{"title":"SpringView: radviz和并行坐标的合作,用于视图优化和减少杂波","authors":"E. Bertini, L. Dell'Aquila, G. Santucci","doi":"10.1109/CMV.2005.17","DOIUrl":null,"url":null,"abstract":"In this paper we integrate radviz and parallel coordinates, two methods able to handle multidimensional datasets, exploiting their contrasting characteristics. From on side radviz offers good direct data manipulation (i.e., brushing) techniques and low cluttering but it fails in providing visualization of quantitative information; conversely, parallel coordinates clearly shows the values of data attributes and their ranges but suffers from high cluttering also on small datasets and presents tedious manipulation techniques. We developed a prototype, called SpringView, that allows for simultaneously viewing both radviz and parallel coordinates and implements several useful techniques to manipulate the data, both interactively and, more interestingly, automatically. We challenged our approach against two well know multidimensional datasets, proving its effectiveness.","PeriodicalId":153029,"journal":{"name":"Coordinated and Multiple Views in Exploratory Visualization (CMV'05)","volume":"66 7","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"44","resultStr":"{\"title\":\"SpringView: cooperation of radviz and parallel coordinates for view optimization and clutter reduction\",\"authors\":\"E. Bertini, L. Dell'Aquila, G. Santucci\",\"doi\":\"10.1109/CMV.2005.17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we integrate radviz and parallel coordinates, two methods able to handle multidimensional datasets, exploiting their contrasting characteristics. From on side radviz offers good direct data manipulation (i.e., brushing) techniques and low cluttering but it fails in providing visualization of quantitative information; conversely, parallel coordinates clearly shows the values of data attributes and their ranges but suffers from high cluttering also on small datasets and presents tedious manipulation techniques. We developed a prototype, called SpringView, that allows for simultaneously viewing both radviz and parallel coordinates and implements several useful techniques to manipulate the data, both interactively and, more interestingly, automatically. We challenged our approach against two well know multidimensional datasets, proving its effectiveness.\",\"PeriodicalId\":153029,\"journal\":{\"name\":\"Coordinated and Multiple Views in Exploratory Visualization (CMV'05)\",\"volume\":\"66 7\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"44\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Coordinated and Multiple Views in Exploratory Visualization (CMV'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CMV.2005.17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Coordinated and Multiple Views in Exploratory Visualization (CMV'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CMV.2005.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SpringView: cooperation of radviz and parallel coordinates for view optimization and clutter reduction
In this paper we integrate radviz and parallel coordinates, two methods able to handle multidimensional datasets, exploiting their contrasting characteristics. From on side radviz offers good direct data manipulation (i.e., brushing) techniques and low cluttering but it fails in providing visualization of quantitative information; conversely, parallel coordinates clearly shows the values of data attributes and their ranges but suffers from high cluttering also on small datasets and presents tedious manipulation techniques. We developed a prototype, called SpringView, that allows for simultaneously viewing both radviz and parallel coordinates and implements several useful techniques to manipulate the data, both interactively and, more interestingly, automatically. We challenged our approach against two well know multidimensional datasets, proving its effectiveness.