Discovering, analyzing and enhancing BPMN models using ProM

A.A. Kalenkova; M. Leoni, de; W.M.P. Aalst, van der

Discovering, analyzing and enhancing BPMN models using ProM

A.A. Kalenkova
, M. Leoni, de
, W.M.P. Aalst, van der

Process Analytics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

20 Citations (Scopus)

211 Downloads (Pure)

Abstract

Process mining techniques relate observed behavior to modeled behavior, e.g., the automatic discovery of a process model based on an event log. Process mining is not limited to process discovery and also includes conformance checking and model enhancement. Conformance checking techniques are used to diagnose the deviations of the observed behavior as recorded in the event log from some process model. Model enhancement allows to extend process models using additional perspectives, conformance and performance information. In recent years, BPMN (Business Process Model and Notation) 2.0 has become a de facto standard for modeling business processes in industry. This paper presents the BPMN support current in ProM. ProM is the most known and used open-source process mining framework. ProM’s functionalities of discovering, analyzing and enhancing BPMN models are discussed. Support of the BPMN 2.0 standard will help ProM users to bridge the gap between formal models (such as Petri nets, causal nets and others) and process models used by practitioners.

Original language	English
Title of host publication	BPM Demo Sessions 2014 (co-located with BPM 2014, Eindhoven, The Netherlands, September 20, 2014)
Editors	L. Limonad, B. Weber
Publisher	CEUR-WS.org
Pages	36-41
Publication status	Published - 2014
Event	12th International Conference on Business Process Management, BPM 2014 - Eindhoven, Netherlands Duration: 7 Sept 2014 → 11 Sept 2014 Conference number: 12 http://bpm2014.haifa.ac.il/evover.net_9090/bpm2014.html https://link.springer.com/book/10.1007/978-3-319-15895-2

Publication series

Name	CEUR Workshop Proceedings
Volume	1295
ISSN (Print)	1613-0073

Conference

Conference	12th International Conference on Business Process Management, BPM 2014
Abbreviated title	BPM 2014
Country/Territory	Netherlands
City	Eindhoven
Period	7/09/14 → 11/09/14
Other	Conference was originally planned in Haifa, but due to the unstable situation in southern Israel, it was relocated to Eindhoven. BPM Demo Sessions 2014, BPMD 2014, Co-located with the 12th International Conference on Business Process Management, BPM 2014
Internet address	http://bpm2014.haifa.ac.il/evover.net_9090/bpm2014.html https://link.springer.com/book/10.1007/978-3-319-15895-2

Access to Document

publishers versionFinal published version, 357 KB

Cite this

@inproceedings{c7a5fa7741dc4b93b976259ccdf17bd6,

title = "Discovering, analyzing and enhancing BPMN models using ProM",

abstract = "Process mining techniques relate observed behavior to modeled behavior, e.g., the automatic discovery of a process model based on an event log. Process mining is not limited to process discovery and also includes conformance checking and model enhancement. Conformance checking techniques are used to diagnose the deviations of the observed behavior as recorded in the event log from some process model. Model enhancement allows to extend process models using additional perspectives, conformance and performance information. In recent years, BPMN (Business Process Model and Notation) 2.0 has become a de facto standard for modeling business processes in industry. This paper presents the BPMN support current in ProM. ProM is the most known and used open-source process mining framework. ProM{\textquoteright}s functionalities of discovering, analyzing and enhancing BPMN models are discussed. Support of the BPMN 2.0 standard will help ProM users to bridge the gap between formal models (such as Petri nets, causal nets and others) and process models used by practitioners.",

author = "A.A. Kalenkova and \{Leoni, de\}, M. and \{Aalst, van der\}, W.M.P.",

year = "2014",

language = "English",

series = "CEUR Workshop Proceedings",

publisher = "CEUR-WS.org",

pages = "36--41",

editor = "L. Limonad and B. Weber",

booktitle = "BPM Demo Sessions 2014 (co-located with BPM 2014, Eindhoven, The Netherlands, September 20, 2014)",

note = "12th International Conference on Business Process Management, BPM 2014, BPM 2014 ; Conference date: 07-09-2014 Through 11-09-2014",

url = "http://bpm2014.haifa.ac.il/evover.net\_9090/bpm2014.html, https://link.springer.com/book/10.1007/978-3-319-15895-2",

}

Kalenkova, AA, Leoni, de, M & Aalst, van der, WMP 2014, Discovering, analyzing and enhancing BPMN models using ProM. in L Limonad & B Weber (eds), BPM Demo Sessions 2014 (co-located with BPM 2014, Eindhoven, The Netherlands, September 20, 2014). CEUR Workshop Proceedings, vol. 1295, CEUR-WS.org, pp. 36-41, 12th International Conference on Business Process Management, BPM 2014, Eindhoven, Netherlands, 7/09/14.

Discovering, analyzing and enhancing BPMN models using ProM. / Kalenkova, A.A.; Leoni, de, M.; Aalst, van der, W.M.P.
BPM Demo Sessions 2014 (co-located with BPM 2014, Eindhoven, The Netherlands, September 20, 2014). ed. / L. Limonad; B. Weber. CEUR-WS.org, 2014. p. 36-41 (CEUR Workshop Proceedings; Vol. 1295).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Discovering, analyzing and enhancing BPMN models using ProM

AU - Kalenkova, A.A.

AU - Leoni, de, M.

AU - Aalst, van der, W.M.P.

N1 - Conference code: 12

PY - 2014

Y1 - 2014

N2 - Process mining techniques relate observed behavior to modeled behavior, e.g., the automatic discovery of a process model based on an event log. Process mining is not limited to process discovery and also includes conformance checking and model enhancement. Conformance checking techniques are used to diagnose the deviations of the observed behavior as recorded in the event log from some process model. Model enhancement allows to extend process models using additional perspectives, conformance and performance information. In recent years, BPMN (Business Process Model and Notation) 2.0 has become a de facto standard for modeling business processes in industry. This paper presents the BPMN support current in ProM. ProM is the most known and used open-source process mining framework. ProM’s functionalities of discovering, analyzing and enhancing BPMN models are discussed. Support of the BPMN 2.0 standard will help ProM users to bridge the gap between formal models (such as Petri nets, causal nets and others) and process models used by practitioners.

AB - Process mining techniques relate observed behavior to modeled behavior, e.g., the automatic discovery of a process model based on an event log. Process mining is not limited to process discovery and also includes conformance checking and model enhancement. Conformance checking techniques are used to diagnose the deviations of the observed behavior as recorded in the event log from some process model. Model enhancement allows to extend process models using additional perspectives, conformance and performance information. In recent years, BPMN (Business Process Model and Notation) 2.0 has become a de facto standard for modeling business processes in industry. This paper presents the BPMN support current in ProM. ProM is the most known and used open-source process mining framework. ProM’s functionalities of discovering, analyzing and enhancing BPMN models are discussed. Support of the BPMN 2.0 standard will help ProM users to bridge the gap between formal models (such as Petri nets, causal nets and others) and process models used by practitioners.

M3 - Conference contribution

T3 - CEUR Workshop Proceedings

SP - 36

EP - 41

BT - BPM Demo Sessions 2014 (co-located with BPM 2014, Eindhoven, The Netherlands, September 20, 2014)

A2 - Limonad, L.

A2 - Weber, B.

PB - CEUR-WS.org

T2 - 12th International Conference on Business Process Management, BPM 2014

Y2 - 7 September 2014 through 11 September 2014

ER -

Discovering, analyzing and enhancing BPMN models using ProM

Abstract

Publication series

Conference

Access to Document

Fingerprint

Cite this