{"title":"提高公民科学数据的质量和可信度","authors":"A. Alabri, J. Hunter","doi":"10.1109/ESCIENCE.2010.33","DOIUrl":null,"url":null,"abstract":"The Internet, Web 2.0 and Social Networking technologies are enabling citizens to actively participate in “citizen science” projects by contributing data to scientific programs. However, the limited expertise of contributors can lead to poor quality or misleading data being submitted. Subsequently, the scientific community often perceive citizen science data as not worthy of being used in serious scientific research. In this paper, we describe a technological framework that combines data quality improvements and trust metrics to enhance the reliability of citizen science data. We describe how trust models provide a simple and effective mechanism for measuring the reliability of community-generated data. We also describe filtering services that remove untrustworthy data, and enable confident re-use of the data. The resulting services are evaluated in the context of the Coral Watch project which uses volunteers to collect data on coral reef bleaching.","PeriodicalId":441488,"journal":{"name":"2010 IEEE Sixth International Conference on e-Science","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"74","resultStr":"{\"title\":\"Enhancing the Quality and Trust of Citizen Science Data\",\"authors\":\"A. Alabri, J. Hunter\",\"doi\":\"10.1109/ESCIENCE.2010.33\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Internet, Web 2.0 and Social Networking technologies are enabling citizens to actively participate in “citizen science” projects by contributing data to scientific programs. However, the limited expertise of contributors can lead to poor quality or misleading data being submitted. Subsequently, the scientific community often perceive citizen science data as not worthy of being used in serious scientific research. In this paper, we describe a technological framework that combines data quality improvements and trust metrics to enhance the reliability of citizen science data. We describe how trust models provide a simple and effective mechanism for measuring the reliability of community-generated data. We also describe filtering services that remove untrustworthy data, and enable confident re-use of the data. The resulting services are evaluated in the context of the Coral Watch project which uses volunteers to collect data on coral reef bleaching.\",\"PeriodicalId\":441488,\"journal\":{\"name\":\"2010 IEEE Sixth International Conference on e-Science\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"74\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE Sixth International Conference on e-Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ESCIENCE.2010.33\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Sixth International Conference on e-Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ESCIENCE.2010.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhancing the Quality and Trust of Citizen Science Data
The Internet, Web 2.0 and Social Networking technologies are enabling citizens to actively participate in “citizen science” projects by contributing data to scientific programs. However, the limited expertise of contributors can lead to poor quality or misleading data being submitted. Subsequently, the scientific community often perceive citizen science data as not worthy of being used in serious scientific research. In this paper, we describe a technological framework that combines data quality improvements and trust metrics to enhance the reliability of citizen science data. We describe how trust models provide a simple and effective mechanism for measuring the reliability of community-generated data. We also describe filtering services that remove untrustworthy data, and enable confident re-use of the data. The resulting services are evaluated in the context of the Coral Watch project which uses volunteers to collect data on coral reef bleaching.