Share on Facebook Tweet on Twitter Share on LinkedIn Share by email
Sample-Oriented Task-Driven Visualizations: Allowing Users to Make Better, More Confident Decisions

Nivan Ferreira, Danyel Fisher, and Arnd Christian König

Abstract

We often use datasets that reflect samples, but many visualization tools treat data as full populations. Uncertain visualizations are good at representing data distributions emerging from samples, but are more limited in allowing users to carry out decision tasks. This is because tasks that are simple on a traditional chart (e.g. “compare two bars”) become a complex probabilistic task on a chart with uncertainty. We present guidelines for creating visual annotations for solving tasks with uncertainty, and an implementation that addresses five core tasks on a bar chart. A preliminary user study shows promising results: that users have a justified confidence in their answers with our system.

Details

Publication typeInproceedings
Published inProceedings of Conference on Human Factors in Computing Systems (CHI 2014)
PublisherACM
> Publications > Sample-Oriented Task-Driven Visualizations: Allowing Users to Make Better, More Confident Decisions