{"title":"使用广义重心坐标框架提高上下文数据布局的保真度","authors":"Shenghui Cheng, K. Mueller","doi":"10.1109/PACIFICVIS.2015.7156390","DOIUrl":null,"url":null,"abstract":"Contextual layouts preserve the context of the data with the associated attributes (variables). However, their linear mapping causes errors in the layout - similar data points and variable nodes may not map to similar regions, and vice versa. In this paper, we first unify the various data layout schemes and choose the Generalized Bary-centric Coordinates (GBC) plot as the standard way to describe them. Second, we propose three algorithms - distance spaced lay-out, iterative error reduction, and force directed adjustment - to reduce the layout error of variables to variables, data to variables and data to data, respectively. We find that the combination of these three algorithms can yield large improvements in the layout error and so achieve a more comprehensive layout. Third, we describe an interface, the GBC Error Explorer, which allows users to explore the error using a variety of visualization schemes combined with some interactions.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Improving the fidelity of contextual data layouts using a Generalized Barycentric Coordinates framework\",\"authors\":\"Shenghui Cheng, K. Mueller\",\"doi\":\"10.1109/PACIFICVIS.2015.7156390\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Contextual layouts preserve the context of the data with the associated attributes (variables). However, their linear mapping causes errors in the layout - similar data points and variable nodes may not map to similar regions, and vice versa. In this paper, we first unify the various data layout schemes and choose the Generalized Bary-centric Coordinates (GBC) plot as the standard way to describe them. Second, we propose three algorithms - distance spaced lay-out, iterative error reduction, and force directed adjustment - to reduce the layout error of variables to variables, data to variables and data to data, respectively. We find that the combination of these three algorithms can yield large improvements in the layout error and so achieve a more comprehensive layout. Third, we describe an interface, the GBC Error Explorer, which allows users to explore the error using a variety of visualization schemes combined with some interactions.\",\"PeriodicalId\":177381,\"journal\":{\"name\":\"2015 IEEE Pacific Visualization Symposium (PacificVis)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Pacific Visualization Symposium (PacificVis)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PACIFICVIS.2015.7156390\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Pacific Visualization Symposium (PacificVis)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACIFICVIS.2015.7156390","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving the fidelity of contextual data layouts using a Generalized Barycentric Coordinates framework
Contextual layouts preserve the context of the data with the associated attributes (variables). However, their linear mapping causes errors in the layout - similar data points and variable nodes may not map to similar regions, and vice versa. In this paper, we first unify the various data layout schemes and choose the Generalized Bary-centric Coordinates (GBC) plot as the standard way to describe them. Second, we propose three algorithms - distance spaced lay-out, iterative error reduction, and force directed adjustment - to reduce the layout error of variables to variables, data to variables and data to data, respectively. We find that the combination of these three algorithms can yield large improvements in the layout error and so achieve a more comprehensive layout. Third, we describe an interface, the GBC Error Explorer, which allows users to explore the error using a variety of visualization schemes combined with some interactions.