3 papers
cs.DB2026
Implementation Guidelines for Data Quality Metrics
Philipp Jung, Katinka Becker, Felix Biessmann +4
Despite decades of data quality (DQ) research, a gap remains between DQ dimensions, such as accuracy or completeness, which the literature defines in textual form, and DQ tools, wh…
cs.LG2026
CURED: Creating, Understanding, and Repairing Errors Demonstrator
Nicholas Chandler, Sebastian Jäger, Philipp Jung +1
Detecting and cleaning errors in tabular data is a prerequisite for data intense software applications. Recent research at the intersection of Machine Learning (ML) and Database Ma…
cs.LG2025
MechDetect: Detecting Data-Dependent Errors
Philipp Jung, Nicholas Chandler, Sebastian Jäger +1
Data quality monitoring is a core challenge in modern information processing systems. While many approaches to detect data errors or shifts have been proposed, few studies investig…