daqapo: 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,...).

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


Reference manual: daqapo.pdf
Vignettes: Introduction to DaQAPO


Package source: daqapo_0.3.2.tar.gz
Windows binaries: r-devel: daqapo_0.3.2.zip, r-release: daqapo_0.3.2.zip, r-oldrel: daqapo_0.3.2.zip
macOS binaries: r-release (arm64): daqapo_0.3.2.tgz, r-oldrel (arm64): daqapo_0.3.2.tgz, r-release (x86_64): daqapo_0.3.2.tgz, r-oldrel (x86_64): daqapo_0.3.2.tgz
Old sources: daqapo archive


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