B. Morrow, Trevor Manz, Arlene E. Chung, N. Gehlenborg, D. Gotz
{"title":"Periphery Plots for Contextualizing Heterogeneous Time-Based Charts","authors":"B. Morrow, Trevor Manz, Arlene E. Chung, N. Gehlenborg, D. Gotz","doi":"10.1109/VISUAL.2019.8933582","DOIUrl":null,"url":null,"abstract":"Patterns in temporal data can often be found across different scales, such as days, weeks, and months, making effective visualization of time-based data challenging. Here we propose a new approach for providing focus and context in time-based charts to enable interpretation of patterns across time scales. Our approach employs a focus zone with a time and a second axis, that can either represent quantities or categories, as well as a set of adjacent periphery plots that can aggregate data along the time, value, or both dimensions. We present a framework for periphery plots and describe two use cases that demonstrate the utility of our approach.","PeriodicalId":192801,"journal":{"name":"2019 IEEE Visualization Conference (VIS)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Visualization Conference (VIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VISUAL.2019.8933582","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Patterns in temporal data can often be found across different scales, such as days, weeks, and months, making effective visualization of time-based data challenging. Here we propose a new approach for providing focus and context in time-based charts to enable interpretation of patterns across time scales. Our approach employs a focus zone with a time and a second axis, that can either represent quantities or categories, as well as a set of adjacent periphery plots that can aggregate data along the time, value, or both dimensions. We present a framework for periphery plots and describe two use cases that demonstrate the utility of our approach.