The graph landscape: A concept for the visual analysis of graph set properties

Andrew J. Kennedy, Karsten Klein, An Nguyen

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    1 Citation (Scopus)

    Abstract

    In a variety of research and application areas graphs are an important structure for data modeling and analysis. While graph properties can have a crucial inuence on the performance of graph algorithms, and thus on the outcome of experiments, often only basic analysis of the graphs under investigation in an experimental evaluation is performed, and a few characteristics are reported in publications. We present Graph Landscape, a concept for the visual analysis of graph set properties. The Graph Landscape aims to support researchers to explore graphs and graph sets regarding their properties, in order to allow to select good experimental test sets, analyze newly generated sets, compare sets and assess the validity (or range) of experimental results and corresponding conclusions.

    Original languageEnglish
    Title of host publicationProceedings of the 8th International Symposium on Visual Information Communication and Interaction (VINCI 2015)
    Subtitle of host publicationTokyo, Japan, 24-26 August 2015
    EditorsPaolo Bottoni, Shigeo Takahashi, Takayuki Itoh
    Place of PublicationNew York NY USA
    PublisherAssociation for Computing Machinery (ACM)
    Pages42 - 51
    Number of pages10
    ISBN (Print)9781450334822
    DOIs
    Publication statusPublished - 24 Aug 2015
    EventInternational Symposium on Visual Information Communication and Interaction 2015 - Tokyo, Japan
    Duration: 24 Aug 201526 Aug 2015
    Conference number: 8th
    https://dl.acm.org/doi/proceedings/10.1145/2801040

    Conference

    ConferenceInternational Symposium on Visual Information Communication and Interaction 2015
    Abbreviated titleVINCI 2015
    Country/TerritoryJapan
    CityTokyo
    Period24/08/1526/08/15
    Internet address

    Keywords

    • Analysis
    • Graphs
    • Multidimensional data
    • Visualisation

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