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Title: | bupaR: Enabling reproducible business process analysis | Authors: | JANSSENSWILLEN, Gert DEPAIRE, Benoit SWENNEN, Marijke JANS, Mieke VANHOOF, Koen |
Issue Date: | 2018 | Source: | Knowledge-based systems, 163, p. 927-930 | 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. | Notes: | Janssenswillen, G (reprint author), UHasselt Hasselt Univ, Fac Business Econ, Martelarenlaan 42, B-3500 Hasselt, Belgium. gert.janssenswillen@uhasselt.be | Keywords: | Event data; Process analysis; R; bupaR; edeaR; eventdataR; processmapR; processmonitR; xesreadR | Document URI: | http://hdl.handle.net/1942/27485 | ISSN: | 0950-7051 | e-ISSN: | 1872-7409 | DOI: | 10.1016/j.knosys.2018.10.018 | ISI #: | 000454468200073 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2020 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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bupar_submission_osp_knowledge_based_systems_revised_2.pdf | Non Peer-reviewed author version | 734.31 kB | Adobe PDF | View/Open |
1-s2.0-S0950705118305045-main.pdf Restricted Access | Published version | 614.68 kB | Adobe PDF | View/Open Request a copy |
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