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cs.IR2026
A Model-Driven Pipeline for Data Quality Specification and Operationalization: A No-Code Approach for Domain Experts
Arno Kesper, Lukas Sebastian Hofmann, Markus Matoni +1
High-quality data is essential for reliable analysis, decision-making, and research across domains. This is especially relevant in areas such as cultural heritage, where data is co…
cs.DB2026
Domain-Specific Data Quality Analysis Using Technology-Independent Query Templates
Arno Kesper, Lukas Sebastian Hofmann, Markus Matoni +1
In an increasingly data-driven world, effectively working with data depends heavily on its quality. Quality analysis is a central aspect of data quality management. As data quality…
cs.DB2026
Quality of Descriptive Information on Cultural Heritage Objects: Definition and Empirical Evaluation
Markus Matoni, Arno Kesper, Gabriele Taentzer
Effective data processing depends on the quality of the underlying data. However, quality issues such as inconsistencies and uncertainties, can significantly impede the processing…