The state of the art in empirical user evaluation of graph visualizations

Burch, M., Huang, W., Wakefield, M., Purchase, H. C. , Weiskopf, D. and Hua, J. (2020) The state of the art in empirical user evaluation of graph visualizations. IEEE Access, 9, pp. 4173-4198. (doi: 10.1109/ACCESS.2020.3047616)

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 paper, 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.

• Item Type: Articles
• Additional Information: This work was partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 251654672 – TRR 161.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Purchase, Dr Helen
• Authors: Burch, M., Huang, W., Wakefield, M., Purchase, H. C., Weiskopf, D., and Hua, J.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: IEEE Access
• Publisher: IEEE
• ISSN: 2169-3536
• ISSN (Online): 2169-3536
• Published Online: 28 December 2020
• Copyright Holders: Copyright © 2020 The Authors
• First Published: First published in IEEE Access 9: 4173-4198
• Publisher Policy: Reproduced under a Creative Commons License