Unearthing the Real Process Behind the Event Data

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The Case for Increased Process Realism, Lecture Notes in Business Information Processing 412

ISBN: 3030707326
ISBN 13: 9783030707323
Autor: Janssenswillen, Gert
Verlag: Springer Verlag GmbH
Umfang: xvi, 283 S., 39 s/w Illustr., 58 farbige Illustr., 283 p. 97 illus., 58 illus. in color.
Erscheinungsdatum: 08.04.2021
Auflage: 1/2021
Produktform: Kartoniert
Einband: Kartoniert

This book is a revised version of the PhD dissertation written by the author at Hasselt University in Belgium.This dissertation introduces the concept of process realism. Process realism is approached from two perspectives in this dissertation. First, quality dimensions and measures for process discovery are analyzed on a large scale and compared with each other on the basis of empirical experiments. It is shown that there are important differences between the different quality measures in terms of feasibility, validity and sensitivity. Moreover, the role and meaning of the generalization dimension is unclear. Second, process realism is also tackled from a data point of view. By developing a transparent and extensible tool-set, a framework is offered to analyze process data from different perspectives. From both perspectives, recommendations are made for future research, and a call is made to give the process realism mindset a central place within process mining analyses. In 2020, the PhD dissertation won the „BPM Dissertation Award“, granted to outstanding PhD theses in the field of Business Process Management.

Artikelnummer: 760734 Kategorie:

Beschreibung

This book is a revised version of the PhD dissertation written by the author at Hasselt University in Belgium. This dissertation introduces the concept of process realism. Process realism is approached from two perspectives in this dissertation. First, quality dimensions and measures for process discovery are analyzed on a large scale and compared with each other on the basis of empirical experiments. It is shown that there are important differences between the different quality measures in terms of feasibility, validity and sensitivity. Moreover, the role and meaning of the generalization dimension is unclear. Second, process realism is also tackled from a data point of view. By developing a transparent and extensible tool-set, a framework is offered to analyze process data from different perspectives. From both perspectives, recommendations are made for future research, and a call is made to give the process realism mindset a central place within process mining analyses. In 2020, the PhD dissertation won the BPM Dissertation Award, granted to outstanding PhD theses in the field of Business Process Management.

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E-Mail: juergen.hartmann@springer.com

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