dc.contributor.author | Dimara, Evanthia | en_US |
dc.contributor.author | Valdivia, Paola | en_US |
dc.contributor.author | Kinkeldey, Christoph | en_US |
dc.contributor.editor | Anna Puig Puig and Tobias Isenberg | en_US |
dc.date.accessioned | 2017-06-12T05:17:53Z | |
dc.date.available | 2017-06-12T05:17:53Z | |
dc.date.issued | 2017 | |
dc.identifier.isbn | 978-3-03868-044-4 | |
dc.identifier.uri | http://dx.doi.org/10.2312/eurp.20171165 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/eurp20171165 | |
dc.description.abstract | Visualizations 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.publisher | The Eurographics Association | en_US |
dc.subject | Visualization System and Toolkit Design | |
dc.subject | Scalability Issues | |
dc.subject | Multidimensional Data | |
dc.title | DcPAIRS: A Pairs Plot Based Decision Support System | en_US |
dc.description.seriesinformation | EuroVis 2017 - Posters | |
dc.description.sectionheaders | Posters | |
dc.identifier.doi | 10.2312/eurp.20171165 | |
dc.identifier.pages | 45-47 | |