Choosing visualization techniques for multidimensional data projection tasks: A guideline with examples

Abstract

This paper presents a guideline for visualization designers who want to choose appropriate techniques for enhancing tasks involving multidimensional projection. Specifically, we adopt a user-centric approach in which we take user perception into consideration. Here, we focus on projection techniques that output 2D or 3D scatterplots that can then be used for a range of common data analysis tasks, which we categorize as pattern identification tasks, relation-seeking tasks, membership disambiguation tasks, or behavior comparison tasks. Our user-centric task categorization can be used to effectively guide the organization of multidimensional data projection layouts. Moreover, we present realworld examples that demonstrate effective choices made by visualization designers faced with complex datasets requiring dimensionality reduction.