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    On Quality Indicators for Progressive Visual Analytics

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    025-029.pdf (1.166Mb)
    Date
    2019
    Author
    Angelini, Marco ORCID
    May, Thorsten
    Santucci, Giuseppe
    Schulz, Hans-Jörg ORCID
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    Abstract
    A key component in using Progressive Visual Analytics (PVA) is to be able to gauge the quality of intermediate analysis outcomes. This is necessary in order to decide whether a current partial outcome is already good enough to cut a long-running computation short and to proceed. To aid in this process, we propose ten fundamental quality indicators that can be computed and displayed to gain a better understanding of the progress of the progression and of the stability and certainty of an intermediate outcome. We further highlight the use of these fundamental indicators to derive other quality indicators, and we show how to apply the indicators in two use cases.
    BibTeX
    @inproceedings {10.2312:eurova.20191120,
    booktitle = {EuroVis Workshop on Visual Analytics (EuroVA)},
    editor = {Landesberger, Tatiana von and Turkay, Cagatay},
    title = {{On Quality Indicators for Progressive Visual Analytics}},
    author = {Angelini, Marco and May, Thorsten and Santucci, Giuseppe and Schulz, Hans-Jörg},
    year = {2019},
    publisher = {The Eurographics Association},
    ISBN = {978-3-03868-087-1},
    DOI = {10.2312/eurova.20191120}
    }
    URI
    https://doi.org/10.2312/eurova.20191120
    https://diglib.eg.org:443/handle/10.2312/eurova20191120
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    Eurographics Association copyright © 2013 - 2022 
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    System hosted at  Graz University of Technology.
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