J. Woodring, J. Ahrens, J. Patchett, C. Tauxe, D. Rogers
{"title":"通过电影探索高维科学数据","authors":"J. Woodring, J. Ahrens, J. Patchett, C. Tauxe, D. Rogers","doi":"10.1109/DSIA.2017.8339086","DOIUrl":null,"url":null,"abstract":"Large-scale scientific simulations and experiments generate enormous volumes of data. Data analytics may become a bottleneck to scientific discovery without scalable tools for interactive exploration. Cinema was developed as a way to overcome hurdles by providing an exploratory, image database approach for analyzing large scientific data sets. In the following, we present several new methods for Cinema: 1) a structured data model that lends itself to querying and database support, 2) support for arbitrary data products beyond images, and 3) parameter exploration through high-dimensional visualization. These changes enrich the types of exporatory visualizations and discoveries that are naturally supported by Cinema-style analyses, further enabling data-driven science.","PeriodicalId":308968,"journal":{"name":"2017 IEEE Workshop on Data Systems for Interactive Analysis (DSIA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"High-dimensional scientific data exploration via cinema\",\"authors\":\"J. Woodring, J. Ahrens, J. Patchett, C. Tauxe, D. Rogers\",\"doi\":\"10.1109/DSIA.2017.8339086\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Large-scale scientific simulations and experiments generate enormous volumes of data. Data analytics may become a bottleneck to scientific discovery without scalable tools for interactive exploration. Cinema was developed as a way to overcome hurdles by providing an exploratory, image database approach for analyzing large scientific data sets. In the following, we present several new methods for Cinema: 1) a structured data model that lends itself to querying and database support, 2) support for arbitrary data products beyond images, and 3) parameter exploration through high-dimensional visualization. These changes enrich the types of exporatory visualizations and discoveries that are naturally supported by Cinema-style analyses, further enabling data-driven science.\",\"PeriodicalId\":308968,\"journal\":{\"name\":\"2017 IEEE Workshop on Data Systems for Interactive Analysis (DSIA)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Workshop on Data Systems for Interactive Analysis (DSIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DSIA.2017.8339086\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Workshop on Data Systems for Interactive Analysis (DSIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSIA.2017.8339086","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
High-dimensional scientific data exploration via cinema
Large-scale scientific simulations and experiments generate enormous volumes of data. Data analytics may become a bottleneck to scientific discovery without scalable tools for interactive exploration. Cinema was developed as a way to overcome hurdles by providing an exploratory, image database approach for analyzing large scientific data sets. In the following, we present several new methods for Cinema: 1) a structured data model that lends itself to querying and database support, 2) support for arbitrary data products beyond images, and 3) parameter exploration through high-dimensional visualization. These changes enrich the types of exporatory visualizations and discoveries that are naturally supported by Cinema-style analyses, further enabling data-driven science.