×

zbMATH — the first resource for mathematics

Discovering object-centric Petri nets. (English) Zbl 07350058
Summary: Techniques to discover Petri nets from event data assume precisely one case identifier per event. These case identifiers are used to correlate events, and the resulting discovered Petri net aims to describe the life-cycle of individual cases. In reality, there is not one possible case notion, but multiple intertwined case notions. For example, events may refer to mixtures of orders, items, packages, customers, and products. A package may refer to multiple items, multiple products, one order, and one customer. Therefore, we need to assume that each event refers to a collection of objects, each having a type (instead of a single case identifier). Such object-centric event logs are closer to data in real-life information systems. From an object-centric event log, we want to discover an object-centric Petri net with places that correspond to object types and transitions that may consume and produce collections of objects of different types. Object-centric Petri nets visualize the complex relationships among objects from different types. This paper discusses a novel process discovery approach implemented in PM4Py. As will be demonstrated, it is indeed feasible to discover holistic process models that can be used to drill-down into specific viewpoints if needed.
MSC:
68-XX Computer science
PDF BibTeX XML Cite
Full Text: DOI
References:
[1] Ehrenfeucht A, Rozenberg G. Partial (Set) 2-Structures - Part 1 and Part 2.Acta Informatica, 1989. 27(4):315-368. doi:10.1007/BF00264612.
[2] Badouel E, Bernardinello L, Darondeau P. Petri Net Synthesis. Texts in Theoretical Computer Science. An EATCS Series. Springer-Verlag, Berlin, 2015. doi:10.5555/2851516. · Zbl 1351.68003
[3] Badouel E, Darondeau P. Theory of Regions. In: Reisig W, Rozenberg G (eds.), Lectures on Petri Nets I: Basic Models, volume 1491 ofLecture Notes in Computer Science. Springer-Verlag, Berlin, 1998 pp. 529-586. doi:10.1007/3-540-65306-6 22.
[4] Desel J, Reisig W. The Synthesis Problem of Petri Nets.Acta Informatica, 1996.33(4):297-315. doi:10.1007/ s002360050046. · Zbl 0849.68085
[5] Kleijn J, Koutny M, Pietkiewicz-Koutny M, Rozenberg G. Applying Regions.Theoretical Computer Science, 2017.658:205-215. doi:10.1016/j.tcs.2016.01.040. · Zbl 1355.68192
[6] Cortadella J, Kishinevsky M, Lavagno L, Yakovlev A. Deriving Petri Nets from Finite Transition Systems. IEEE Transactions on Computers, 1998.47(8):859-882. doi:10.1109/12.707587. · Zbl 1392.68291
[7] Carmona J, Cortadella J, Kishinevsky M, Kondratyev A, Lavagno L, Yakovlev A. A Symbolic Algorithm for the Synthesis of Bounded Petri Nets. In: Applications and Theory of Petri Nets (Petri Nets 2008). 2008 pp. 92-111. doi:10.1007/978-3-540-68746-7 10. · Zbl 1143.68478
[8] Carmona J, Cortadella J, Kishinevsky M. New Region-Based Algorithms for Deriving Bounded Petri Nets.IEEE Transactions on Computers, 2010.59(3):371-384. doi:10.1109/TC.2009.131. · Zbl 1368.68259
[9] Kleijn J, Koutny M, Pietkiewicz-Koutny M. Regions of Petri nets with a/sync connections.Theoretical Computer Science, 2012.454:189-198. doi:10.1016/j.tcs.2012.04.016. · Zbl 1267.68156
[10] Darondeau P. On the Synthesis of Zero-Safe Nets. In: Concurrency, Graphs and Models, volume 5065 of Lecture Notes in Computer Science. Springer-Verlag, Berlin, 2008 pp. 364-378. doi:10.1007/978-3-54068679-8 25. · Zbl 1143.68481
[11] Bergenthum R, Desel J, Lorenz R, Mauser S. Process Mining Based on Regions of Languages. In: Alonso G, Dadam P, Rosemann M (eds.), International Conference on Business Process Management (BPM 2007), volume 4714 ofLecture Notes in Computer Science. Springer-Verlag, Berlin, 2007 pp. 375- 383. doi:10.1007/978-3-540-75183-0 27.
