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    VisMiFlow: Visual Analytics to Support Citizen Migration Understanding Over Time and Space

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    Date
    2021
    Author
    Scheidl, Andreas
    Leite, Roger A.
    Miksch, Silvia ORCID
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    Abstract
    Multivariate networks are complex data structures, which are ubiquitous in many application domains. Driven by a real-world problem, namely the movement behavior of citizens in Vienna, we designed and implemented a Visual Analytics (VA) approach to ease citizen behavior analyses over time and space. We used a dataset of citizens' movement behavior to, from, or within Vienna from 2007 to 2018, provided by Vienna's city. To tackle the complexity of time, space, and other moving people's attributes, we follow a data-user-tasks design approach to support urban developers. We qualitatively evaluated our VA approach with five experts coming from the field of VA and one non-expert. The evaluation illustrated the importance of task-specific visualization and interaction techniques to support users' decision-making and insights. We elaborate on our findings and suggest potential future works to the field.
    BibTeX
    @inproceedings {10.2312:evs.20211056,
    booktitle = {EuroVis 2021 - Short Papers},
    editor = {Agus, Marco and Garth, Christoph and Kerren, Andreas},
    title = {{VisMiFlow: Visual Analytics to Support Citizen Migration Understanding Over Time and Space}},
    author = {Scheidl, Andreas and Leite, Roger A. and Miksch, Silvia},
    year = {2021},
    publisher = {The Eurographics Association},
    ISBN = {978-3-03868-143-4},
    DOI = {10.2312/evs.20211056}
    }
    URI
    https://doi.org/10.2312/evs.20211056
    https://diglib.eg.org:443/handle/10.2312/evs20211056
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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