"I Came Across a Junk": Understanding Design Flaws of Data Visualization from the Public's Perspective

TL;DR

This work investigated visualization design flaws through the lens of the public, constructed a framework to summarize and categorize the identified flaws, and explored why these flaws occur.

Abstract

The visualization community has a rich history of reflecting upon flaws of visualization design, and research in this direction has remained lively until now. However, three main gaps still exist. First, most existing work characterizes design flaws from the perspective of researchers rather than the perspective of general users. Second, little work has been done to infer why these design flaws occur. Third, due to problems such as unclear terminology and ambiguous research scope, a better framework that systematically outlines various design flaws and helps distinguish different types of flaws is desired. To address the above gaps, this work investigated visualization design flaws through the lens of the public, constructed a framework to summarize and categorize the identified flaws, and explored why these flaws occur.

Figures (10)

• Figure 1: Visualization design flaws and their frequencies. More descriptions for each flaw can be browsed at https://flawviz.github.io/.
• Figure 2: Examples of identified design flaws in data visualization, with indexes showing their corresponding categories.
• Figure 3: Locating R1-R7 identified in \ref{['sec:focus']} in the InfoVis reference model card1999readings. O1-O9 correspond to the nine research opportunities discussed in \ref{['sec:agenda']}.
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