{"title":"A 3D Visualization of Multiple Time Series on Maps","authors":"Sidharth Thakur, A. Hanson","doi":"10.1109/IV.2010.54","DOIUrl":null,"url":null,"abstract":"In the analysis of spatially-referenced time-dependent data, gaining an understanding of the spatio-temporal distributions and relationships among the attributes in the data can be quite difficult. We present a visualization technique that addresses some of the challenges involved in visually exploring and analyzing the distributions of geo-spatial time-varying data. We have developed a pictorial representation that is based on the standard space-time cube metaphor and provides in a single display the overview and details of a large number of time-varying quantities. Our approach involves three-dimensional graphical widgets that intuitively represent profiles of the time-varying quantities and can be plotted on a geographic map to expose interesting spatio-temporal distributions of the data. We show how combining our visualization technique with standard data exploration features can assist in the exploration of salient patterns in a data set. The visualization approach described here supports expeditious exploration of multiple data sets; this in turn assists the process of building initial hypotheses about the attributes in a data set and enhances the user's ability to pose and explore interesting questions about the data.","PeriodicalId":328464,"journal":{"name":"2010 14th International Conference Information Visualisation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"40","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 14th International Conference Information Visualisation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IV.2010.54","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 40
Abstract
In the analysis of spatially-referenced time-dependent data, gaining an understanding of the spatio-temporal distributions and relationships among the attributes in the data can be quite difficult. We present a visualization technique that addresses some of the challenges involved in visually exploring and analyzing the distributions of geo-spatial time-varying data. We have developed a pictorial representation that is based on the standard space-time cube metaphor and provides in a single display the overview and details of a large number of time-varying quantities. Our approach involves three-dimensional graphical widgets that intuitively represent profiles of the time-varying quantities and can be plotted on a geographic map to expose interesting spatio-temporal distributions of the data. We show how combining our visualization technique with standard data exploration features can assist in the exploration of salient patterns in a data set. The visualization approach described here supports expeditious exploration of multiple data sets; this in turn assists the process of building initial hypotheses about the attributes in a data set and enhances the user's ability to pose and explore interesting questions about the data.