{"title":"A characterization of the scientific data analysis process","authors":"R. Springmeyer, M. Blattner, N. Max","doi":"10.1109/VISUAL.1992.235203","DOIUrl":null,"url":null,"abstract":"It is shown how data visualization fits into the broader process of scientific data analysis. Scientists from several disciplines were observed while they analyzed their own data. Examination of the observations exposed process elements outside conventional image viewing. For example, analysts queried for quantitative information, made a variety of comparisons, applied math, managed data, and kept records. The characterization of scientific data analysis reveals activity beyond that traditionally supported by computer. It offers an understanding which has the potential to be applied to many future designs, and suggests specific recommendations for improving the support of this important aspect of scientific computing.<<ETX>>","PeriodicalId":164549,"journal":{"name":"Proceedings Visualization '92","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"139","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Visualization '92","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VISUAL.1992.235203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 139
Abstract
It is shown how data visualization fits into the broader process of scientific data analysis. Scientists from several disciplines were observed while they analyzed their own data. Examination of the observations exposed process elements outside conventional image viewing. For example, analysts queried for quantitative information, made a variety of comparisons, applied math, managed data, and kept records. The characterization of scientific data analysis reveals activity beyond that traditionally supported by computer. It offers an understanding which has the potential to be applied to many future designs, and suggests specific recommendations for improving the support of this important aspect of scientific computing.<>
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