R. Machiraju, Chris R. Johnson, T. Yoo, R. Crawfis, D. Ebert, D. Stredney
{"title":"我真的看到骨头了吗?","authors":"R. Machiraju, Chris R. Johnson, T. Yoo, R. Crawfis, D. Ebert, D. Stredney","doi":"10.1109/VISUAL.2003.1250429","DOIUrl":null,"url":null,"abstract":"Raw data from scanners and simulations has insight embedded within it. However, there is a need to explicitly glean the insight from the data or a version of it. Visualization algorithms and methods are designed just to do that. What insight is to be gleaned depends on the data, its use, and the medium of display. Thus, visualization embodies all tasks that increase information content and understanding when presented to the users.","PeriodicalId":372131,"journal":{"name":"IEEE Visualization, 2003. VIS 2003.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Do I really see a bone?\",\"authors\":\"R. Machiraju, Chris R. Johnson, T. Yoo, R. Crawfis, D. Ebert, D. Stredney\",\"doi\":\"10.1109/VISUAL.2003.1250429\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Raw data from scanners and simulations has insight embedded within it. However, there is a need to explicitly glean the insight from the data or a version of it. Visualization algorithms and methods are designed just to do that. What insight is to be gleaned depends on the data, its use, and the medium of display. Thus, visualization embodies all tasks that increase information content and understanding when presented to the users.\",\"PeriodicalId\":372131,\"journal\":{\"name\":\"IEEE Visualization, 2003. VIS 2003.\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-10-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Visualization, 2003. VIS 2003.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VISUAL.2003.1250429\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Visualization, 2003. VIS 2003.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VISUAL.2003.1250429","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Raw data from scanners and simulations has insight embedded within it. However, there is a need to explicitly glean the insight from the data or a version of it. Visualization algorithms and methods are designed just to do that. What insight is to be gleaned depends on the data, its use, and the medium of display. Thus, visualization embodies all tasks that increase information content and understanding when presented to the users.