• Login
    View Item 
    •   Eurographics DL Home
    • Computer Graphics Forum
    • Volume 35 (2016)
    • 35-Issue 3
    • View Item
    •   Eurographics DL Home
    • Computer Graphics Forum
    • Volume 35 (2016)
    • 35-Issue 3
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Pathfinder: Visual Analysis of Paths in Graphs

    Thumbnail
    View/Open
    v35i3pp071-080.pdf (1.023Mb)
    0160-file2.pdf (693.2Kb)
    0160-file1.mp4 (67.82Mb)
    Date
    2016
    Author
    Partl, Christian
    Gratzl, Samuel
    Streit, Marc
    Wassermann, Anne-Mai
    Pfister, Hanspeter
    Schmalstieg, Dieter
    Lex, Alexander
    Pay-Per-View via TIB Hannover:

    Try if this item/paper is available.

    Metadata
    Show full item record
    Abstract
    The analysis of paths in graphs is highly relevant in many domains. Typically, path-related tasks are performed in node-link layouts. Unfortunately, graph layouts often do not scale to the size of many real world networks. Also, many networks are multivariate, i.e., contain rich attribute sets associated with the nodes and edges. These attributes are often critical in judging paths, but directly visualizing attributes in a graph layout exacerbates the scalability problem. In this paper, we present visual analysis solutions dedicated to path-related tasks in large and highly multivariate graphs. We show that by focusing on paths, we can address the scalability problem of multivariate graph visualization, equipping analysts with a powerful tool to explore large graphs. We introduce Pathfinder, a technique that provides visual methods to query paths, while considering various constraints. The resulting set of paths is visualized in both a ranked list and as a node-link diagram. For the paths in the list, we display rich attribute data associated with nodes and edges, and the node-link diagram provides topological context. The paths can be ranked based on topological properties, such as path length or average node degree, and scores derived from attribute data. Pathfinder is designed to scale to graphs with tens of thousands of nodes and edges by employing strategies such as incremental query results. We demonstrate Pathfinder's fitness for use in scenarios with data from a coauthor network and biological pathways.
    BibTeX
    @article {10.1111:cgf.12883,
    journal = {Computer Graphics Forum},
    title = {{Pathfinder: Visual Analysis of Paths in Graphs}},
    author = {Partl, Christian and Gratzl, Samuel and Streit, Marc and Wassermann, Anne-Mai and Pfister, Hanspeter and Schmalstieg, Dieter and Lex, Alexander},
    year = {2016},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.12883}
    }
    URI
    http://dx.doi.org/10.1111/cgf.12883
    https://diglib.eg.org:443/handle/10
    Collections
    • 35-Issue 3
    • EuroVis16: Eurographics Conference on Visualization

    Eurographics Association copyright © 2013 - 2020 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA
     

     

    Browse

    All of Eurographics DLCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    BibTeX | TOC

    Create BibTeX Create Table of Contents

    Eurographics Association copyright © 2013 - 2020 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA