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Artifact Lifecycle Discovery

Viara Popova

Institute of Computer Science, University of Tartu, J. Liivi 2, Tartu 50409, Estonia

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Dirk Fahland

Eindhoven University of Technology, The Netherlands

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Marlon Dumas

Institute of Computer Science, University of Tartu, J. Liivi 2, Tartu 50409, Estonia

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https://doi.org/10.1142/S021884301550001XCited by:52 (Source: Crossref)

Abstract

Artifact-centric modeling is an approach for capturing business processes in terms of so-called business artifacts — key entities driving a company's operations and whose lifecycles and interactions define an overall business process. This approach has been shown to be especially suitable in the context of processes where one-to-many or many-to-many relations exist between the entities involved in the process. As a contribution towards building up a body of methods to support artifact-centric modeling, this article presents a method for automated discovery of artifact-centric process models starting from logs consisting of flat collections of event records. We decompose the problem in such a way that a wide range of existing (non-artifact-centric) automated process discovery methods can be reused in a flexible manner. The presented methods are implemented as a package for ProM, a generic open-source framework for process mining. The methods have been applied to reverse-engineer an artifact-centric process model starting from logs of a real-life business process.

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References

D. Cohn and R. Hull, IEEE Data Eng. Bull. 32(3), 3 (2009). Google Scholar
A. Nigam and N. S. Caswell, IBM Systems Journal 42(3), 428 (2003). Crossref, Web of Science, Google Scholar
R. Hullet al., Introducing the Guard-Stage-Milestone approach for specifying business entity lifecycles, Proc. WS-FM'20106551, Lecture Notes in Computer Science (Springer, 2010) pp. 1–24. Google Scholar
R. Hullet al., Business artifacts with Guard-Stage-Milestone lifecycles: Managing artifact interactions with conditions and events, DEBS 2011 (ACM, 2011) pp. 51–62. Google Scholar
K. R. Dittrich, S. Gatziu and A. Geppert, Rules in Database Systems, Lecture Notes in Computer Science 985 (Springer, 1995) pp. 3–20. Google Scholar
W. M. P. van der Aalst , Process Mining — Discovery, Conformance and Enhancement of Business Processes ( Springer , 2011 ) . Crossref, Google Scholar
D. Fahland, M. de Leoni, B. F. van Dongen and W. M. P. van der Aalst, Many-to-many: Some observations on interactions in artifact choreographies, in Proc. ZEUS'2011. Volume 705 of CEUR Workshop Proceedings, CEUR-WS.org (2011), pp. 9–15 . Google Scholar
V. Popova and M. Dumas , From Petri nets to Guard-Stage-Milestone models , Proc. of the BPM'2012 Workshops 132 , Lecture Notes in Business Information Processing ( Springer , 2013 ) . Google Scholar
T. Murata, Proc. IEEE 77(4), 541 (1989). Crossref, Web of Science, Google Scholar
W. van der Aalstet al., Int. J. Cooperative Inf. Syst. 10(4), 443 (2001). Link, Web of Science, Google Scholar
A. Silberschatz, H. F. Korth and S. Sudarshan, Database System Concepts, 4th edn. (McGraw-Hill Book Company, 2001). Google Scholar
Y. Huhtalaet al., Comput. J. 42(2), 100 (1999). Crossref, Web of Science, Google Scholar
J. Bauckmannet al., Efficiently detecting inclusion dependencies, Proc. ICDE'2007 (IEEE, 2007) pp. 1448–1450. Google Scholar
J. Bauckmann, U. Leser and F. Naumann, Efficient and exact computation of inclusion dependencies for data integration. Technical Report 34, Hasso-Plattner-Institute for Software Systems at University of Potsdam (2010) . Google Scholar
P. Feldman and D. Miller, The Comput. J. 29(4), 348 (1986). Crossref, Web of Science, Google Scholar
T. Cormen et al. , Introduction to Algorithms , 3rd edn. ( The MIT Press , 2009 ) . Google Scholar
J. M. E. M. van der Werfet al., Fundam. Inform. 94(4), 387 (2009). Crossref, Web of Science, Google Scholar
W. M. P. van der Aalst, T. Weijters and L. Maruster, IEEE Trans. Knowl. Data Eng. 16(9), 1128 (2004). Crossref, Web of Science, Google Scholar
W. M. P. van der Aalst, A. K. A. de Medeiros and A. J. M. M. Weijters, Genetic process mining, Proc ICATPN 20053536, Lecture Notes in Computer Science (2005) pp. 48–69. Google Scholar
