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.

Data visualization is one of the most important tools we have to analyze data. But it’s just as easy to mislead as it is to educate using charts and graphs. In this article we’ll take a look at 3 of ...

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 ...

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 ...