Data Quality Assessment for Process-Oriented Data

Provides a variety of methods to identify data quality issues in process-oriented data, which are useful to verify data quality in a process mining context. Builds on the class for activity logs implemented in the package 'bupaR'. Methods to identify data quality issues either consider each activity log entry independently (e.g. missing values, activity duration outliers,...), or focus on the relation amongst several activity log entries (e.g. batch registrations, violations of the expected activity order,...).


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Reference manual

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install.packages("daqapo")

0.3.0 by Niels Martin, 4 months ago


https://github.com/nielsmartin


Report a bug at https://github.com/nielsmartin/daqapo/issues


Browse source code at https://github.com/cran/daqapo


Authors: Niels Martin [aut, cre] , Greg Van Houdt [ctb] , Gert Janssenswillen [ctb]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports dplyr, lubridate, stringdist, stringr, tidyr, xesreadR, rlang, bupaR, readr, edeaR, magrittr, purrr, glue, miniUI, shiny

Suggests knitr, rmarkdown


See at CRAN