Comparative Study and Evaluation of Hybrid Visualizations of Graphs

Abstract

Hybrid visualizations combine different metaphors into a single network layout, in order to help humans in finding the "right way" of displaying the different portions of the network, especially when it is globally sparse and locally dense. We investigate hybrid visualizations in two complementary directions: (i) On the one hand, we evaluate the effectiveness of different hybrid visualization models through a comparative user study; (ii) On the other hand, we estimate the usefulness of an interactive visualization that integrates all the considered hybrid models together. The results of our study provide some hints about the usefulness of the different hybrid visualizations for specific tasks of analysis and indicates that integrating different hybrid models into a single visualization may offer a valuable tool of analysis.

De-Emphasise, Aggregate, and Hide: A Study of Interactive Visual Transformations for Group Structures in Network Visualisations

“…Overall, our results are also in line with the findings from Di Giacomo et al, where participants positively evaluated an interactive system combining several group-based hybrid visualisations [5].…”

“…A common way to investigate networks of interest is to visualise them and explore these visualisations. Networks can be visualised as node-link diagrams [1], adjacency matrices [2], [3], or using hybrid representations [4], [5]. In our evaluation, we focus on node-link diagrams as the most commonly used representation.…”

DynTrix: A Hybrid Representation for Dynamic Graphs

“…We chose this type of evaluation for different reasons. First, we thought about making a comparative user study as in the work by Didimo et al [GDL*22], however we did not find suitable candidates to compare DynTrix with, as both NodeTrix and Chordlink (see Section 2) focus on static graphs. Therefore, the comparison would not include the temporal aspects of the visualization, While having users solving tasks about the data would have shed light on the readability and usability of the visualization, we believed that it would have been more interesting investigating the “holistic” value of DynTrix design, its ability to provide a “ true understanding of the data ” [WAM*19], and whether is capable of generating insights and knowledge beyond specific pre‐determined tasks.…”

“…The size of the sectors and the width of the edge can be used to encode further variables. Didimo et al [GDL*22] recently performed a user study where the performance of various hybrid graph representations, including Nodetrix and Chordlink, are evaluated on tasks concerning the analysis of clustered networks. The results suggest that while they do not accelerate the analysis process, hybrid representations tend to be more accurate, with Nodetrix being recommended when the analysis task entails identifying attributes of single nodes.…”

“…One of the most known examples is NodeTrix [HFM07]: it combines the adjacency matrix representation for dense communities and a node‐link representation to connect them to each other, improving support for path finding and overview tasks. This type of techniques gained significant research attention for their potential in showing complex structures in different types of networks, including social, biological, financial, and collaboration networks [HFM07,GDL*22]. Research on hybrid representations however exclusively focused on the static scenario, disregarding whether their advantages could be leveraged in a dynamic context as well – a research question we tackle in this paper.…”