Many data sets, crucial for today's applications, consist of enormous networks, containing millions or even billions of elements. Having the possibility of visualizing such networks is of paramount importance. We propose an algorithmic framework and a visual metaphor, dubbed Treebar Maps, to provide schematic representations of huge networks. Our goal is to convey the main features of the network's inner structure in a straightforward, two-dimensional, one-page drawing, that effectively captures the essential quantitative information about the network's main components. Experiments show that we are able to create such representations in a few hundreds of seconds. We demonstrate the metaphor's efficacy through visual examination of extensive graphs, highlighting how their diverse structures are instantly comprehensible via their representations.

Di Battista, G., Grosso, F., Montorselli, S., Patrignani, M. (2024). Treebar Maps: Schematic Representation of Networks at Scale. In IEEE Pacific Visualization Symposium (pp.132-141). 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA : IEEE Computer Society [10.1109/PacificVis60374.2024.00023].

Treebar Maps: Schematic Representation of Networks at Scale

Di Battista G.;Grosso F.;Montorselli S.;Patrignani M.
2024-01-01

Abstract

Many data sets, crucial for today's applications, consist of enormous networks, containing millions or even billions of elements. Having the possibility of visualizing such networks is of paramount importance. We propose an algorithmic framework and a visual metaphor, dubbed Treebar Maps, to provide schematic representations of huge networks. Our goal is to convey the main features of the network's inner structure in a straightforward, two-dimensional, one-page drawing, that effectively captures the essential quantitative information about the network's main components. Experiments show that we are able to create such representations in a few hundreds of seconds. We demonstrate the metaphor's efficacy through visual examination of extensive graphs, highlighting how their diverse structures are instantly comprehensible via their representations.
2024
Di Battista, G., Grosso, F., Montorselli, S., Patrignani, M. (2024). Treebar Maps: Schematic Representation of Networks at Scale. In IEEE Pacific Visualization Symposium (pp.132-141). 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA : IEEE Computer Society [10.1109/PacificVis60374.2024.00023].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/490756
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