[12] Lorenz R, Bergenthum R, Desel J, Mauser S. Synthesis of Petri Nets from Finite Partial Languages. In: Basten T, Juh´as G, Shukla S (eds.), International Conference on Application of Concurrency to System Design (ACSD 2007). IEEE Computer Society, 2007 pp. 157-166. doi:10.1109/ACSD.2007.34. · Zbl 1167.68037
[13] Bergenthum R, Desel J, Lorenz R, Mauser S. Synthesis of Petri Nets from Finite Partial Languages. Fundamenta Informaticae, 2008.88(4):437-468. doi:10.1109/ACSD.2007.34. · Zbl 1167.68037
[14] van Dongen B, Desel J, van der Aalst WMP. Aggregating Causal Runs into Workflow Nets. In: Jensen K, van der Aalst WMP, Marsan MA, Franceschinis G, Kleijn J, Kristensen L (eds.), Transactions on Petri Nets and Other Models of Concurrency (ToPNoC VI), volume 7400 ofLecture Notes in Computer Science. Springer-Verlag, Berlin, 2012 pp. 334-363. doi:10.1007/978-3-642-35179-2 14. · Zbl 1377.68154
[15] Bergenthum R, Desel J, Mauser S, Lorenz R. Synthesis of Petri Nets from Term Based Representations of Infinite Partial Languages.Fundamenta Informaticae, 2009.95(1):187-217. doi:10.3233/FI-2009-147. · Zbl 1217.68147
[16] Lorenz R, Juh´as G. How to Synthesize Nets from Languages: A Survey. In: Henderson S, Biller B, Hsieh M, Shortle J, Tew JD, Barton RR (eds.), Proceedings of the Wintersimulation Conference (WSC 2007). IEEE Computer Society, 2007 pp. 637-647. doi:10.1109/WSC.2007.4419657.
[17] Lorenz R, Juhas G. Towards Synthesis of Petri Nets from Scenarios. In: Donatelli S, Thiagarajan P (eds.), Application and Theory of Petri Nets 2006, volume 4024 ofLecture Notes in Computer Science. Springer-Verlag, Berlin, 2006 pp. 302-321. doi:10.1007/11767589 17. · Zbl 1217.68152
[18] Bergenthum R, Desel J, Lorenz R, Mauser S. Synthesis of Petri Nets from Scenarios with VipTool. In: Applications and Theory of Petri Nets (Petri Nets 2008), volume 5062 ofLecture Notes in Computer Science. Springer-Verlag, Berlin, 2008 pp. 388-398. doi:10.1007/978-3-540-68746-7 25. · Zbl 1167.68037
[19] Lorenz R, Desel J, Juhas G. Models from Scenarios. In: Jensen K, van der Aalst WMP, Balbo G, Koutny M, Wolf K (eds.), Transactions on Petri Nets and Other Models of Concurrency (ToPNoC VII), volume 7480 ofLecture Notes in Computer Science. Springer-Verlag, Berlin, 2013 pp. 314-371. 10.1007/978-3642-38143-0 9. · Zbl 1382.68152
[20] Carmona J, Cortadella J, Kishinevsky M. A Region-Based Algorithm for Discovering Petri Nets from Event Logs. In: Business Process Management (BPM 2008). 2008 pp. 358-373. doi:10.1007/978-3-54085758-7 26.
[21] Sol´e M, Carmona J. Process Mining from a Basis of State Regions. In: Lilius J, Penczek W (eds.), Applications and Theory of Petri Nets 2010, volume 6128 ofLecture Notes in Computer Science. SpringerVerlag, Berlin, 2010 pp. 226-245. doi:10.1007/978-3-642-13675-7 14. · Zbl 1233.68170
[22] van Zelst S, van Dongen B, van der Aalst WMP, Verbeek H. Discovering Workflow Nets Using Integer Linear Programming.Computing, 2018.100(5):529-556. doi:10.1007/s00607-017-0582-5. · Zbl 1395.90166
[23] van der Aalst WMP. A Practitioner’s Guide to Process Mining: Limitations of the Directly-Follows Graph. In: International Conference on Enterprise Information Systems (Centeris 2019), volume 164 ofProcedia Computer Science. Elsevier, 2019 pp. 321-328. doi:10.1016/j.procs.2019.12.189.
