Data Quality Assessment for Process-Oriented Data R package daqapo version 0.3.2 CRAN Task View: MissingData (https://CRAN.R-project.org/view=MissingData) 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,...). Software Depends: R (>= 3.5.0) Imports: dplyr, lubridate, stringdist, stringr, tidyr, xesreadR, rlang, bupaR (>= 0.5.0), readr, edeaR, magrittr, purrr, glue, miniUI, shiny, tibble Suggests: knitr, rmarkdown Niels Martin <niels.martin@uhasselt.be> Comprehensive R Archive Network (CRAN) Niels Martin [aut, cre], Greg Van Houdt [ctb], Gert Janssenswillen [ctb] MIT + file LICENSE (https://CRAN.R-project.org/package=daqapo/LICENSE) 2022-07-14 application/tgz https://CRAN.R-project.org/package=daqapo doi:10.32614/CRAN.package.daqapo