Taxonomy for interactive visual analysis

Interactive visualization continues to grow more useful and prominent in every day analysis. Jeffrey Heer and Ben Shneiderman offer a taxonomy for the budding field.

Visualization provides a powerful means of making sense of data. By mapping data attributes to visual properties such as position, size, shape, and color, visualization designers leverage perceptual skills to help users discern and interpret patterns within data. A single image, however, typically provides answers to, at best, a handful of questions. Instead, visual analysis typically progresses in an iterative process of view creation, exploration, and refinement. Meaningful analysis consists of repeated explorations as users develop insights about significant relationships, domain-specific contextual influences, and causal patterns. Confusing widgets, complex dialog boxes, hidden operations, incomprehensible displays, or slow response times can limit the range and depth of topics considered and may curtail thorough deliberation and introduce errors. To be most effective, visual analytics tools must support the fluent and flexible use of visualizations at rates resonant with the pace of human thought.

[ACM Queue via @krees]

Favorites

Unemployment in America, Mapped Over Time

Watch the regional changes across the country from 1990 to 2016.

Graphical perception – learn the fundamentals first

Before you dive into the advanced stuff – like just about everything in your life – you have to learn the fundamentals before you know when you can break the rules.

Best Data Visualization Projects of 2016

Here are my favorites for the year.

How to Spot Visualization Lies

Many charts don’t tell the truth. This is a simple guide to spotting them.