J. C. A. M. Buijs, B. F. van Dongen and W. M. P. van der Aalst, A genetic algorithm for discovering process trees, IEEE Congress on Evolutionary Computation (IEEE, 2012) pp. 1–8. Google Scholar
S. J. J. Leemans, D. Fahland and W. M. P. van der Aalst, Discovering block-structured process models from event logs — A constructive approach, in Petri Nets, Volume 7927 of Lecture Notes in Computer Science (Springer, 2013), pp. 311–329 . Google Scholar
A. K. A. de Medeiros, A. J. M. M. Weijters and W. M. P. van der Aalst, Data Min. Knowl. Discov. 14(2), 245 (2007). Crossref, Web of Science, Google Scholar
A. J. M. M. Weijters and W. M. P. van der Aalst, Integr. Comput.-Aided Eng. 10(2), 151 (2003). Crossref, Web of Science, Google Scholar
A. J. M. M. Weijters and J. T. S. Ribeiro, Flexible Heuristics Miner (FHM), Proc. IEEE CIDM 2011 (2011) pp. 310–317. Google Scholar
B. F. van Dongen and A. Adriansyah, Process mining: Fuzzy clustering and performance visualization, Proc. Business Process Management Workshops 200943, Lecture Notes in Business Information Processing (Springer, 2009) pp. 158–169. Google Scholar
R. P. J. C. Bose, H. M. W. E. Verbeek and W. M. P. van der Aalst, Discovering hierarchical process models using ProM, in CAiSE Forum (Selected Papers), Volume 107 of Lecture Notes in Business Information Processing (Springer, 2011), pp. 33–48 . Google Scholar
J. D. Weerdtet al., Inf. Syst. 37(7), 654 (2012). Crossref, Web of Science, Google Scholar
A. Rozinat and W. M. P. van der Aalst, Inf. Syst. 33(1), 64 (2008). Crossref, Web of Science, Google Scholar
D. Fahland and W. M. P. van der Aalst, Repairing process models to reflect reality, Proc. BPM 20127481, Lecture Notes in Computer Science (Springer, 2012) pp. 229–245. Google Scholar
D. Fahland and W. M. P. van der Aalst, Inf. Syst. 38(4), 585 (2013). Crossref, Web of Science, Google Scholar
C. Ouyanget al., Translating standard process models to BPEL, Proc. CAiSE'20064001, Lecture Notes in Computer Science (2006) pp. 417–432. Google Scholar
A. Rozinat and W. M. P. van der Aalst, Decision mining in ProM, Proc. BPM'20064102, Lecture Notes in Computer Science (Springer, 2006) pp. 420–425. Google Scholar
J. C. A. M. Buijs, B. F. van Dongen and W. M. P. van der Aalst, On the role of fitness, precision, generalization and simplicity in process discovery, OTM Conf. (1)7565, Lecture Notes in Computer Science (Springer, 2012) pp. 305–322. Google Scholar
A. Weijters, W. van der Aalst and A. Alves de Medeiros, Process mining with the Heuristics Miner algorithm, Technical Report WP 166 (BETA Working Paper Series), Eindhoven University of Technology (2006) . Google Scholar
S. J. Leemans, D. Fahland and W. M. van der Aalst, Discovering block-structured process models from non-conforming event logs, in Proc. of the BPM'2013 Workshops (Springer, 2013), to appear . Google Scholar
H. M. W. Verbeek, J. C. A. M. Buijs, B. F. van Dongen and W. M. P. van der Aalst, XES, XESame, and ProM 6, in CAiSE Forum, Volume 72 of Lecture Notes in Business Information Processing (Springer, 2010), pp. 60–75 . Google Scholar
C. Rodríguez, R. Engel, G. Kostoska, F. Daniel, F. Casati and M. Aimar, Eventifier: Extracting process execution logs from operational databases, in BPM (Demos), Volume 940 of CEUR Workshop Proceedings, CEUR-WS.org (2012), pp. 17–22 . Google Scholar
E. H. J. Nooijen, B. F. van Dongen and D. Fahland, Automatic discovery of data-centric and artifact-centric processes, Business Process Management Workshops132, Lecture Notes in Business Information Processing (Springer, 2012) pp. 316–327. Google Scholar
V. Popova, M. De Leoni, M. Dumas, D. Fahland, L. García-Bañuelos, B. van Dongen, D. Boaz, D. Lembo and M. Montali, Full artifact discovery, Deliverable D3.4, ACSI Project (2013) . Google Scholar
V. Popova and M. Dumas, Discovering unbounded synchronization conditions in artifact-centric process models, in Proc. of the BPM'2013 Workshops, Workshop on Business Process Intelligence, Lecture Notes in Business Information Processing (Springer, 2014), pp. 28–40 . Google Scholar
R. Johnson, D. Pearson and K. Pingali, The program structure tree: Computing control regions in linear time, Proc. ACM SIGPLAN 1994 Conf. Programming Language Design and Implementation. PLDI '94 (ACM, New York, NY, USA, 1994) pp. 171–185. Google Scholar