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    A Survey of Multi-faceted Graph Visualization

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    Date
    2015
    Author
    Hadlak, Steffen
    Schumann, Heidrun
    Schulz, Hans-Jörg ORCID
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    Abstract
    Graph visualization is an important field in information visualization that is centered on the graphical display of graph-structured data. Yet real world data is rarely just graph-structured, but instead exhibits multiple facets, such as multivariate attributes, or spatial and temporal frames of reference. In an effort to display different facets of a graph, such a wealth of visualization techniques has been developed in the past that current surveys focus on a single additional facet only in order to enumerate and classify them. This report builds on existing graph visualization surveys for the four common facets of partitions, attributes, time, and space. It contributes a generic high-level categorization of faceted graph visualization that subsumes the existing classifications, which can be understood as facet-specific refinements of the resulting categories. Furthermore, it extends beyond existing surveys by applying the same categorization to graph visualizations with multiple facets. For each of the introduced categories and considered facets, this overview provides visualization examples to illustrate instances of their realization.
    BibTeX
    @inproceedings {10.2312:eurovisstar.20151109,
    booktitle = {Eurographics Conference on Visualization (EuroVis) - STARs},
    editor = {R. Borgo and F. Ganovelli and I. Viola},
    title = {{A Survey of Multi-faceted Graph Visualization}},
    author = {Hadlak, Steffen and Schumann, Heidrun and Schulz, Hans-Jörg},
    year = {2015},
    publisher = {The Eurographics Association},
    DOI = {10.2312/eurovisstar.20151109}
    }
    URI
    http://dx.doi.org/10.2312/eurovisstar.20151109
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA