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dc.contributor.authorBartolomeo, Sara Dien_US
dc.contributor.authorPister, Alexisen_US
dc.contributor.authorBuono, Paoloen_US
dc.contributor.authorPlaisant, Catherineen_US
dc.contributor.authorDunne, Codyen_US
dc.contributor.authorFekete, Jean-Danielen_US
dc.contributor.editorBorgo, Ritaen_US
dc.contributor.editorMarai, G. Elisabetaen_US
dc.contributor.editorSchreck, Tobiasen_US
dc.date.accessioned2022-06-03T06:06:10Z
dc.date.available2022-06-03T06:06:10Z
dc.date.issued2022
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14538
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14538
dc.description.abstractHypergraphs are a generalization of graphs in which edges (hyperedges) can connect more than two vertices-as opposed to ordinary graphs where edges involve only two vertices. Hypergraphs are a fairly common data structure but there is little consensus on how to visualize them. To optimize a hypergraph drawing for readability, we need a layout algorithm. Common graph layout algorithms only consider ordinary graphs and do not take hyperedges into account. We focus on layered hypergraphs, a particular class of hypergraphs that, like layered graphs, assigns every vertex to a layer, and the vertices in a layer are drawn aligned on a linear axis with the axes arranged in parallel. In this paper, we propose a general method to apply layered graph layout algorithms to layered hypergraphs. We introduce six different transformations for layered hypergraphs. The choice of transformation affects the subsequent graph layout algorithm in terms of computational performance and readability of the results. Thus, we perform a comparative evaluation of these transformations in terms of number of crossings, edge length, and impact on performance. We also provide two case studies showing how our transformations can be applied to real-life use cases.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Human-centered computing --> Graph drawings; Visualization theory, concepts and paradigms
dc.subjectHuman centered computing
dc.subjectGraph drawings
dc.subjectVisualization theory
dc.subjectconcepts and paradigms
dc.titleSix Methods for Transforming Layered Hypergraphs to Apply Layered Graph Layout Algorithmsen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersHigh Dimensional Data
dc.description.volume41
dc.description.number3
dc.identifier.doi10.1111/cgf.14538
dc.identifier.pages259-270
dc.identifier.pages12 pages


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  • 41-Issue 3
    EuroVis 2022 - Conference Proceedings

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