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: 0.3.0
Depends: R (≥ 3.5.0)
Imports: dplyr, lubridate, stringdist, stringr, tidyr, xesreadR, rlang, bupaR, readr, edeaR, magrittr, purrr, glue, miniUI, shiny
Suggests: knitr, rmarkdown
Published: 2020-04-08
Author: Niels Martin [aut, cre], Greg Van Houdt [ctb], Gert Janssenswillen [ctb]
Maintainer: Niels Martin <niels.martin at uhasselt.be>
BugReports: https://github.com/nielsmartin/daqapo/issues
License: MIT + file LICENSE
URL: https://github.com/nielsmartin
NeedsCompilation: no
Materials: README
CRAN checks: daqapo results


Reference manual: daqapo.pdf
Vignettes: Introduction to DaQAPO
Package source: daqapo_0.3.0.tar.gz
Windows binaries: r-prerelease: daqapo_0.3.0.zip, r-release: daqapo_0.3.0.zip, r-oldrel: daqapo_0.3.0.zip
macOS binaries: r-prerelease: daqapo_0.3.0.tgz, r-release: daqapo_0.3.0.tgz, r-oldrel: not available


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