[24] Leemans S, Fahland D, van der Aalst WMP. Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour. In: Lohmann N, Song M, Wohed P (eds.), Business Process Management Workshops, Int. Workshop on Business Process Intelligence (BPI 2013), vol. 171 ofLecture Notes in Business Information Processing. Springer, 2014 pp. 66-78. doi:10.1007/978-3-319-06257-0 6.
[25] Leemans S, Fahland D, van der Aalst WMP. Scalable Process Discovery with Guarantees. In: Gaaloul K, Schmidt R, Nurcan S, Guerreiro S, Ma Q (eds.), Enterprise, Business-Process and Information Systems Modeling (BPMDS 2015), volume 214 ofLecture Notes in Business Information Processing. SpringerVerlag, Berlin, 2015 pp. 85-101. doi:10.1007/978-3-319-19237-6 6.
[26] Augusto A, Conforti R, Marlon M, La Rosa M, Polyvyanyy A. Split Miner: Automated Discovery of Accurate and Simple Business Process Models from Event Logs.Knowledge Information Systems, 2019. 59(2):251-284. doi:10.1007/s10115-018-1214-x.
[27] van der Aalst WMP. Object-Centric Process Mining: Dealing With Divergence and Convergence in Event Data. In: ¨Olveczky P, Sala¨un G (eds.), Software Engineering and Formal Methods (SEFM 2019), volume 11724 ofLecture Notes in Computer Science. Springer-Verlag, Berlin, 2019 pp. 3-25. doi:10.1007/9783-030-30446-1 1.
[28] Li G, Medeiros de Carvalho R, van der Aalst WMP. Automatic Discovery of Object-Centric Behavioral Constraint Models.In: Abramowicz W (ed.), Business Information Systems (BIS 2017), volume 288 ofLecture Notes in Business Information Processing. Springer-Verlag, Berlin, 2017 pp. 43-58. doi:10.1007/978-3-319-59336-4 4.
[29] van Eck M, Sidorova N, van der Aalst WMP. Guided Interaction Exploration in Artifact-centric Process Models. In: IEEE Conference on Business Informatics (CBI 2017). IEEE Computer Society, 2017 pp. 109-118. doi:10.1109/CBI.2017.42.
[30] van Eck M, Sidorova N, van der Aalst WMP. Multi-instance Mining: Discovering Synchronisation in Artifact-Centric Processes. In: Daniel F, Sheng Q, Motahari H (eds.), Business Process Management Workshops, International Workshop on Business Process Intelligence (BPI 2018), volume 342 ofLecture Notes in Business Information Processing. Springer-Verlag, Berlin, 2018 pp. 18-30. doi:10.1007/978-3030-11641-5 2.
[31] Fahland D, de Leoni M, van Dongen B, van der Aalst WMP. Behavioral Conformance of Artifact-Centric Process Models. In: Abramowicz A (ed.), Business Information Systems (BIS 2011), volume 87 ofLecture Notes in Business Information Processing. Springer-Verlag, Berlin, 2011 pp. 37-49. doi:10.1007/978-3642-21863-7 4.
[32] Fahland D, de Leoni M, van Dongen B, van der Aalst WMP. Many-to-Many: Some Observations on Interactions in Artifact Choreographies. In: Eichhorn D, Koschmider A, Zhang H (eds.), Proceedings of the 3rd Central-European Workshop on Services and their Composition (ZEUS 2011), CEUR Workshop Proceedings. CEUR-WS.org, 2011 pp. 9-15. URL: http://ceur-ws.org/Vol-705/paper1.pdf.
[33] Lu X, Nagelkerke M, van de Wiel D, Fahland D. Discovering Interacting Artifacts from ERP Systems. IEEE Transactions on Services Computing, 2015.8(6):861-873. doi:10.1109/TSC.2015.2474358.
[34] van der Aalst WMP. Process Mining: Data Science in Action. 2016. doi:10.1007/978-3-662-49851-4 1.
[35] IEEE Task Force on Process Mining. XES Standard Definition. www.xes-standard.org, 2013.
