Wil's References for the year 2020!

Looking back at 2020, it was an exceptionally productive year in which many of the foundations for our current work were laid. A particularly important development was the move toward object-centric process mining: the papers on Discovering Object-Centric Petri Nets and Extracting Multiple Viewpoint Models from Relational Databases challenged the traditional assumption that every event needs to be forced into a single case notion and provided new ways to capture the true fabric of interconnected processes. At the same time, we worked extensively on making process mining more robust and scalable, with contributions on uncertain event data, faster and approximate conformance checking, incremental and scalable process discovery, and improved token-based replay. Another major theme was privacy-preserving process mining, including work on privacy models, abstraction, encryption, and privacy-preserving data publishing, addressing an increasingly important prerequisite for applying process mining to sensitive domains such as healthcare. Several papers also pushed process mining beyond retrospective analysis toward operational support: work on performance spectra and dynamic bottlenecks helped diagnose performance problems, while combining process mining with system dynamics opened new possibilities for data-driven simulation and decision support. Other contributions addressed organizational mining, blockchain logging, workflow-engine integration, resource-centric analysis, event-log repair, and the relationship between process mining, RPA, automation, and AI. 2020 was also the year in which our Alexander von Humboldt Professorship project at RWTH Aachen really kicked off, allowing us to expand the team substantially and explore these new research directions in parallel. Despite the disruptions caused by COVID-19, the breadth of the work shows how rapidly process mining was developing from a collection of analysis techniques into a much broader discipline connecting data science, process science, simulation, automation, and operational decision making. I invite you to browse the complete list of 2020 publications and, more importantly, to read the papers themselves—many of the ideas explored here are likely to shape process mining research and applications for years to come.

I try to update my webpage once per year and provide as many papers as possible. Enjoy reading! Click here to return to my home page and here for all publications.

  1. W.M.P. van der Aalst and A. Berti. Discovering Object-Centric Petri Nets. Fundamenta Informaticae, 175(1-4):1-40, 2020.
  2. W.M.P. van der Aalst, O. Hinz, and C. Weinhardt. Impact of COVID-19 on BISE Research and Education. Business and Information Systems Engineering, 62(6):463-466, 2020.
  3. T. Brockhoff, M.S. Uysal, and W.M.P. van der Aalst. Time-aware Concept Drift Detection Using the Earth Mover's Distance. In B.F. van Dongen, M. Montali, and M. Wynn, editors, International Conference on Process Mining (ICPM 2020), pages 33-40. IEEE Computer Society, 2020.
  4. W.M.P. van der Aalst. Process Mining as the Bridge between Process Science and Data Science (11 Lessons). Listenable Audio Courses, listenable.io, 2020.
  5. M. Dees, B.Hompes, and W.M.P. van der Aalst. Events Put into Context (EPiC). In B.F. van Dongen, M. Montali, and M. Wynn, editors, International Conference on Process Mining (ICPM 2020), pages 65-72. IEEE Computer Society, 2020.
  6. W.M.P. van der Aalst, A. Auli, S. Remsen, M. Rosik, and H. Jansen. How to become a process hero in your company? PEX Process Excellence Network, 2020.
  7. Z. Toosinezhad, D. Fahland, O. Koroglu, and W.M.P. van der Aalst. Detecting System-Level Behavior Leading To Dynamic Bottlenecks. In B.F. van Dongen, M. Montali, and M. Wynn, editors, International Conference on Process Mining (ICPM 2020), pages 17-24. IEEE Computer Society, 2020. (Winner Best Paper Award ICPM 2020) Winner of the ICPM 2020 best paper award.
  8. M. Fani Sani, J.J.G. Gonzalez, S.J. van Zelst, and W.M.P. van der Aalst. Conformance Checking Approximation Using Simulation. In B.F. van Dongen, M. Montali, and M. Wynn, editors, International Conference on Process Mining (ICPM 2020), pages 105-112. IEEE Computer Society, 2020.
  9. W.M.P. van der Aalst. Process Mining as the Superglue between Data and Process Management. In M. van Sinderen, H.G. Fill, and L.A. Maciaszek, editors, Proceedings of the 15th International Conference on Software Technologies (ICSOFT 2020), pages 7-8. ScitePress, 2020.
