{"title":"综合数据和公共政策:用算法生成的数据支持现实世界的决策者","authors":"Kevin Jenkins","doi":"10.26686/pq.v19i2.8234","DOIUrl":null,"url":null,"abstract":"Good policy is best developed by drawing on a wide array of high-quality evidence. The rapid growth of data science and the emergence of big datasets has materially advanced the supply and use of quantitative evidence. However, some key constraints remain, including that available datasets are still not big enough for some analytical purposes. There are also privacy and data security risks. Synthetic data is an emerging area of data science that can potentially support policy decision making through enabling research to work faster and with fewer errors while also ensuring privacy and security.","PeriodicalId":43642,"journal":{"name":"Turkish Policy Quarterly","volume":"93 1","pages":""},"PeriodicalIF":0.1000,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Synthetic Data and Public Policy: supporting real-world policymakers with algorithmically generated data\",\"authors\":\"Kevin Jenkins\",\"doi\":\"10.26686/pq.v19i2.8234\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Good policy is best developed by drawing on a wide array of high-quality evidence. The rapid growth of data science and the emergence of big datasets has materially advanced the supply and use of quantitative evidence. However, some key constraints remain, including that available datasets are still not big enough for some analytical purposes. There are also privacy and data security risks. Synthetic data is an emerging area of data science that can potentially support policy decision making through enabling research to work faster and with fewer errors while also ensuring privacy and security.\",\"PeriodicalId\":43642,\"journal\":{\"name\":\"Turkish Policy Quarterly\",\"volume\":\"93 1\",\"pages\":\"\"},\"PeriodicalIF\":0.1000,\"publicationDate\":\"2023-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Turkish Policy Quarterly\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26686/pq.v19i2.8234\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"POLITICAL SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Turkish Policy Quarterly","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26686/pq.v19i2.8234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"POLITICAL SCIENCE","Score":null,"Total":0}
Synthetic Data and Public Policy: supporting real-world policymakers with algorithmically generated data
Good policy is best developed by drawing on a wide array of high-quality evidence. The rapid growth of data science and the emergence of big datasets has materially advanced the supply and use of quantitative evidence. However, some key constraints remain, including that available datasets are still not big enough for some analytical purposes. There are also privacy and data security risks. Synthetic data is an emerging area of data science that can potentially support policy decision making through enabling research to work faster and with fewer errors while also ensuring privacy and security.