Understanding user preferences in time-based accuracy visualizations

This study investigates how users perceive and evaluate different time-based data visualizations that represent the relative proportion of correctly classified failures over time.

The study also explores potential differences in perception between distinct user groups. In particular, we compare perspectives from participants working in industrial contexts (e.g., production, logistics, transportation) with those from participants who have expertise in data visualization.

The visualizations are based on data derived from a multi-machine production environment. They are intended to support the interpretation of temporal developments in classification accuracy, for example identifying whether values improve, decline, or remain stable over multiple years.

The objective of this research is to understand how different visualization formats are perceived in terms of their suitability for identifying temporal trends, and whether these perceptions vary across user groups.

Participation in this survey is voluntary. All responses are collected anonymously and will be analyzed exclusively for research purposes. No personally identifiable information is recorded, and the data will be processed only in aggregated form for publishing reasons.

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