  10. M. Pourbafrani, S.J. van Zelst, and W.M.P. van der Aalst. Supporting Decisions in Production Line Processes by Combining Process Mining and System Dynamics. In T.Z. Ahram, W. Karwowski, and A. Vergnano, editors, Proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020), volume 1131 of Advances in Intelligent Systems and Computing, pages 461-467. Springer-Verlag, Berlin, 2020.
  11. M. Rafiei, M. Wagner, and W.M.P. van der Aalst. TLKC-Privacy Model for Process Mining. In F. Dalpiaz, J. Zdravkovic, and P. Loucopoulos, editors, International Conference on Research Challenges in Information Science (RCIS 2020), volume 385 of Lecture Notes in Business Information Processing, pages 398-416. Springer-Verlag, Berlin, 2020. Distinguished Paper Award RCIS 2020.
  12. A. Pika, M. Wynn, S. Budiono, A. ter Hofstede, W.M.P. van der Aalst, and H. Reijers. Privacy-Preserving Process Mining in Healthcare. Environmental Research and Public Health, 17(5):1216:1-18, 2020.
  13. G. Schuh, A. Gutzlaff, S. Schmitz, and W.M.P. van der Aalst. Data-Based Description of Process Performance in End-to-End Order Processing. CIRP Annals, 69(1):381-384, 2020.
  14. M. Rafiei and W.M.P. van der Aalst. Towards Quantifying Privacy in Process Mining. Computing Research Repository (CoRR) in arXiv, abs/2012.12031, 2020.
  15. J. Yang, C. Ouyang, W.M.P. van der Aalst, A. ter Hofstede, and Y. Yu. OrgMining 2.0: A Novel Framework for Organizational Model Mining from Event Logs. Computing Research Repository (CoRR) in arXiv, abs/2011.12445, 2020.
  16. W.M.P. van der Aalst. Interview in the 2020 Gartner Market Guide for Process Mining, Research Note G00387812. www.gartner.com, 2020.
  17. W.M.P. van der Aalst and A. Berti. Discovering Object-Centric Petri Nets. Computing Research Repository (CoRR) in arXiv, abs/2010.02047, 2020.
  18. M. Pourbafrani and W.M.P. van der Aalst. PMSD: Data-Driven Simulation Using System Dynamics and Process Mining. Computing Research Repository (CoRR) in arXiv, abs/2010.00943, 2020.
  19. M. Pegoraro, M.S. Uysal, and W.M.P. van der Aalst. Efficient Time and Space Representation of Uncertain Event Data. Computing Research Repository (CoRR) in arXiv, abs/2010.00334, 2020.
  20. M. Pegoraro, M. S. Uysal, and W.M.P. van der Aalst. Conformance Checking over Uncertain Event Data. Computing Research Repository (CoRR) in arXiv, abs/2009.14452, 2020.
  21. D. Schuster, S.J. van Zelst, and W.M.P. van der Aalst. Alignment Approximation for Process Trees. Computing Research Repository (CoRR) in arXiv, abs/2009.14094, 2020.
  22. W.M.P. van der Aalst. How LNCS Helped to Shape the Field of Business Process Management. In The Art and Craft of Scientific Publishing: A Liber Amicorum in Honor of Alfred Hofmann, volume 2020 of LNAH, pages 151-154. Springer-Verlag, Berlin, 2020.
  23. M.Rafiei and W.M.P. van der Aalst. Practical Aspect of Privacy-Preserving Data Publishing in Process Mining. Computing Research Repository (CoRR) in arXiv, abs/2009.11542, 2020.
  24. M. Shankara Narayana, H. Khalifa, and W.M.P. van der Aalst. JXES: JSON Support for the XES Event Log Standard. Computing Research Repository (CoRR) in arXiv, abs/2009.06363, 2020.
  25. A. Berti, W.M.P. van der Aalst, D. Zang, and M. Lang. An Open-Source Integration of Process Mining Features into the Camunda Workflow Engine: Data Extraction and Challenges. Computing Research Repository (CoRR) in arXiv, abs/2009.06209, 2020.
