations: toward a scientific basis for constructing visual notations in software engineering. IEEE Trans. Softw. Eng. 35(6), 756–779 (2009)CrossRefGoogle Scholar
  13. 13.
    Poppe, E., Brown, R., Recker, J., Johnson, D., Vanderfeesten, I.: Design and evaluation of virtual environments mechanisms to support remote collaboration on complex process diagrams. Inform. Syst. 66, 59–81 (2017)CrossRefGoogle Scholar
  14. 14.
    Puchovsky, M., Di Ciccio, C., Mendling, J.: A case study on the business benefits of automated process discovery. In: SIMPDA, pp. 35–49 (2016)Google Scholar
  15. 15.
    Rogowitz, B.E., Treinish, L.A., Bryson, S.: How not to lie with visualization. Comput. Phys. 10(3), 268–273 (1996)CrossRefGoogle Scholar
  16. 16.
    Theus, M.: Mosaic plots. Wiley Interdisciplinary Reviews: Computational Statistics 4(2), 191–198 (2012)CrossRefGoogle Scholar
  17. 17.
    Tory, M., Möller, T.: Human factors in visualization research. IEEE Trans. Vis. Comput. Graph. 10(1), 72–84 (2004)CrossRefGoogle Scholar
  18. 18.
    Turetken, O., Schuff, D., Sharda, R., Ow, T.T.: Supporting systems analysis and design through fisheye views. Commun. ACM 47(9), 72–77 (2004)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Stefan Bachhofner
    • 1
  • Isabella Kis
    • 1
  • Claudio Di Ciccio
    • 1
  • Jan Mendling
    • 1
  1. 1.Vienna University of Economics and BusinessViennaAustria

Personalised recommendations