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dc.contributor.authorValdivia, Paolaen_US
dc.contributor.authorBuono, Paoloen_US
dc.contributor.authorFekete, Jean-Danielen_US
dc.contributor.editorAnna Puig Puig and Tobias Isenbergen_US
dc.date.accessioned2017-06-12T05:17:52Z
dc.date.available2017-06-12T05:17:52Z
dc.date.issued2017
dc.identifier.isbn978-3-03868-044-4
dc.identifier.urihttp://dx.doi.org/10.2312/eurp.20171162
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurp20171162
dc.description.abstractWe present Hypenet, a novel technique to visualize dynamic hypergraphs. Such structures can model multiple types of data, such as computer networks with multiple destination addresses (multicast) or co-authorship networks with multiple authors per article. Hypenet visualizes the evolving topology of the hypergraph in a compact way, allowing users to detect patterns and inconsistencies. We describe our technique and show how it applies to the case of the history of publications of the Eurovis conference, revealing interesting patterns that can contribute to tell a story about data and create hypotheses.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectGraph/Network Data
dc.titleHypenet: Visualizing Dynamic Hypergraphsen_US
dc.description.seriesinformationEuroVis 2017 - Posters
dc.description.sectionheadersPosters
dc.identifier.doi10.2312/eurp.20171162
dc.identifier.pages33-35


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