Massive simulations and arrays of sensing devices, in combination with increasing
computing resources, have generated large, complex, high-dimensional datasets used to …

Abstract 3D representations are potentially useful under many circumstances, but suffer from
long known perception and interaction challenges. Current immersive technologies, which …

Given a scatterplot with tens of thousands of points or even more, a natural question is which
sampling method should be used to create a small but “good” scatterplot for a better …

Scatterplots are among the most widely used visualization techniques. Compelling
scatterplot visualizations improve understanding of data by leveraging visual perception to …

Single-cell RNAseq is a routinely used method to explore heterogeneity within cell
populations. Data from these experiments are often visualized using dimension reduction …

Understanding three-dimensional projections created by dimensionality reduction from high-
variate datasets is very challenging. In particular, classical three-dimensional scatterplots …

We introduce a novel interactive framework for visualizing and exploring high‐dimensional
datasets based on subspace analysis and dynamic projections. We assume the high …

The analysis of vast amounts of network data for monitoring and safeguarding a core pillar of
the internet, the root DNS, is an enormous challenge. Understanding the distribution of the …

We propose Steadiness and Cohesiveness, two novel metrics to measure the inter-cluster
reliability of multidimensional projection (MDP), specifically how well the inter-cluster …

ABSTRACT 3D virtual reality (VR) technology has long promised to provide new ways to
view and interact with abstract data, but it has been held back by technological limitations …