IEEE VIS 2024 Content: Quality Metrics and Reordering Strategies for Revealing Patterns in BioFabric Visualizations

Quality Metrics and Reordering Strategies for Revealing Patterns in BioFabric Visualizations

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Johannes Fuchs - University of Konstanz, Konstanz, Germany

 Alexander Frings - University of Konstanz, Konstanz, Germany

 Maria-Viktoria Heinle - University of Konstanz, Konstanz, Germany

 Daniel Keim - University of Konstanz, Konstanz, Germany

 Sara Di Bartolomeo - University of Konstanz, Konstanz, Germany. TU Wien, Vienna, Austria

 Room: Bayshore I

2024-10-16T17:57:00ZGMT-0600Change your timezone on the schedule page
2024-10-16T17:57:00Z

Exemplar figure, described by caption below — The same synthetic data is visualized with BioFabric. The edge order has a huge influence on the appearance of patterns. A random edge order shows no topological structure, whereas our degreecending technique reveals three staircases and one path.

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Keywords

Network Visualization, Graph Drawing, Graph Layout Algorithms, BioFabric, Graph Motif

Abstract

Visualizing relational data is crucial for understanding complex connections between entities in social networks, political affiliations, or biological interactions. Well-known representations like node-link diagrams and adjacency matrices offer valuable insights, but their effectiveness relies on the ability to identify patterns in the underlying topological structure. Reordering strategies and layout algorithms play a vital role in the visualization process since the arrangement of nodes, edges, or cells influences the visibility of these patterns. The BioFabric visualization combines elements of node-link diagrams and adjacency matrices, leveraging the strengths of both, the visual clarity of node-link diagrams and the tabular organization of adjacency matrices.A unique characteristic of BioFabric is the possibility to reorder nodes and edges separately.This raises the question of which combination of layout algorithms best reveals certain patterns. In this paper, we discuss patterns and anti-patterns in BioFabric, such as staircases or escalators, relate them to already established patterns, and propose metrics to evaluate their quality. Based on these quality metrics, we compared combinations of well-established reordering techniques applied to BioFabric with a well-known benchmark data set. Our experiments indicate that the edge order has a stronger influence on revealing patterns than the node layout. The results show that the best combination for revealing staircases is a barycentric node layout, together with an edge order based on node indices and length.Our research contributes a first building block for many promising future research directions, which we also share and discuss. A free copy of this paper and all supplemental materials are available at https://osf.io/9mt8r/?view_only=b70dfbe550e3404f83059afdc60184c6