Value-driven evaluation of visualizations

Abstract

Existing evaluations of data visualizations often employ a series of low-level, detailed questions to be answered or benchmark tasks to be performed. While that methodology can be helpful to determine a visualization's usability, such evaluations overlook the key benefits that visualization uniquely provides over other data analysis methods. I propose a value-driven evaluation of visualizations in which a person illustrates a system's value through four important capabilities: minimizing the time to answer diverse questions, spurring the generation of insights and insightful questions, conveying the essence of the data, and generating confidence and knowledge about the data's domain and context. Additionally, I explain how interaction is instrumental in creating much of the value that can be found in visualizations.