  26. A. Berti and W.M.P. van der Aalst. A Novel Token-Based Replay Technique to Speed Up Conformance Checking and Process Enhancement. Computing Research Repository (CoRR) in arXiv, abs/2007.14237, 2020.
  27. M. Pegoraro, M.S. Uysal, and W.M.P. van der Aalst. Efficient Construction of Behavior Graphs for Uncertain Event Data. Computing Research Repository (CoRR) in arXiv, abs/2002.08225, 2020.
  28. W.M.P. van der Aalst. Bringing Data Insights and Automation Together: The Next Big Thing in Process Mining (Blog Post Celonis). celonis.com, 2020.
  29. C. Klinkmüller, I. Weber, A. Ponomarev, A. Binh Tran, and W.M.P. van der Aalst. Efficient Logging for Blockchain Applications. Computing Research Repository (CoRR) in arXiv, abs/2001.10281, 2020.
  30. A. Berti and W.M.P. van der Aalst. Extracting Multiple Viewpoint Models from Relational Databases. Computing Research Repository (CoRR) in arXiv, abs/2001.02562, 2020.
  31. A. Berti and W.M.P. van der Aalst. Extracting Multiple Viewpoint Models from Relational Databases. In P. Ceravolo, M. van Keulen, and M.T. Gomez Lopez, editors, Postproceedings International Symposium on Data-driven Process Discovery and Analysis, volume 379 of Lecture Notes in Business Information Processing, pages 24-51. Springer-Verlag, Berlin, 2020.
  32. M. Rafiei, L. von Waldthausen, and W.M.P. van der Aalst. Supporting Confidentiality in Process Mining Using Abstraction and Encryption. In P. Ceravolo, M. van Keulen, and M.T. Gomez Lopez, editors, Postproceedings International Symposium on Data-driven Process Discovery and Analysis, volume 379 of Lecture Notes in Business Information Processing, pages 101-123. Springer-Verlag, Berlin, 2020.
  33. W.M.P. van der Aalst, J. vom Brocke, M. Comuzzi, C. Di Ciccio, F. Garcia, A. Kumar, J. Mendling, B. Pentland, L. Pufahl, M. Reichert, and M. Weske, editors. Proceedings of the Best Dissertation Award, Doctoral Consortium, Demonstration and Resources Track at BPM 2020 co-located with the 18th International Conference on Business Process Management (BPM 2020), Sevilla, Spain, September 13-18, 2020, volume 2673 of CEUR Workshop Proceedings. CEUR-WS.org, 2020.
  34. W.M.P. van der Aalst, R. Bergenthum, and J. Carmona, editors. Proceedings of the International Workshop on Algorithms and Theories for the Analysis of Event Data (ATAED 2020), volume 2625 of CEUR Workshop Proceedings. CEUR-WS.org, 2020.
  35. W.M.P. van der Aalst, V. Batagelj, D. Ignatov, M. Khachay, V. Kuskova, A. Kutuzov, S. Kuznetsov, I.A. Lomazova, N. Loukachevitch, A. Napoli, P. Pardalos, M. Pelillo, A. Savchenko, and E. Tutubalina, editors. Analysis of Images, Social Networks and Texts, Revised and Selected Papers of AIST 2019, volume 1086 of Communications in Computer and Information Science. Springer-Verlag, Berlin, 2020.
  36. L. Delcoucq, F. Lecron, P. Fortemps, and W.M.P. van der Aalst. Resource-Centric Process Mining: Clustering Using Local Process Models. In C.C. Hung, T. Cerny, D. Shin, and A. Bechini, editors, Annual ACM Symposium on Applied Computing (SAC 2020), pages 45-52. ACM Press, 2020.
  37. L.L. Mannel, R. Bergenthum, and W.M.P. van der Aalst. Removing Implicit Places Using Regions for Process Discovery. In Proceedings of the International Workshop on Algorithms and Theories for the Analysis of Event Data (ATAED 2020), volume 2625 of CEUR Workshop Proceedings, pages 20-32. CEUR-WS.org, 2020.
