Unearthing the Real Process Behind the Event Data

Part I Introduction.- 1 Process Realism.- 1.1 Introduction to Process Mining.- 1.1.1 Business Process Management.- 1.1.2 The emergence of process mining.- 1.1.3 Perspectives.- 1.1.4 Tools.- 1.1.5 Towards Evidence-based Business Process Management.- 1.2 The case for Process Realism.- 1.2.1 Motivation.- 1.2.2 Research objective.- 1.3 Methodology and Outline.- 1.3.1 Process Model Quality.- 1.3.2 Process Analytics.- Part II Process Model Quality.- 2 Introduction to Conformance Checking.- 2.1 Introduction to Process Mining.- 2.1.1 Preliminaries.- 2.1.2 Process.- 2.1.3 Event log.- 2.1.4 Model.- 2.2 Quality Dimensions.- 2.2.1 Fitness.- 2.2.2 Precision.- 2.2.3 Generalization.- 2.2.4 Simplicity.- 2.3 Quality Measures.- 2.3.1 Fitness.- 2.3.2 Precision.- 2.3.3 Generalization.- 2.4 Conclusion.- 2.5 Further Reading.- 3 Calculating the Number of Distinct Paths in a Block-Structured Model.- 3.1 Introduction.- 3.2 Formal Algorithm.- 3.2.1 Assumptions and used notations.- 3.2.2 Generic approach.- 3.2.3Block Functions.- 3.2.4 Limitations.- 3.3 Implementation.- 3.3.1 Preliminaries.- 3.3.2 Algorithm.- 3.3.3 Extended Block Functions.- 3.3.4 Silent transitions and duplicate tasks.- 3.4 Performance.- 3.5 Conclusion and future work.- 3.6 Further Reading.- 4 Comparative Study of Quality Measures.- 4.1 Introduction.- 4.2 Problem Statement.- 4.3 Methodology.- 4.3.1 Generate systems.- 4.3.2 Calculate the number of paths.- 4.3.3 Simulate logs.- 4.3.4 Discover models.- 4.3.5 Measure quality.- 4.3.6 Statistical Analysis.- 4.4 Results.- 4.4.1 Feasibility.-4.4.2 Validity.- 4.4.3 Sensitivity.- 4.5 Discussion.- 4.6 Conclusion.- 4.7 Further Reading.- 5 Reassessing the Quality Framework.- 5.1 Introduction.- 5.2 Exploratory versus confirmatory process discovery.- 5.2.1 Problem statement.- 5.3 Methodology.- 5.3.1 Generate systems.- 5.3.2 Simulate logs.- 5.3.3 Discover models.- 5.3.4 Measure log-quality.- 5.3.5 Measure system-quality.- 5.3.6 Statistical analysis.- 5.4 Results.- 5.4.1 Log versus system-perspective.- 5.4.2 Generalization.- 5.5 Discussion.- 5.6 Conclusion.- 5.7 Further Reading.- 6 Towards Mature Conformance Checking.- 6.1 Synthesis.- 6.1.1 Fitness.- 6.1.2 Precision.- 6.1.3 Generalization.- 6.2 Future research.- 6.2.1 System-fitness and system-precision.- 6.2.2 Improving the Experimental Setup.- Part III Process Analytics.- 7 Reproducible Process Analytics.- 7.1 Introduction.- 7.2 Problem Statement.- 7.3 Requirements Definition.- 7.3.1 Functionality requirements.- 7.3.2 Design Requirements.- 7.4 Design and Development of Artefact.- 7.4.1 Core packages.- 7.4.2 Supplementary packages.- 7.5 Demonstration of Artefact.- 7.5.1 Event data extraction.- 7.5.2 Data Processing.- 7.5.3 Mining and Analysis.- 7.6 Discussion.- 7.7 Conclusion.- 7.8 Further Reading.- 8 Student Trajectories in Higher Education.- 8.1 Learning analytics and process mining.- 8.2 Data Understanding.- 8.3 Followed versus prescribed trajectories.- 8.3.1 Root causes.- 8.3.2 Impact.- 8.4 Failure Patterns.- 8.4.1 Bags.- 8.4.2 High-level analysis.- 8.4.3 Low-level analysis.- 8.5 Understanding Trajectory Decisions.- 8.6 Discussion.- 8.7 Conclusion.- 8.8 Further Reading.- 9 Process-Oriented Analytics in Railway Systems.- 9.1 Introduction.- 9.2 Problem statement and related work.- 9.3 Methodology.- 9.3.1 Rerouting severity.- 9.3.2 Rerouting diversity.- 9.3.3 Discovering patterns.- 9.4 Results.- 9.4.1 Rerouting severity.- 9.4.2 Rerouting diversity.- 5 Discussion.- 9.6 Conclusions.- 9.7 Further Reading.- Part IV Conclusions.- 10 Conclusions and Recommendations for Future Research.- 10.1 Process Model Quality.- 10.1.1 Lessons Learned.- 10.1.2 Recommendations for Future Research.- 10.2 Process Analytics.- 10.2.1 Lessons Learned.- 10.2.2 Recommendations for Future Research.- Afterword.- A Additional Figures and Tables Chapter 4.- B Function Index bupaR packages.- B.1 bupaR.- B.2 edeaR.- B.3 evendataR.- B.4 xesreadR.- B.5 processmapR.- B.6 processmonitR.- B.7 petrinetR.- B.8 ptR.- B.9 discoveR.- CScripts Chapter 8.- D Scripts Chapter 9.- References.