Data Quality Assessment for Process-Oriented Data
daqapo - Data Quality Assessment for Process-oriented Data
Check activity frequencies
Detect activity order violations
Detect dependency violations between attributes
Detect gaps in case_id
Detect conditional activity presence violations
Detect activity duration outliers
Detect inactive periods
Detect incomplete cases
Detect incorrect activity names
Detect missing values
Detect multi-registration
Detect overlapping acitivity instances
Detect missing related activities
Search for similar labels in a column
Detect time anomalies
Search for unique values / distinct combinations
Detect value range violations
Define allowable range of values
Define allowable range of values
Define allowable time range
Define bounds for activity duration
Filter anomalies from the activity log
Fix problems
Objects exported from other packages
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,...).