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bupaR: Enabling reproducible business process analysis

Published on Jan 1, 2019in Knowledge Based Systems5.101
· DOI :10.1016/j.knosys.2018.10.018
Gert Janssenswillen5
Estimated H-index: 5
(University of Hasselt),
Benoît Depaire10
Estimated H-index: 10
(University of Hasselt)
+ 2 AuthorsKoen Vanhoof27
Estimated H-index: 27
(University of Hasselt)
Sources
Abstract
Abstract Over the last decades, the field of process mining has emerged as a response to a growing amount of event data being recorded in the context of business processes. Concurrently with the increasing amount of literature produced in this field, a set of tools has been developed to implement the various algorithms and provide them to end users. However, the majority of tools does not provide the possibility of creating workflows which can be reused at a later point in time to reproduce the results, and most tools are not easily customizable. This paper introduces bupaR, an integrated collection of R-packages which creates a framework for reproducible process analysis in R and supports different steps of a process analysis project, from data extraction to data analysis. It is an extensible framework of several R-packages to analyze process data, each with their specific purpose and set of tools.
  • References (17)
  • Citations (2)
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References17
Newest
#1Darko Etinger (Juraj Dobrila University of Pula)H-Index: 2
#2Tihomir Orehovački (Juraj Dobrila University of Pula)H-Index: 10
Last. Snježana Babić (Polytechnic of Rijeka)H-Index: 4
view all 3 authors...
Based on the event logs gathered from the learning management system in use at the Juraj Dobrila University of Pula, this study attempts to discover frequent behavioural patterns in event logs. The process mining tool Fluxicon Disco was used to create, clean and prepare the event log. The discovered process model represents the starting point for the assessment of the usage behaviour of the Moodle LMS. A procedure was developed in R (R-project) to analyse the process model by using various R bas...
1 CitationsSource
#1Ingo Weber (UNSW: University of New South Wales)H-Index: 23
#2Xiwei Xu (UNSW: University of New South Wales)H-Index: 14
Last. Jan Mendling (WU: Vienna University of Economics and Business)H-Index: 56
view all 6 authors...
The integration of business processes across organizations is typically beneficial for all involved parties. However, the lack of trust is often a roadblock. Blockchain is an emerging technology for decentralized and transactional data sharing across a network of untrusted participants. It can be used to find agreement about the shared state of collaborating parties without trusting a central authority or any particular participant. Some blockchain networks also provide a computational infrastru...
121 CitationsSource
#1Marijke SwennenH-Index: 3
Last. Koen Vanhoof (University of Hasselt)H-Index: 27
view all 5 authors...
Currently, process mining literature is primarily focused on the discovery of comprehensible process models that best capture the underlying behavior in event logs. Consequently, the resulting models a) aggregate information, based on algorithm-specific assumptions, and b) transform information into a simplified representation. Both characteristics, which are valuable in certain, different contexts, suffer from the inability to describe objectively the behavior that is inherent to the event log ...
5 Citations
Jun 16, 2014 in CAiSE (Conference on Advanced Information Systems Engineering)
#1Francesco Folino (National Research Council)H-Index: 12
#2Massimo Guarascio (National Research Council)H-Index: 6
Last. Luigi Pontieri (National Research Council)H-Index: 15
view all 3 authors...
Process Mining techniques have been gaining attention, especially as concerns the discovery of predictive process models. Traditionally focused on workflows, they usually assume that process tasks are clearly specified, and referred to in the logs. This limits however their application to many real-life BPM environments (e.g. issue tracking systems) where the traced events do not match any predefined task, but yet keep lots of context data. In order to make the usage of predictive process mining...
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Sep 9, 2013 in CoopIS (Cooperative Information Systems)
#1Fabrizio Maria Maggi (UT: University of Tartu)H-Index: 28
#2Andrea Burattin (UNIPD: University of Padua)H-Index: 13
Last. Alessandro Sperduti (UNIPD: University of Padua)H-Index: 27
view all 4 authors...
Today’s business processes are often controlled and supported by information systems. These systems record real-time information about business processes during their executions. This enables the analysis at runtime of the process behavior. However, many modern systems produce “big data”, i.e., collections of data sets so large and complex that it becomes impossible to store and process all of them. Moreover, few processes are in steady-state and due to changing circumstances processes evolve an...
29 CitationsSource
Jun 24, 2013 in Petri Nets (Applications and Theory of Petri Nets)
#1Sander J. J. Leemans (TU/e: Eindhoven University of Technology)H-Index: 6
#2Dirk Fahland (TU/e: Eindhoven University of Technology)H-Index: 25
Last. Aalst van der Wmp (TU/e: Eindhoven University of Technology)H-Index: 116
view all 3 authors...
Process discovery is the problem of, given a log of observed behaviour, finding a process model that 'best' describes this behaviour. A large variety of process discovery algorithms has been proposed. However, no existing algorithm guarantees to return a fitting model (i.e., able to reproduce all observed behaviour) that is sound (free of deadlocks and other anomalies) in finite time. We present an extensible framework to discover from any given log a set of block-structured process models that ...
192 CitationsSource
Apr 1, 2011 in CIDM (Computational Intelligence and Data Mining)
#1A. J. M. M. Weijters (TU/e: Eindhoven University of Technology)H-Index: 23
#2Joel Ribeiro (TU/e: Eindhoven University of Technology)H-Index: 6
One of the aims of process mining is to retrieve a process model from a given event log. However, current techniques have problems when mining processes that contain nontrivial constructs, processes that are low structured and/or dealing with the presence of noise in the event logs. To overcome these problems, a new process representation language is presented in combination with an accompanying process mining algorithm. The most significant property of the new representation language is in the ...
235 CitationsSource
#1Aalst van der WmpH-Index: 116
The first to cover this missing link between data mining and process modeling, this book provides real-world techniques for monitoring and analyzing processes in real time. It is a powerful new tool destined to play a key role in business process management.
1,255 Citations
Jun 7, 2010 in CAiSE (Conference on Advanced Information Systems Engineering)
#1Hmw Eric Verbeek (TU/e: Eindhoven University of Technology)H-Index: 27
#2Jcam Joos Buijs (TU/e: Eindhoven University of Technology)H-Index: 12
Last. Aalst van der Wmp (TU/e: Eindhoven University of Technology)H-Index: 116
view all 4 authors...
Process mining has emerged as a new way to analyze business processes based on event logs. These events logs need to be extracted from operational systems and can subsequently be used to discover or check the conformance of processes. ProM is a widely used tool for process mining. In earlier versions of ProM, MXML was used as an input format. In future releases of ProM, a new logging format will be used: the eXtensible Event Stream (XES) format. This format has several advantages over MXML. The ...
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#1Werf van der Jmem (TU/e: Eindhoven University of Technology)H-Index: 6
#2Boudewijn F. van Dongen (TU/e: Eindhoven University of Technology)H-Index: 32
Last. Alexander Serebrenik (TU/e: Eindhoven University of Technology)H-Index: 32
view all 4 authors...
The research domain of process discovery aims at constructing a process model (e.g. a Petri net) which is an abstract representation of an execution log. Such a model should (1) be able to reproduce the log under consideration and (2) be independent of the number of cases in the log. In this paper, we present a process discovery algorithm where we use concepts taken from the language-based theory of regions, a well-known Petri net research area. We identify a number of shortcomings of this theor...
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