bupaR is an open-source, integrated suite of R-packages for the handling and analysis of business process data. It currently consists of 8 packages, including the central package, supporting different stages of a process mining workflow.

bupaR provides support for different stages in process analysis, such as importing event data, calculating descriptives, process monitoring and process visualization. The central package, bupaR includes basic functionality for creating event log objects in R. It contains several functions to get information about an event log and also provides specific event log versions of generic R functions.

## Packages

Package Description
bupaR The bupaR-package is the core package of the framework, implements an S3-objects class for event data. It provides functions to create these objects, as well as support for common transformations. Auxiliary functions to seamlessly change the classifiers of the event data are made available, and event log versions of common dplyr functions for data manipulation are implemented, such as filter, group_by and mutate, among others. These functions can be used to preprocess event data. Some specific preprocessing tasks are supported explicitly by specific functions, such as aggregations of activity labels.
edeaR edeaR stands for Exploratory and Descriptive Event-Data Analyses, and contains a set of process metrics to describe and explore event logs. The process metrics are based on Lean Six Sigma literature and can be analyzed and visualized at different levels of granularity. Additionally, edeaR contains an extensive collection of event data specific filters.
eventdataR eventdataR is a data-package which provide easy access to event logs for testing and experiments. Currently, both artificial event data, e.g. patients, as well as real-life event data, such as the sepsis dataset.
xesreadR In order to be compatible with teh eXtensible Event Stram IEEE standard, the xesreadR package allows to read and write .xes-files.
processmapR Process data specific visualizations, such as process maps and dotted charts, are provided by processmapR. The provided visualizations are highly customizable and can be used to give insights to different aspects of the process.
processanimateR As an extension of processmapR, processanimateR allows to easily animate process maps using token replay.
petrinetR While most package of bupaR are focused on process data, petrinetR is the first package to introduce a process model notation in R. Currently, it supports the creation of Petri Nets, as well as reading and writing .PMNL-files. Furthermore, Petri Nets can be visualized, adjusted and one can perform manual token replay and parse transition sequences.
processmonitR processmonitR provides a limited set of process dashboards. These can be used in a permanent, real-time fashion, as well as for interactive data analysis.

## Pay tribute

Janssenswillen, G., Depaire, B., Swennen, M., Jans, M., & Vanhoof, K. (2019). bupaR: Enabling reproducible business process analysis. Knowledge-Based Systems, 163, 927-930.

To cite invidual packages, use the citation function in R.

citation("processmapR")
##
## To cite package 'processmapR' in publications use:
##
##   Gert Janssenswillen (2020). processmapR: Construct Process Maps Using
##   Event Data. https://www.bupar.net,
##   https://github.com/bupaverse/processmapr.
##
## A BibTeX entry for LaTeX users is
##
##   @Manual{,
##     title = {processmapR: Construct Process Maps Using Event Data},
##     author = {Gert Janssenswillen},
##     year = {2020},
##     note = {https://www.bupar.net, https://github.com/bupaverse/processmapr},
##   }