  38. V. Denisov, D.Fahland, and W.M.P. van der Aalst. Repairing Event Logs with Missing Events to Support Performance Analysis of Systems with Shared Resources. In R.Janicki, N. Sidorova, and T. Chatain, editors, Applications and Theory of Petri Nets 2020, volume 12152 of Lecture Notes in Computer Science, pages 239-259, 2020.
  39. W.M.P. van der Aalst, D. Tacke Genannt Unterberg, V. Denisov, and D. Fahland. Visualizing Token Flows Using Interactive Performance Spectra. In R.Janicki, N. Sidorova, and T. Chatain, editors, Applications and Theory of Petri Nets 2020, volume 12152 of Lecture Notes in Computer Science, pages 369-380, 2020.
  40. W.M.P. van der Aalst. he Self-Driving Enterprise: To Bring AI to Your Processes, Start With the EMS(Blog Post Celonis). celonis.com, 2020.
  41. M. Pegoraro, M.S. Uysal, and W.M.P. van der Aalst. Efficient Construction of Behavior Graphs for Uncertain Event Data. In W. Abramowicz and G. Klein, editors, International Conference on Business Information Systems (BIS 2020), volume 3389 of Lecture Notes in Business Information Processing, pages 76-88. Springer-Verlag, Berlin, 2020.
  42. M. Pourbafrani, S.J. van Zelst, and W.M.P. van der Aalst. Supporting Automatic System Dynamics Model Generation for Simulation in the Context of Process Mining. In W. Abramowicz and G. Klein, editors, International Conference on Business Information Systems (BIS 2020), volume 3389 of Lecture Notes in Business Information Processing, pages 249-263. Springer-Verlag, Berlin, 2020.
  43. M. Pourbafrani and W.M.P. van der Aalst. PMSD: Data-Driven Simulation Using System Dynamics and Process Mining. In Proceedings of the Demonstration Track of the 18th International Conference on Business Process Management (BPM 2020), volume 2673 of CEUR Workshop Proceedings, pages 77-81. CEUR-WS.org, 2020.
  44. O. Hinz, W.M.P. van der Aalst, and C. Weinhardt. Research in the Attention Economy. Business and Information Systems Engineering, 62(2):83-85, 2020.
  45. M. Rafiei and W.M.P. van der Aalst. Practical Aspect of Privacy-Preserving Data Publishing in Process Mining. In Proceedings of the Demonstration Track of the 18th International Conference on Business Process Management (BPM 2020), volume 2673 of CEUR Workshop Proceedings, pages 92-96. CEUR-WS.org, 2020.
  46. M. Rafiei and W.M.P. van der Aalst. Privacy-Preserving Data Publishing in Process Mining. In D. Fahland, C. Ghidini, J. Becker, and M.Dumas, editors, Business Process Management Forum (BPM Forum 2020), volume 392 of Lecture Notes in Business Information Processing, pages 122-138. Springer-Verlag, Berlin, 2020.
  47. M. Fani Sani, S.J. van Zelst, and W.M.P. van der Aalst. Conformance Checking Approximation Using Subset Selection and Edit Distance. In S. Dustdar, E. Yu, C. Salinesi, D. Rieu, and V.Pant, editors, International Conference on Advanced Information Systems Engineering (CAiSE 2020), volume 12127 of Lecture Notes in Computer Science, pages 234-251. Springer-Verlag, Berlin, 2020.
  48. W.M.P. van der Aalst. On the Pareto Principle in Process Mining and Task Mining and and Robotic Process Automation. In S. Hammoudi, C. Quix, and J. Bernardino, editors, Proceedings of the 9th International Conference on Data Science, Technology and Applications (DATA 2020), pages 5-12. SciTePress, 2020.
  49. C. Weinhardt, S. Kloker, O. Hinz, and W.M.P. van der Aalst. Citizen Science in Information Systems Research. Business and Information Systems Engineering, 62(4):273-277, 2020.
  50. M. Pourbafrani, S.J. van Zelst, and W.M.P. van der Aalst. Semi-automated Time-Granularity Detection for Data-Driven Simulation Using Process Mining and System Dynamics. In G. Dobbie, U. Frank, G. Kappel, S. Liddle, and H.C. Mayr, editors, International Conference on Conceptual Modeling (ER 2020), volume 12400 of Lecture Notes in Computer Science, pages 77-91, 2020.
