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dc.contributor.authorDimara, Evanthiaen_US
dc.contributor.authorValdivia, Paolaen_US
dc.contributor.authorKinkeldey, Christophen_US
dc.contributor.editorAnna Puig Puig and Tobias Isenbergen_US
dc.date.accessioned2017-06-12T05:17:53Z
dc.date.available2017-06-12T05:17:53Z
dc.date.issued2017
dc.identifier.isbn978-3-03868-044-4
dc.identifier.urihttp://dx.doi.org/10.2312/eurp.20171165
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurp20171165
dc.description.abstractVisualizations designed to support multi-attribute decisions often use colors to encode the identity of the attributes. This approach facilitates mapping of attributes across multiple coordinated views but it has certain limitations: colors often communicate semantics (e.g., red stands for ''danger'') deemed to influence the user's preference, and qualitative color palettes are of limited scalability. We are currently developing a tool with an alternative approach, DCPAIRS: a pairs plot based decision making support tool that employs a compact overview of the decision space and uses visual encodings that communicate uncertainty and suboptimal preference elicitation. Instead of encoding the identity of attributes we use colors for user-authored annotations to support the decision making process. A use case scenario of a prospective undergraduate student choosing a university from the ''QS world university ranking'' dataset illustrates the functionality of the tool.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectVisualization System and Toolkit Design
dc.subjectScalability Issues
dc.subjectMultidimensional Data
dc.titleDcPAIRS: A Pairs Plot Based Decision Support Systemen_US
dc.description.seriesinformationEuroVis 2017 - Posters
dc.description.sectionheadersPosters
dc.identifier.doi10.2312/eurp.20171165
dc.identifier.pages45-47


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