1. 复旦大学计算机科学技术学院,上海 200433
2. 上海市数据科学重点实验室,上海 200433
[ "朱扬勇(1963-),男,博士,复旦大学计算机科学技术学院教授、学术委员会主任,上海市数据科学重点实验室主任。1989年起从事数据领域研究,2008年提出数据资源保护和利用,2009年发表了数据科学论文“Data explosion,data nature and dataology”,并出版专著《数据学》,对数据科学进行了系统探讨和描述。2010年创办了“International Workshop on Dataology and Data Science”,2014年和石勇、张成奇共同创办了“International Conference on Data Science”。担任第462次香山科学会议“数据科学与大数据的理论问题探索”的执行主席、《大数据技术与应用丛书》主编。目前主要研究方向为数据科学、大数据。" ]
[ "熊贇(1980-),女,博士,复旦大学计算机科学技术学院教授。2004年起从事数据领域方面的研究工作,作为项目负责人主持国家自然科学基金、上海市科委发展基金以及企业合作项目。相关研究成果在本领域国际权威期刊或会议发表论文30余篇,出版著作3本。目前主要研究方向为数据科学、大数据。" ]
网络首发:2016-09,
纸质出版:2016-09-20
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朱扬勇, 熊贇. 大数据人才培养的基础条件初探[J]. 大数据, 2016,2(5):2016059.
Yangyong ZHU, Yun XIONG. On prerequisites for cultivating big data talents[J]. Big data research, 2016, 2(5): 2016059.
朱扬勇, 熊贇. 大数据人才培养的基础条件初探[J]. 大数据, 2016,2(5):2016059. DOI: 10.11959/j.issn.2096-0271.2016059.
Yangyong ZHU, Yun XIONG. On prerequisites for cultivating big data talents[J]. Big data research, 2016, 2(5): 2016059. DOI: 10.11959/j.issn.2096-0271.2016059.
人才短缺是发展大数据的主要障碍,越来越多的大学启动了大数据人才培养计划。大数据人才培养的基础条件有哪些?首先要有师资,但这是一个矛盾的基础条件,人才短缺意味着师资更短缺;其次要有数据,且是“大”的数据,没有数据的人才培养是纸上谈兵;有了“大”数据,就需要相应的计算条件。探索了大数据人才培养所需的师资、数据和计算条件问题,提出超学科创新培养模式解决师资条件问题、建立大数据试验场解决数据和计算条件问题。
The shortage of big data talents becomes a global concern
which restricts the development of big data.Cultivating big data talents has been paid attention widely and increasing universities have launched big data talents training plans.It is important and necessary to discuss the prerequisites for cultivating big data talents
including qualified teachers
data resources
computing capabilities.Building qualified teachers team is the first element.It is impossible to discuss cultivating talents if there is no qualified teacher.However
this is a contradiction
because the shortage of big data talents means the shortage of the qualified teachers for big data training.The second one is data resource
especially big data.If there is no data
the big data talents training will not make sense.Correspondingly
the third one is computation capability for big data.Three main prerequisites for big data talents training were discussed including qualified teachers
data resources and computation capabilities.Two solutions were presented:one was to develop an innovation talents training pattern
namely transdisciplinary
for the shortage of qualified teachers
the other was to establish big data arena for innovation and advance to supply the data resource and computation capability.
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