{"title":"DcPAIRS: A Pairs Plot Based Decision Support System","authors":"Evanthia Dimara, Paola Valdivia, C. Kinkeldey","doi":"10.2312/eurp.20171165","DOIUrl":null,"url":null,"abstract":"Visualizations designed to support multi-attribute decisions often use colors to encode the identity of the attributes. This approach \nfacilitates mapping of attributes across multiple coordinated views but it has certain limitations: colors often communicate \nsemantics (e.g., red stands for “danger”) deemed to influence the user’s preference, and qualitative color palettes are \nof limited scalability. We are currently developing a tool with an alternative approach, DCPAIRS: a pairs plot based decision \nmaking support tool that employs a compact overview of the decision space and uses visual encodings that communicate uncertainty \nand suboptimal preference elicitation. Instead of encoding the identity of attributes we use colors for user-authored \nannotations to support the decision making process. A use case scenario of a prospective undergraduate student choosing a \nuniversity from the “QS world university ranking” dataset illustrates the functionality of the tool.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"600 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eurographics Conference on Visualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/eurp.20171165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
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.