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2021 | Book

Process Realism Read chapter Read first chapter

Unearthing the Real Process Behind the Event Data

The Case for Increased Process Realism

Author: Dr. Gert Janssenswillen

Publisher: Springer International Publishing

Book Series : Lecture Notes in Business Information Processing

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

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.

Table of Contents

Frontmatter

Introduction

Frontmatter
Chapter 1. Process Realism
Abstract
In current times, organisations possess a tremendous amount of data concerning their customers, products and processes.
Gert Janssenswillen

Process Model Quality

Frontmatter
Chapter 2. Introduction to Conformance Checking
Abstract
In this chapter, a further introduction to the domain of process mining and some essential notations are provided in Sect. 2.1.
Gert Janssenswillen
Chapter 3. Calculating the Number of Distinct Paths in a Block-Structured Model
Abstract
When formalising the quality dimensions in the previous chapter, we already slightly touched upon the difficulties that exist in quantifying process behaviour.
Gert Janssenswillen
Chapter 4. Comparative Study of Quality Measures
Abstract
In Chap. 2, an overview was presented of all implemented quality measures for fitness, precision and generalization. Although the existing measures have been used to compare the performance of process discovery algorithms [43], little research has been done concerning the evaluation and comparison of the measures itself. Until now, it is unclear what the differences are between measures within the same dimension: do they judge discovered process models in a similar way, or do they qualify models differently? Are some measures more optimistic or pessimistic than others? Furthermore, there is ongoing debate about the precise definition of certain dimensions, and the relationships between the dimensions.
Gert Janssenswillen
Chapter 5. Reassessing the Quality Framework
Abstract
The results of process discovery and consecutive analyses are often directly based on a sample of event data that may not have captured all possible/actual behaviour correctly or completely.
Gert Janssenswillen
Chapter 6. Towards Mature Conformance Checking
Abstract
A summary of the results of the previous chapters is shown in Table 6.1. In the subsequent Sections, the results will be described in more detail for each dimensions, and recommendations on the usage and future development of measures will be given.
Gert Janssenswillen

Process Analytics

Frontmatter
Chapter 7. Reproducible Process Analytics
Abstract
Part II examined ways to increase process realism through conformance checking. As a result, the focus has so far been mainly on process models, and how to measure their quality. In this part, we will shift focus towards the process data itself. Indeed, as a process is more than control-flow alone, progressing towards a realistic understanding of a process requires more instruments than process models and quality measures alone.
Gert Janssenswillen
Chapter 8. Student Trajectories in Higher Education
Abstract
In this chapter, we evaluate the use of bupaR in the context of education.
Gert Janssenswillen
Chapter 9. Process-Oriented Analytics in Railway Systems
Abstract
Improving the punctuality of railway operations is one of the most important objectives of rail infrastructure managers.
Gert Janssenswillen

Conclusions

Frontmatter
Chapter 10. Conclusions and Recommendations for Future Research
Abstract
At the start of this thesis, we set out on a quest for process realism: viewing and representing processes as they really are, as distinguished from the speculative.
Gert Janssenswillen
Backmatter
Metadata
Title
Unearthing the Real Process Behind the Event Data
Author
Dr. Gert Janssenswillen
Copyright Year
2021
Electronic ISBN
978-3-030-70733-0
Print ISBN
978-3-030-70732-3
DOI
https://doi.org/10.1007/978-3-030-70733-0