There are some open questions within the data visualization community as to what benefits the third dimension might add to visualizing information that doesn’t have an inherent spatial component.

Compound graphs, a frequently encountered type of data set, have a hierarchical tree structure with parent-child relations (‘inclusion’ relations) and non-hierarchical relations between leaf nodes ...

Topological Data Analysis (TDA) is an increasingly influential framework that leverages the principles of algebraic topology to extract, quantify and visualise the intrinsic structure of complex, high ...

The t-SNE ("t-distributed Stochastic Neighbor Embedding") technique is a method for visualizing high-dimensional data. The basic t-SNE technique is very specific: It converts data with three or more ...

Cartogram visualisation has undergone substantial evolution, merging geographic representation with quantitative data display. At its core, a cartogram resizes regions such that their areas are ...

Choosing the right way to visualize your data makes the difference between telling a clear, compelling story or creating cognitive overload. Here's how to pick. Data is best understood when presented ...

This pie chart illustrates the distribution of visualization tools in the FigureYa resource package across three dimensions: research type (outer ring), analysis method (middle ring), and output ...