3 papers
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.HC2026
Bridging the Gap between Micro-scale Traffic Simulation and 4D Digital Cityscapes
Longxiang Jiao, Lukas Hofmann, Yiru Yang +2
While micro-scale traffic simulations provide essential data for urban planning, they are rarely coupled with the high-fidelity visualization or auralization necessary for effectiv…