The State of the Art in Empirical User Evaluation of Graph Visualizations

Abstract

While graph drawing focuses more on the aesthetic representation of node-link diagrams, graph visualization takes into account other visual metaphors making them useful for graph exploration tasks in information visualization and visual analytics. Although there are aesthetic graph drawing criteria that describe how a graph should be presented to make it faster and more reliably explorable, many controlled and uncontrolled empirical user studies flourished over the past years. The goal of them is to uncover how well the human user performs graph-specific tasks, in many cases compared to previously designed graph visualizations. Due to the fact that many parameters in a graph dataset as well as the visual representation of them might be varied and many user studies have been conducted in this space, a state-of-the-art survey is needed to understand evaluation results and findings to inform the future design, research, and application of graph visualizations. In this article, we classify the present literature on the topmost level into graph interpretation, graph memorability, and graph creation where the users with their tasks stand in focus of the evaluation, not the computational aspects. As another outcome of this work, we identify the white spots in this field and sketch ideas for future research directions.

Placing Arrows in Directed Graph Layouts: Algorithms and Experiments

“…Similar to many user studies in graph visualization (see the recent survey of Burch et al . [BHW*21]), we used a between‐subject design. Namely, exposing the users to all three conditions would have implied each user solving 72 trials (12 graphs $$\times 2$$ tasks $$\times 3$$ conditions).…”

Path Tracing in 2D, 3D, and Physicalized Networks

“…Network visualization constitutes a large literature [5], [34], [35], [36], [37]. Some previous works have evaluated networks embedded in 3D [38], [39], [40] but without focusing on the question of comparing a flat 2D layout (on a plane) vs fully 3D layout (with nodes distributed throughout a volume).…”

A User Study on Hybrid Graph Visualizations

“…Our work falls into the research line devoted to the design of user experiments in graph drawing and network visualization. We recall here the contributions that are mainly related to our study; refer to [19] for a comprehensive survey on the subject. There is a series of works that compare node-link diagrams with matrixbased representations (see, e.g., [3,4,20,25,30,36,47,48]).…”

“…According to the top-level task classification by Burch et al [19], all our tasks are interpretation tasks, as our goal is to evaluate the differences of the considered visualization models in terms of readability, understandability, and effectiveness. About task T5, we point out that there are two commonly used definitions for the density of a graph with n nodes and m edges:…”