Improved bipartite plots of ecological networks using the k-core decomposition with the BipartGraph application

Visualizing bipartite networks with the well-known bipartite plot often produces an obfuscated image. This article introduces an approach that uses a two-pronged strategy to improve the readability of conventional bipartite plots. First, it reorders the network layout based on the k-core decomposition, positioning the central species more prominently. Second, it reduces visual clutter by grouping and compactly representing peripheral nodes. The new plotting feature is integrated into the open-source R package kcorebip and is also offered in the interactive web application BipartGraph. We explain the advantages of this innovation through several representative use cases showcasing its ability to generate clearer, more interpretable visualizations.

Authors

Publication Details

Journal
PeerJ Computer Science
Published
2026-01-13
DOI
https://doi.org/10.7717/peerj-cs.3526
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

Improved bipartite plots of ecological networks using the k-core decomposition with the BipartGraph application

Javier Garcia-Algarra
PeerJ Computer Science
Data Visualization and Analytics
article

Improved bipartite plots of ecological networks using the k-core decomposition with the BipartGraph application

Javier Garcia-Algarra
article en

Abstract

Visualizing bipartite networks with the well-known bipartite plot often produces an obfuscated image. This article introduces an approach that uses a two-pronged strategy to improve the readability of conventional bipartite plots. First, it reorders the network layout based on the k-core decomposition, positioning the central species more prominently. Second, it reduces visual clutter by grouping and compactly representing peripheral nodes. The new plotting feature is integrated into the open-source R package kcorebip and is also offered in the interactive web application BipartGraph. We explain the advantages of this innovation through several representative use cases showcasing its ability to generate clearer, more interpretable visualizations.

PeerJ Computer ScienceVol. 12
Industry, innovation and infrastructure
Openalex Percentile: Top 91%
Data Visualization and Analytics
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