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dc.contributor.authorYau, Calvinen_US
dc.contributor.authorKarimzadeh, Mortezaen_US
dc.contributor.authorSurakitbanharn, Chittayongen_US
dc.contributor.authorElmqvist, Niklasen_US
dc.contributor.authorEbert, Daviden_US
dc.contributor.editorGleicher, Michael and Viola, Ivan and Leitte, Heikeen_US
dc.date.accessioned2019-06-02T18:28:03Z
dc.date.available2019-06-02T18:28:03Z
dc.date.issued2019
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.13696
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13696
dc.description.abstractCommunication-minded visualizations are designed to provide their audience-managers, decision-makers, and the public-with new knowledge. Authoring such visualizations effectively is challenging because the audience often lacks the expertise, context, and time that professional analysts have at their disposal to explore and understand datasets. We present a novel summarized line graph visualization technique designed specifically for data analysts to communicate data to decision-makers more effectively and efficiently. Our summarized line graph reduces a large and detailed dataset of multiple quantitative time-series into (1) representative data that provides a quick takeaway of the full dataset; (2) analytical highlights that distinguish specific insights of interest; and (3) a data envelope that summarizes the remaining aggregated data. Our summarized line graph achieved the best overall results when evaluated against line graphs, band graphs, stream graphs, and horizon graphs on four representative tasks.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectVisualization techniques
dc.subjectInformation visualization
dc.titleBridging the Data Analysis Communication Gap Utilizing a Three-Component Summarized Line Graphen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersTime Series
dc.description.volume38
dc.description.number3
dc.identifier.doi10.1111/cgf.13696
dc.identifier.pages375-386


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  • 38-Issue 3
    EuroVis 2019 - Conference Proceedings

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