Reviewing Data Visualization: an Analytical Taxonomical Study

TL;DR

This paper develops an analytical taxonomy of data visualization techniques focusing on their mechanisms and perceptual foundations to better understand how they convey meaning.

Contribution

It introduces a novel taxonomy that describes visualization techniques based on their underlying mechanisms and perceptual principles, moving beyond simple classification.

Findings

Provides a model explaining how visualization techniques work

Enhances understanding of visualization mechanisms and perception

Facilitates better design and analysis of visualization methods

Abstract

This paper presents an analytical taxonomy that can suitably describe, rather than simply classify, techniques for data presentation. Unlike previous works, we do not consider particular aspects of visualization techniques, but their mechanisms and foundational vision perception. Instead of just adjusting visualization research to a classification system, our aim is to better understand its process. For doing so, we depart from elementary concepts to reach a model that can describe how visualization techniques work and how they convey meaning.