Data Visualization: Preference and Use of Two-Dimensional and Three-Dimensional Graphs

Abstract

This study considered the interplay of simple versus perspective graphical information on aesthetic preference, instructional effectiveness, and retention. Students in an introductory U.S. government course were presented with examples of 2-D and 3-D graphs and asked to choose which was pleasing to the eye and which was most useful in answering questions about the graph's content. The results of this study indicated that when visual appeal was the only criterion, subject choices overall were approximately evenly matched. When subjects were required to extract information from graphs, they used simple graphs almost 3 times more often than elaborate graphs. Information drawn from bar and circle graphs was extracted more accurately than the other three types of graphs.

Executive Dashboard Widgets: A Performance-Based Comparative Analysis

“…In an earlier study, Fisher, Dempsey, and Marousky (1997) found mostly no difference between 2D and 3D performance, although subjects chose simple graphs almost 3 times as often as more complex graphs when asked to extract information. This was an interesting finding, since people in our first study reported preferences for 3D graphs.…”

Evaluating Visual Variables in a Virtual Reality Environment

“…Variables such as size, orientation, and opacity [9, 36] encode quantitative data information, while colour and shape are used for visualising nominal data. Fisher et al [34] investigated which 3D graph type was easiest to interpret among bar, pie, floating line, mixed bar/line, and layered line charts. It was revealed that information extracted from bar and pie charts were found to be more effective than others.…”

Data Visualization and Information Literacy

“…The techniques developed to produce these visualizations are both an art and a science, and should be appreciated and emulated by students, who should also learn to be cautious of oversimplification and approaches that sacrifice features of the data in favor of graphical elegance. For example, Fisher, Dempsey and Marousky (1997) show that despite more complex 3D forms being appealing to the eye, simpler 2D graphics were preferred when the task required actual extraction of information from the graphs. New methods, such as tableplots, are also being developed to simplify the visualization of large datasets (Tenneke, de Jonge and Daas, 2013).…”