OC-PM: analyzing object-centric event logs and process models
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Published:2022-09-20
Issue:1
Volume:25
Page:1-17
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ISSN:1433-2779
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Container-title:International Journal on Software Tools for Technology Transfer
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language:en
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Short-container-title:Int J Softw Tools Technol Transfer
Author:
Berti Alessandro,van der Aalst Wil M. P.
Abstract
AbstractObject-centric process mining is a novel branch of process mining that aims to analyze event data from mainstream information systems (such as SAP) more naturally, without being forced to form mutually exclusive groups of events with the specification of a case notion. The development of object-centric process mining is related to exploiting object-centric event logs, which includes exploring and filtering the behavior contained in the logs and constructing process models which can encode the behavior of different classes of objects and their interactions (which can be discovered from object-centric event logs). This paper aims to provide a broad look at the exploration and processing of object-centric event logs to discover information related to the lifecycle of the different objects composing the event log. Also, comprehensive tool support (OC-PM) implementing the proposed techniques is described in the paper.
Funder
RWTH Aachen University
Publisher
Springer Science and Business Media LLC
Subject
Information Systems,Software
Reference28 articles.
1. van der Aalst, W.M.P.: Process mining - data science in action, second Edition. Springer, New York City (2016). https://doi.org/10.1007/978-3-662-49851-4 2. van der Aalst, W.M.P.: Object-Centric Process Mining: Dealing with Divergence and Convergence in Event Data. In: Ölveczky, P.C., Salaün, G. (eds.) Software Engineering and Formal Methods - 17th International Conference, SEFM 2019, Oslo, Norway, September 18-20, 2019, Proceedings. Lecture Notes in Computer Science, vol. 11724, pp. 3–25. Springer, New York City (2019). https://doi.org/10.1007/978-3-030-30446-1_1 3. Adams, J.N., van der Aalst, W.M.P.: Oc$$\pi $$: Object-centric process insights. In: Bernardinello, L., Petrucci, L. (eds.) Application and Theory of Petri Nets and Concurrency - 43rd International Conference, PETRI NETS 2022, Bergen, Norway, June 19-24, 2022, Proceedings. Lecture Notes in Computer Science, vol. 13288, pp. 139–150. Springer, New York (2022). https://doi.org/10.1007/978-3-031-06653-5_8 4. Ghahfarokhi, A.F., Park, G., Berti, A., van der Aalst, W.M.P.: OCEL: A standard for object-centric event logs. In: Bellatreche, L., Dumas, M., Karras, P., Matulevicius, R., Awad, A., Weidlich, M., Ivanovic, M., Hartig, O. (eds.) New Trends in Database and Information Systems - ADBIS 2021 Short Papers, Doctoral Consortium and Workshops: DOING, SIMPDA, MADEISD, MegaData, CAoNS, Tartu, Estonia, August 24-26, 2021, Proceedings. Communications in Computer and Information Science, vol. 1450, pp. 169–175. Springer, New York City (2021). https://doi.org/10.1007/978-3-030-85082-1_16 5. Berti, A., Farhang, A., Park, G., van der Aalst, W.M.P.: A scalable database for the storage of object-centric event logs. In: ICPM 2021 Doctoral Consortium and Demo Track 2021. CEUR Workshop Proceedings, vol. 3098, pp. 19–20. CEUR-WS.org, Sun SITE Central Europe (2021). http://ceur-ws.org/Vol-3098/demo_137.pdf
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