Abstract
Process mining tools use Directly-Follows Graphs (DFGs) as the main means of visualization for exploring event logs and extracting valuable insights therefrom. Extracting significant insights from DFGs is a laborious process that involves multiple data manipulation operations and comparisons between the resulting DFGs generated after each manipulation. However, current process mining tools lack the ability to uniformly manipulate and manage multiple DFGs in a consistent manner. The objective of this study is to identify the requirements for designing a user-friendly interface to handle collections of DFGs to search for interesting visualizations for process mining analysis. To achieve this, three different data sources were used: a literature review of visual query tools, the analysis of LoVizQL, a query language for process mining, and the examination of reports from Business Process Intelligence Challenges. By combining these sources, insights into interface design needs aligned with real process mining applications were obtained. As a result, we have identified 14 requirements grouped into 3 main categories. These requirements serve as the basis to build future user interfaces of visual query tools for process mining.
This work has been funded by projects PID2022-140221NB-I00 (TAPIOCA), PID2021-126227NB-C21 (PERSEO) and TED2021-131023B-C22 (ORCHID) granted by MCIN/AEI/10.13039/501100011033/ and ERDF A way of making Europe. M. Salas-Urbano is supported by PREP2022-000372 financed by MICIN/AEI/10.13039/501100011033 and by FSE+. C. Capitán-Agudo is supported by the Spanish Ministry of Education under the FPU national plan (FPU21/03631).
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References
Alman, A., Di Ciccio, C., Maggi, F.M., Montali, M., van der Aa, H.: RuM: declarative process mining, distilled. In: Polyvyanyy, A., Wynn, M.T., Van Looy, A., Reichert, M. (eds.) BPM 2021. LNCS, vol. 12875, pp. 23–29. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-85469-0_3
Capitán-Agudo, C., Salas-Urbano, M., Cabanillas, C., Resinas, M.: Analyzing how process mining reports answer time performance questions. In: Di Ciccio, C., Dijkman, R., del Río Ortega, A., Rinderle-Ma, S. (eds.) BPM 2022. LNCS, vol. 13420, pp. 234–250. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-16103-2_17
Catarci, T., Costabile, M.F., Levialdi, S., Batini, C.: Visual query systems for databases: a survey. J. Vis. Lang. Comput. 8(2), 215–260 (1997). https://doi.org/10.1006/jvlc.1997.0037
Cohn, M.: User Stories Applied: For Agile Software Development. Addison-Wesley Professional, Boston (2004)
van Dongen, B.: BPI Challenge 2015. 4TU.ResearchData (2015). https://doi.org/10.4121/uuid:31a308ef-c844-48da-948c-305d167a0ec1
van Dongen, B.: BPI Challenge 2016. 4TU.ResearchData (2016). https://doi.org/10.4121/uuid:360795c8-1dd6-4a5b-a443-185001076eab
van Dongen, B.: BPI Challenge 2017. 4TU.ResearchData (2017). https://doi.org/10.4121/uuid:5f3067df-f10b-45da-b98b-86ae4c7a310b
van Dongen, B.: BPI Challenge 2018. 4TU.ResearchData (2018). https://doi.org/10.4121/uuid:3301445f-95e8-4ff0-98a4-901f1f204972
van Dongen, B.: BPI Challenge 2019. 4TU.ResearchData (2019). https://doi.org/10.4121/uuid:d06aff4b-79f0-45e6-8ec8-e19730c248f1
van Dongen, B.: BPI Challenge 2020. 4TU.ResearchData (2020). https://doi.org/10.4121/uuid:52fb97d4-4588-43c9-9d04-3604d4613b51
Imani, S., Alaee, S., Keogh, E.: Qute: query by text search for time series data. In: Arai, K., Kapoor, S., Bhatia, R. (eds.) FTC 2020. AISC, vol. 1289, pp. 412–427. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-63089-8_27
Klinkmüller, C., Müller, R., Weber, I.: Mining process mining practices: an exploratory characterization of information needs in process analytics. In: International Conference on Business Process Management, pp. 322–337 (2019). https://doi.org/10.1007/978-3-030-26619-6_21
Kubrak, K., Milani, F., Nolte, A., Dumas, M.: Design and evaluation of a user interface concept for prescriptive process monitoring. In: Indulska, M., Reinhartz-Berger, I., Cetina, C., Pastor, O. (eds.) Advanced Information Systems Engineering, CAiSE 2023. Lecture Notes in Computer Science, vol. 13901, pp. 347–363. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-34560-9_21
Lee, D.J.L., Kim, J., Wang, R., Parameswaran, A.: Scattersearch: Visual querying of scatterplot visualizations. arXiv preprint arXiv:1907.11743 (2019)
Lee, D.J.L., Lee, J., Siddiqui, T., Kim, J., Karahalios, K., Parameswaran, A.: You can’t always sketch what you want: understanding sensemaking in visual query systems. IEEE Trans. Vis. Comput. Graph. 26(1), 1267–1277 (2020). https://doi.org/10.1109/TVCG.2019.2934666
Lee, D.J.L., Siddiqui, T., Karahalios, K., Parameswaran, A.: Three lessons from accelerating scientific insight discovery via visual querying. Patterns 1(7), 100126 (2020). https://doi.org/10.1016/j.patter.2020.100126
Leemans, S.J., Poppe, E., Wynn, M.T.: Directly follows-based process mining: exploration & a case study. In: International Conference on Process Mining, pp. 25–32. IEEE (2019). https://doi.org/10.1109/ICPM.2019.00015
Mannino, M., Abouzied, A.: Expressive time series querying with hand-drawn scale-free sketches. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, pp. 1–13 (2018). https://doi.org/10.1145/3173574.3173962
Polyvyanyy, A.: Process Querying Methods. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-92875-9
Salas-Urbano, M., Capitán-Agudo, C., Cabanillas, C., Resinas, M.: LoVizQL: a query language for visualizing and analyzing business processes from event logs. In: Monti, F., Rinderle-Ma, S., Ruiz Cortés, A., Zheng, Z., Mecella, M. (eds.) ICSOC 2023. LNCS, vol. 14420, pp. 13–28. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-48424-7_2
Siddiqui, T., et al.: Fast-forwarding to desired visualizations with zenvisage. In: 8th Biennial Conference on Innovative Data Systems Research (2017)
Siddiqui, T., Luh, P., Wang, Z., Karahalios, K., Parameswaran, A.: Shapesearch: a flexible and efficient system for shape-based exploration of trendlines. In: Proceedings of ACM SIGMOD International Conference on Management of Data, pp. 51–65 (2020). https://doi.org/10.1145/3318464.3389722
Siddiqui, T., Luh, P., Wang, Z., Karahalios, K., Parameswaran, A.G.: From sketching to natural language: expressive visual querying for accelerating insight. ACM SIGMOD Rec. 50(1), 51–58 (2021). https://doi.org/10.1145/3471485.3471498
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Salas-Urbano, M., Capitán-Agudo, C., Cabanillas, C., Resinas, M. (2024). Designing a User Interface to Explore Collections of Directly-Follows Graphs for Process Mining Analysis. In: van der Aa, H., Bork, D., Schmidt, R., Sturm, A. (eds) Enterprise, Business-Process and Information Systems Modeling. BPMDS EMMSAD 2024 2024. Lecture Notes in Business Information Processing, vol 511. Springer, Cham. https://doi.org/10.1007/978-3-031-61007-3_4
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