[36] Lu X, Fahland D, van der Aalst WMP. Conformance Checking Based on Partially Ordered Event Data. In: Fournier F, Mendling J (eds.), Business Process Management Workshops, International Workshop on Business Process Intelligence (BPI 2014), volume 202 ofLecture Notes in Business Information Processing. Springer-Verlag, Berlin, 2015 pp. 75-88. doi:10.1007/978-3-319-15895-2 7.
[37] van der Aalst WMP, Stahl C. Modeling Business Processes: A Petri Net Oriented Approach. MIT Press, Cambridge, MA, 2011. ISBN: 978-0-262-01538-7. · Zbl 1216.00032
[38] Jensen K, Kristensen L. Coloured Petri Nets. Springer-Verlag, Berlin, 2009. doi:10.1007/b95112. W.M.P. van der Aalst and A. Berti/Discovering Object-centric Petri Nets39 · Zbl 1215.68153
[39] Berti A, van der Aalst WMP. StarStar Models: Using Events at Database Level for Process Analysis. In: Ceravolo P, Keulen M, Lopez MG (eds.), International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2018), volume 2270 ofCEUR Workshop Proceedings. CEUR-WS.org, 2018 pp. 60-64. URL: http://ceur-ws.org/Vol-2270/short3.pdf.
[40] Berti A, van der Aalst WMP. Discovering Multiple Viewpoint Models from Relational Databases. In: Ceravolo P, Keulen M, Lopez MG (eds.), Postproceedings International Symposium on Data-driven Process Discovery and Analysis, volume 379 ofLecture Notes in Business Information Processing. SpringerVerlag, Berlin, 2020 pp. 24-51. doi:10.1007/978-3-030-46633-6 2.
[41] Leemans S, Fahland D, van der Aalst WMP.Scalable Process Discovery and Conformance Checking.Software and Systems Modeling, 2018.17(2):599-631.doi:10.1007/s10270-016-0545-x. doi:10.1007/s10270-016-0545-x.
[42] Berti A, van der Aalst WMP. Reviving Token-based Replay: Increasing Speed While Improving Diagnostics. In: Proceedings of the International Workshop on Algorithms and Theories for the Analysis of Event Data (ATAED 2019), volume 2371 ofCEUR Workshop Proceedings. CEUR-WS.org, 2019 pp. 87-103. URL:http://ceur-ws.org/Vol-2371/ATAED2019-87-103.pdf.
[43] Rozinat A, van der Aalst WMP. Conformance Checking of Processes Based on Monitoring Real Behavior. Information Systems, 2008.33(1):64-95. doi:10.1016/j.is.2007.07.001.
[44] van der Aalst WMP. The Application of Petri Nets to Workflow Management.The Journal of Circuits, Systems and Computers, 1998.8(1):21-66. doi:10.1142/S0218126698000043,
[45] van der Aalst WMP, Hee K, ter Hofstede A, Sidorova N, Verbeek H, Voorhoeve M, Wynn M. Soundness of Workflow Nets: Classification, Decidability, and Analysis.Formal Aspects of Computing, 2011. 23(3):333-363. doi:10.1007/s00165-010-0161-4. · Zbl 1225.68129
[46] Leemans S, Fahland D, van der Aalst WMP. Discovering Block-structured Process Models from Event Logs: A Constructive Approach. In: Colom J, Desel J (eds.), Applications and Theory of Petri Nets 2013, volume 7927 ofLecture Notes in Computer Science. Springer-Verlag, Berlin, 2013 pp. 311-329. doi:10.1007/978-3-642-38697-8 17. · Zbl 1381.68211
[47] OMG. Business Process Model and Notation (BPMN). Object Management Group, formal/2011-01-03, 2011. URL: https://www.omg.org/spec/BPMN/2.0/PDF.
[48] Scheer A. Business Process Engineering: Reference Models for Industrial Enterprises. Springer-Verlag, Berlin, 1994. ISBN: 978-3-540-58234-2.
[49] IBM. IBM MQSeries Workflow - Getting Started With Buildtime. IBM Deutschland Entwicklung GmbH, Boeblingen, Germany, 1999. URL:ftp://public.dhe.ibm.com/ps/products/workflow/docu/ v322/pdf/enu/fmcu0mst.pdf.