  51. A. Berti, W.M.P. van der Aalst, D. Zang, and M. Lang. An Open-Source Integration of Process Mining Features Into the Camunda Workflow Engine: Data Extraction and Challenges. In C. Di Ciccio, B. Depaire, J. De Weerdt, C. Di Francescomarino, and J.Munoz-Gama, editors, Proceedings of the ICPM Doctoral Consortium and Tool Demonstration Track 2020 co-located with the 2nd International Conference on Process Mining (ICPM 2020), volume 2703 of CEUR Workshop Proceedings, pages 23-26. CEUR-WS.org, 2020.
  52. V. Denisov, D. Fahland, and W.M.P. van der Aalst. Multi-Dimensional Performance Analysis and Monitoring Using Integrated Performance Spectra. In C. Di Ciccio, B. Depaire, J. De Weerdt, C. Di Francescomarino, and J.Munoz-Gama, editors, Proceedings of the ICPM Doctoral Consortium and Tool Demonstration Track 2020 co-located with the 2nd International Conference on Process Mining (ICPM 2020), volume 2703 of CEUR Workshop Proceedings, pages 27-30. CEUR-WS.org, 2020.
  53. W.M.P. van der Aalst. Process Mining and RPA: How To Pick Your Automation Battles? (Blog Post PEX Network, January 2020). PEX Process Excellence Network, www.processexcellencenetwork.com, 2020.
  54. D. Schuster, S.J. van Zelst, and W.M.P. van der Aalst. Incremental Discovery of Hierarchical Process Models. In F. Dalpiaz, J. Zdravkovic, and P. Loucopoulos, editors, International Conference on Research Challenges in Information Science (RCIS 2020), volume 385 of Lecture Notes in Business Information Processing, pages 417-433. Springer-Verlag, Berlin, 2020.
  55. S. Mann, J. Pennekamp, T. Brockhoff, A. Farhang, M. Pourbafrani, L. Oster, M.S. Uysal, R. Sharma, U. Reisgen, K. Wehrle, and W.M.P. van der Aalst. Connected, Digitalized Welding Production—Secure, Ubiquitous Utilization of Data Across Process Layers. In L.F.M. da Silva, P.A.F. Martins, and M.S. El-Zein, editors, Advanced Joining Processes, volume 125 of Advanced Structured Materials, pages 101-108. Springer-Verlag, Berlin, 2020.
  56. W.M.P. van der Aalst. The Data Science Revolution: How Learning Machines Changed the Way We Work and Do Business. In L. Strous, R. Johnson, D. Grier, and D. Swade, editors, Unimagined Futures: ICT Opportunities and Challenges, volume 555 of IFIP Advances in Information and Communication Technology, pages 5-19. Springer-Verlag, Berlin, 2020.
  57. M. Fani Sani, S.J. van Zelst, and W.M.P. van der Aalst. Improving the Performance of Process Discovery Algorithms By Instance Selection. Computer Science and Information Systems, 17(3):927-958, 2020.
  58. M. Pegoraro, M.S. Uysal, and W.M.P. van der Aalst. Efficient Time and Space Representation of Uncertain Event Data. Algorithms, 13(11):285:1-27, 2020.
  59. L. Cheng, B.F. van Dongen, and W.M.P. van der Aalst. Scalable Discovery of Hybrid Process Models in a Cloud Computing Environment. IEEE Transactions on Services Computing, 13(2):368-380, 2020.
  60. W.M.P. van der Aalst. Development of the Process Mining Discipline. In L. Reinkemeyer, editor, Process Mining in Action: Principles, Use Cases and Outlook, pages 181-196. Springer-Verlag, Berlin, 2020.
  61. E.G.L. de Murillas, H.A. Reijers, and W.M.P. van der Aalst. Case Notion Discovery and Recommendation: Automated Event Log Building on Databases. Knowledge and Information Systems, 62(7):2539-2575, 2020.

For reflections on 2025, 2024, 2023, 2022, 2021 2020, 2019, and 2018 see the respective pages.