Project: Dynamic and continuous graph visualization using ChordLink
Description
Dynamic networks can be found in several domains: they are at the heart of social network platforms, are used to map computer network topologies, and so on. As these network become larger and update fast, new techniques are necessary to ensure a meaningful visual analysis of this information.
Hybrid graph visualization were introduced for large networks, combining node-link diagrams with matrix-based or aggregated representations. ChordLink was designed with this in mind: clusters are represented as chord diagrams while the relationships between individual nodes are shown using a node-link representation. However, when the network changes over time, maintaining a stable and understandable visualization becomes more challenging.
In this project, the candidate investigates techniques for extending the ChordLink visualization paradigm to dynamic networks, focusing on how to represent changes in a smooth and continuous way. The goal is to study animation and transition strategies that preserve the user's mental map while the network evolves, considering events such as node and edge additions or removals, as well as nodes moving between clusters. The resulting techniques could provide a framework for interactively exploring evolving networks while preserving the advantages of the hybrid ChordLink representation.
The project will be developed in co-operation with the University of Perugia (Italy), offering the opportunity of expanding your international network of collaborations.
Recommended Readings:
- Lorenzo Angori, Walter Didimo, Fabrizio Montecchiani, Daniele Pagliuca, Alessandra Tappini: Hybrid Graph Visualizations With ChordLink: Algorithms, Experiments, and Applications. IEEE Trans. Vis. Comput. Graph. 28(2): 1288-1300 (2022)
- B. Vago, Daniel Archambault, Alessio Arleo: DynTrix: A Hybrid Representation for Dynamic Graphs. Comput. Graph. Forum 43(3) (2024)
Details
- Supervisor
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Alessio Arleo
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