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,...).
Version: 0.3.2 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 Published: 2022-07-14 DOI: 10.32614/CRAN.package.daqapo Author: Niels Martin [aut, cre], Greg Van Houdt [ctb], Gert Janssenswillen [ctb] Maintainer: Niels Martin <niels.martin at uhasselt.be> BugReports: https://github.com/bupaverse/daqapo/issues/ License: MIT + file LICENSE URL: https://github.com/bupaverse/daqapo/ NeedsCompilation: no Materials: README In views: MissingData CRAN checks: daqapo results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=daqapo to link to this page.
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