Measuring the precision of multi-perspective process models

Felix Mannhardt; Massimiliano De Leoni; Hajo A. Reijers; Wil M P Van Der Aalst

doi:10.1007/978-3-319-42887-1_10

Measuring the precision of multi-perspective process models

Felix Mannhardt^*
, Massimiliano De Leoni
, Hajo A. Reijers
, Wil M P Van Der Aalst

^*Corresponding author for this work

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

Abstract

Process models need to reflect the real behavior of an organization’s processes to be beneficial for several use cases, such as process analysis, process documentation and process improvement. One quality criterion for a process model is that they should precise and not express more behavior than what is observed in logging data. Existing precision measures for process models purely focus on the control-flow dimension of a process model, thereby ignoring other perspectives, such as the data objects manipulated by the process, the resources executing process activities, and time-related aspects (e.g., activity deadlines). Focusing on the control-flow only, the results may be misleading. This paper extends existing precision measures to incorporate the other perspectives and, through an evaluation with a real-life process and corresponding logging data, demonstrates how the new measure matches our intuitive understanding of precision.

Original language	English
Title of host publication	Business Process Management Workshops - 13th International Workshops, BPM 2015, Revised Papers
Publisher	Springer - Verlag
Pages	113-125
Number of pages	13
Volume	256
ISBN (Print)	9783319428864
DOIs	https://doi.org/10.1007/978-3-319-42887-1_10
Publication status	Published - 2016
Event	13th International Workshops on Business Process Management Workshops, BPM 2015 - Innsbruck, Austria Duration: 31 Aug 2015 → 3 Sept 2015

Publication series

Name	Lecture Notes in Business Information Processing
Volume	256
ISSN (Print)	18651348

Conference

Conference	13th International Workshops on Business Process Management Workshops, BPM 2015
Country/Territory	Austria
City	Innsbruck
Period	31/08/15 → 3/09/15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 12 Responsible Consumption and Production

Keywords

Multi-perspective process mining
Precision
Process mining
Process model quality

Access to Document

10.1007/978-3-319-42887-1_10

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Cite this

Mannhardt, F., De Leoni, M., Reijers, H. A., & Van Der Aalst, W. M. P. (2016). Measuring the precision of multi-perspective process models. In Business Process Management Workshops - 13th International Workshops, BPM 2015, Revised Papers (Vol. 256, pp. 113-125). (Lecture Notes in Business Information Processing; Vol. 256). Springer - Verlag. https://doi.org/10.1007/978-3-319-42887-1_10

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title = "Measuring the precision of multi-perspective process models",

abstract = "Process models need to reflect the real behavior of an organization{\textquoteright}s processes to be beneficial for several use cases, such as process analysis, process documentation and process improvement. One quality criterion for a process model is that they should precise and not express more behavior than what is observed in logging data. Existing precision measures for process models purely focus on the control-flow dimension of a process model, thereby ignoring other perspectives, such as the data objects manipulated by the process, the resources executing process activities, and time-related aspects (e.g., activity deadlines). Focusing on the control-flow only, the results may be misleading. This paper extends existing precision measures to incorporate the other perspectives and, through an evaluation with a real-life process and corresponding logging data, demonstrates how the new measure matches our intuitive understanding of precision.",

keywords = "Multi-perspective process mining, Precision, Process mining, Process model quality",

author = "Felix Mannhardt and \{De Leoni\}, Massimiliano and Reijers, \{Hajo A.\} and \{Van Der Aalst\}, \{Wil M P\}",

year = "2016",

doi = "10.1007/978-3-319-42887-1\_10",

language = "English",

isbn = "9783319428864",

volume = "256",

series = "Lecture Notes in Business Information Processing",

publisher = "Springer - Verlag",

pages = "113--125",

booktitle = "Business Process Management Workshops - 13th International Workshops, BPM 2015, Revised Papers",

note = "13th International Workshops on Business Process Management Workshops, BPM 2015 ; Conference date: 31-08-2015 Through 03-09-2015",

}

Mannhardt, F, De Leoni, M, Reijers, HA & Van Der Aalst, WMP 2016, Measuring the precision of multi-perspective process models. in Business Process Management Workshops - 13th International Workshops, BPM 2015, Revised Papers. vol. 256, Lecture Notes in Business Information Processing, vol. 256, Springer - Verlag, pp. 113-125, 13th International Workshops on Business Process Management Workshops, BPM 2015, Innsbruck, Austria, 31/08/15. https://doi.org/10.1007/978-3-319-42887-1_10

Measuring the precision of multi-perspective process models. / Mannhardt, Felix; De Leoni, Massimiliano; Reijers, Hajo A. et al.
Business Process Management Workshops - 13th International Workshops, BPM 2015, Revised Papers. Vol. 256 Springer - Verlag, 2016. p. 113-125 (Lecture Notes in Business Information Processing; Vol. 256).

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

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T1 - Measuring the precision of multi-perspective process models

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AU - De Leoni, Massimiliano

AU - Reijers, Hajo A.

AU - Van Der Aalst, Wil M P

PY - 2016

Y1 - 2016

N2 - Process models need to reflect the real behavior of an organization’s processes to be beneficial for several use cases, such as process analysis, process documentation and process improvement. One quality criterion for a process model is that they should precise and not express more behavior than what is observed in logging data. Existing precision measures for process models purely focus on the control-flow dimension of a process model, thereby ignoring other perspectives, such as the data objects manipulated by the process, the resources executing process activities, and time-related aspects (e.g., activity deadlines). Focusing on the control-flow only, the results may be misleading. This paper extends existing precision measures to incorporate the other perspectives and, through an evaluation with a real-life process and corresponding logging data, demonstrates how the new measure matches our intuitive understanding of precision.

AB - Process models need to reflect the real behavior of an organization’s processes to be beneficial for several use cases, such as process analysis, process documentation and process improvement. One quality criterion for a process model is that they should precise and not express more behavior than what is observed in logging data. Existing precision measures for process models purely focus on the control-flow dimension of a process model, thereby ignoring other perspectives, such as the data objects manipulated by the process, the resources executing process activities, and time-related aspects (e.g., activity deadlines). Focusing on the control-flow only, the results may be misleading. This paper extends existing precision measures to incorporate the other perspectives and, through an evaluation with a real-life process and corresponding logging data, demonstrates how the new measure matches our intuitive understanding of precision.

KW - Multi-perspective process mining

KW - Precision

KW - Process mining

KW - Process model quality

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Measuring the precision of multi-perspective process models

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Persistent URL (handle)

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