M. Balazinska, S. Davidson, Bill Howe, Alexandros Labrinidis
{"title":"数据科学家的教育和职业道路","authors":"M. Balazinska, S. Davidson, Bill Howe, Alexandros Labrinidis","doi":"10.1145/2484838.2484886","DOIUrl":null,"url":null,"abstract":"MOTIVATION: As industry and science are increasingly data-driven, the need for skilled data scientists is exceeding what our universities are producing. According to a Mckinsey report: \"By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills\". Similarly, the ability to extract knowledge from scientific data is accelerating discovery and we need the next generation of domain scientists to be experts not only in their domain but also in data management. At the same time, however, researchers in academia who focus on building instruments or data management tools are often less recognized for their contributions than researchers focusing purely on the actual science.\n OVERVIEW: The goal of this panel will be to discuss all these challenges. We will discuss various aspects of how we should be educating both the emerging \"data science\" experts and the next generation of database and domain science experts. The panel will also discuss career paths for researchers who choose to specialize in developing new methods and tools for Big Data management in domain sciences, with recommendations for how we should better support these less traditional career paths.","PeriodicalId":74773,"journal":{"name":"Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management","volume":"82 1","pages":"3:1-3:2"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Education and career paths for data scientists\",\"authors\":\"M. Balazinska, S. Davidson, Bill Howe, Alexandros Labrinidis\",\"doi\":\"10.1145/2484838.2484886\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"MOTIVATION: As industry and science are increasingly data-driven, the need for skilled data scientists is exceeding what our universities are producing. According to a Mckinsey report: \\\"By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills\\\". Similarly, the ability to extract knowledge from scientific data is accelerating discovery and we need the next generation of domain scientists to be experts not only in their domain but also in data management. At the same time, however, researchers in academia who focus on building instruments or data management tools are often less recognized for their contributions than researchers focusing purely on the actual science.\\n OVERVIEW: The goal of this panel will be to discuss all these challenges. We will discuss various aspects of how we should be educating both the emerging \\\"data science\\\" experts and the next generation of database and domain science experts. The panel will also discuss career paths for researchers who choose to specialize in developing new methods and tools for Big Data management in domain sciences, with recommendations for how we should better support these less traditional career paths.\",\"PeriodicalId\":74773,\"journal\":{\"name\":\"Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management\",\"volume\":\"82 1\",\"pages\":\"3:1-3:2\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2484838.2484886\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2484838.2484886","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MOTIVATION: As industry and science are increasingly data-driven, the need for skilled data scientists is exceeding what our universities are producing. According to a Mckinsey report: "By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills". Similarly, the ability to extract knowledge from scientific data is accelerating discovery and we need the next generation of domain scientists to be experts not only in their domain but also in data management. At the same time, however, researchers in academia who focus on building instruments or data management tools are often less recognized for their contributions than researchers focusing purely on the actual science.
OVERVIEW: The goal of this panel will be to discuss all these challenges. We will discuss various aspects of how we should be educating both the emerging "data science" experts and the next generation of database and domain science experts. The panel will also discuss career paths for researchers who choose to specialize in developing new methods and tools for Big Data management in domain sciences, with recommendations for how we should better support these less traditional career paths.