{"title":"数据来源的研究问题","authors":"Chad Vicknair","doi":"10.1145/1900008.1900037","DOIUrl":null,"url":null,"abstract":"As the volume of scientific data increases, the need for automated data provenance has expanded. Currently, several provenance systems exist to aid users in recording and querying provenance data. They range from very specific programs designed to accomplish a small number of clearly defined tasks to broad-range applications intended to appeal to a wider audience. This paper discusses several provenance systems and describes some areas for future study.","PeriodicalId":333104,"journal":{"name":"ACM SE '10","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Research issues in data provenance\",\"authors\":\"Chad Vicknair\",\"doi\":\"10.1145/1900008.1900037\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the volume of scientific data increases, the need for automated data provenance has expanded. Currently, several provenance systems exist to aid users in recording and querying provenance data. They range from very specific programs designed to accomplish a small number of clearly defined tasks to broad-range applications intended to appeal to a wider audience. This paper discusses several provenance systems and describes some areas for future study.\",\"PeriodicalId\":333104,\"journal\":{\"name\":\"ACM SE '10\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM SE '10\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1900008.1900037\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SE '10","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1900008.1900037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
As the volume of scientific data increases, the need for automated data provenance has expanded. Currently, several provenance systems exist to aid users in recording and querying provenance data. They range from very specific programs designed to accomplish a small number of clearly defined tasks to broad-range applications intended to appeal to a wider audience. This paper discusses several provenance systems and describes some areas for future study.
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