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 |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=daqapo
to link to this page.