Knowledge of human perception has long been incorporated into visualizations to enhance
their quality and effectiveness. The last decade, in particular, has shown an increase in …

Visual analysis of multidimensional data requires expressive and effective ways to reduce
data dimensionality to encode them visually. Multidimensional projections (MDP) figure …

Visualizations of tabular data are widely used; understanding their effectiveness in different
task and data contexts is fundamental to scaling their impact. However, little is known about …

The visualization community has developed to date many intuitions and understandings of
how to judge the quality of views in visualizing data. The computation of a visualization's …

Visualization and artificial intelligence (AI) are well-applied approaches to data analysis. On
one hand, visualization can facilitate humans in data understanding through intuitive visual …

In addition to the choice of visual encodings, the effectiveness of a data visualization may
vary with the analytical task being performed and the distribution of data values. To better …

Immersive Analytics (IA) uses immersive virtual and augmented reality displays for data
visualization and visual analytics. Designers rely on studies of how accurately people …

Similarity measuring methods are widely adopted in a broad range of visualization
applications. In this work, we address the challenge of representing human perception in the …

Topic models are a class of unsupervised learning algorithms for detecting the semantic
structure within a text corpus. Together with a subsequent dimensionality reduction …

Famous examples such as Anscombe's Quartet highlight that one of the core benefits of
visualizations is allowing people to discover visual patterns that might otherwise be hidden …