6 papers
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…
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…
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…
How to Define the Quality of Data? A Feature-Based Literature Survey
Markus Matoni, Arno Kesper, Gabriele Taentzer
The digital transformation of our society is a constant challenge, as data is generated in almost every digital interaction. To use data effectively, it must be of high quality. Th…
Detecting Quality Problems in Data Models by Clustering Heterogeneous Data Values
Viola Wenz, Arno Kesper, Gabriele Taentzer
Data is of high quality if it is fit for its intended use. The quality of data is influenced by the underlying data model and its quality. One major quality problem is the heteroge…
Detecting Quality Problems in Research Data: A Model-Driven Approach
Arno Kesper, Viola Wenz, Gabriele Taentzer
As scientific progress highly depends on the quality of research data, there are strict requirements for data quality coming from the scientific community. A major challenge in dat…