[50] van der Aalst WMP, ter Hofstede A, Kiepuszewski B, Barros A. Workflow Patterns.Distributed and Parallel Databases, 2003.14(1):5-51. doi:10.1023/A:1022883727209.
[51] van der Aalst WMP, Barthelmess P, Ellis C, Wainer J. Workflow Modeling using Proclets. In: Etzion O, Scheuermann P (eds.), 7th International Conference on Cooperative Information Systems (CoopIS 2000), volume 1901 ofLecture Notes in Computer Science. Springer-Verlag, Berlin, 2000 pp. 198-209. doi:10.1007/10722620 20.
[52] van der Aalst WMP, Barthelmess P, Ellis C, Wainer J. Proclets: A Framework for Lightweight Interacting Workflow Processes.International Journal of Cooperative Information Systems, 2001.10(4):443-482. doi:10.1142/S0218843001000412.
[53] Bhattacharya K, Gerede C, Hull R, Liu R, Su J. Towards Formal Analysis of Artifact-Centric Business Process Models. In: Alonso G, Dadam P, Rosemann M (eds.), International Conference on Business Process Management (BPM 2007), volume 4714 ofLecture Notes in Computer Science. Springer-Verlag, Berlin, 2007 pp. 288-304. doi:10.1007/978-3-540-75183-0 21.
[54] Cohn D, Hull R. Business Artifacts: A Data-centric Approach to Modeling Business Operations and Processes.IEEE Data Engineering Bulletin, 2009.32(3):3-9. doi:10.1.1.183.76.
[55] Lohmann N. Compliance by Design for Artifact-Centric Business Processes. In: Rinderle S, Toumani F, Wolf K (eds.), Business Process Management (BPM 2011), volume 6896 ofLecture Notes in Computer Science. Springer-Verlag, Berlin, 2011 pp. 99-115. doi:10.1016/j.is.2012.07.003.
[56] Nigam A, Caswell N. Business artifacts: An Approach to Operational Specification.IBM Systems Journal, 2003.42(3):428-445. doi:10.1147/sj.423.0428.
[57] Fahland D. Describing Behavior of Processes with Many-to-Many Interactions. In: Donatelli S, Haar S (eds.), Applications and Theory of Petri Nets 2019, volume 11522 ofLecture Notes in Computer Science. Springer-Verlag, Berlin, 2019 pp. 3-24. doi:10.1007/978-3-030-21571-2 1.
[58] de Murillas EGL, Reijers H, van der Aalst WMP. Connecting Databases with Process Mining: A Meta Model and Toolset. In: Schmidt R, Guedria W, Bider I, Guerreiro S (eds.), Enterprise, Business-Process and Information Systems Modeling (BPMDS 2015), volume 248 ofLecture Notes in Business Information Processing. Springer-Verlag, Berlin, 2016 pp. 231-249. doi:10.1007/s10270-018-0664-7.
[59] Li G, de Murillas EGL, de Carvalho RM, van der Aalst WMP. Extracting Object-Centric Event Logs to Support Process Mining on Databases. In: Mendling J, Mouratidis H (eds.), Information Systems in the Big Data Era, CAiSE Forum 2018, volume 317 ofLecture Notes in Business Information Processing. Springer-Verlag, Berlin, 2018 pp. 182-199. doi:10.1007/978-3-319-92901-9 16.
[60] van der Aalst WMP, Artale A, Montali M, Tritini S.Object-Centric Behavioral Constraints: Integrating Data and Declarative Process Modelling.In: Proceedings of the 30th International Workshop on Description Logics (DL 2017), volume 1879 ofCEUR Workshop Proceedings. 2017 URL: http://ceur-ws.org/Vol-1879/paper51.pdf.
[61] van der Aalst WMP, Li G, Montali M.Object-Centric Behavioral Constraints.CoRR, 2017. abs/1703.05740. URL:http://arxiv.org/abs/1703.05740.
[62] Artale A, Calvanese D, Montali M, van der Aalst WMP. Enriching Data Models with Behavioral Constraints. In: Borgo S (ed.), Ontology Makes Sense (Essays in honor of Nicola Guarino). IOS Press, 2019 pp. 257-277. doi:10.3233/978-1-61499-955-3-257.
[63] van der Aalst WMP, Pesic M, Schonenberg H.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.