{"title":"重新定位大数据修辞","authors":"N. Verma","doi":"10.1145/2957276.2997027","DOIUrl":null,"url":null,"abstract":"Data analytics and BI (business intelligence) systems are the most prominent user-facing manifestation of 'big data' and the related computational turn in thinking within organizations. However, the big data mythologies-specifically that data can offer more accurate, objective and truthful forms of intelligence and knowledge-impact, reinforce, and reproduce certain epistemological biases. In my research, I study these big data technologies in human services related contexts to examine knowledge claims and the strengths and limitations of big data.","PeriodicalId":244100,"journal":{"name":"Proceedings of the 2016 ACM International Conference on Supporting Group Work","volume":"258 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Towards Re-Orienting the Big Data Rhetoric\",\"authors\":\"N. Verma\",\"doi\":\"10.1145/2957276.2997027\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data analytics and BI (business intelligence) systems are the most prominent user-facing manifestation of 'big data' and the related computational turn in thinking within organizations. However, the big data mythologies-specifically that data can offer more accurate, objective and truthful forms of intelligence and knowledge-impact, reinforce, and reproduce certain epistemological biases. In my research, I study these big data technologies in human services related contexts to examine knowledge claims and the strengths and limitations of big data.\",\"PeriodicalId\":244100,\"journal\":{\"name\":\"Proceedings of the 2016 ACM International Conference on Supporting Group Work\",\"volume\":\"258 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2016 ACM International Conference on Supporting Group Work\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2957276.2997027\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 ACM International Conference on Supporting Group Work","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2957276.2997027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data analytics and BI (business intelligence) systems are the most prominent user-facing manifestation of 'big data' and the related computational turn in thinking within organizations. However, the big data mythologies-specifically that data can offer more accurate, objective and truthful forms of intelligence and knowledge-impact, reinforce, and reproduce certain epistemological biases. In my research, I study these big data technologies in human services related contexts to examine knowledge claims and the strengths and limitations of big data.
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