{"title":"视觉质量指标","authors":"E. Bertini, G. Santucci","doi":"10.1145/1168149.1168159","DOIUrl":null,"url":null,"abstract":"The definition and usage of quality metrics for Information Visualization techniques is still an immature field. Several proposals are available but a common view and understanding of this issue is still missing. This paper attempts a first step toward a visual quality metrics systematization, providing a general classification of both metrics and usage purposes. Moreover, the paper explores a quite neglected class of visual quality metrics, namely Feature Preservation Metrics, that allow for evaluating and improving in a novel way the effectiveness of basic Infovis techniques.","PeriodicalId":235801,"journal":{"name":"Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":"{\"title\":\"Visual quality metrics\",\"authors\":\"E. Bertini, G. Santucci\",\"doi\":\"10.1145/1168149.1168159\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The definition and usage of quality metrics for Information Visualization techniques is still an immature field. Several proposals are available but a common view and understanding of this issue is still missing. This paper attempts a first step toward a visual quality metrics systematization, providing a general classification of both metrics and usage purposes. Moreover, the paper explores a quite neglected class of visual quality metrics, namely Feature Preservation Metrics, that allow for evaluating and improving in a novel way the effectiveness of basic Infovis techniques.\",\"PeriodicalId\":235801,\"journal\":{\"name\":\"Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"33\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1168149.1168159\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1168149.1168159","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The definition and usage of quality metrics for Information Visualization techniques is still an immature field. Several proposals are available but a common view and understanding of this issue is still missing. This paper attempts a first step toward a visual quality metrics systematization, providing a general classification of both metrics and usage purposes. Moreover, the paper explores a quite neglected class of visual quality metrics, namely Feature Preservation Metrics, that allow for evaluating and improving in a novel way the effectiveness of basic Infovis techniques.