A Critical Reflection on the Values and Assumptions in Data Visualization

TL;DR

This paper critically examines foundational values in data visualization, such as universality, objectivity, and efficiency, advocating for a more diverse and pluralistic approach to future visualization research and practice.

Contribution

It analyzes the underlying values in seminal visualization works and calls for embracing diverse perspectives to enrich visualization research and tools.

Findings

Identifies core values in foundational visualization literature

Highlights the influence of these values on current practices

Advocates for a broader range of perspectives in visualization

Abstract

Visualization has matured into an established research field, producing widely adopted tools, design frameworks, and empirical foundations. As the field has grown, ideas from outside computer science have increasingly entered visualization discourse, questioning the fundamental values and assumptions on which visualization research stands. In this short position paper, we examine a set of values that we see underlying the seminal works of Jacques Bertin, John Tukey, Leland Wilkinson, Colin Ware, and Tamara Munzner. We articulate three prominent values in these texts - universality, objectivity, and efficiency - and examine how these values permeate visualization tools, curricula, and research practices. We situate these values within a broader set of critiques that call for more diverse priorities and viewpoints. By articulating these tensions, we call for our community to embrace a more pluralistic range of values to shape our future visualization tools and guidelines.