Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1126/science.aal4217 |
Data-driven predictions in the science of science | |
Clauset, Aaron1,2,3; Larremore, Daniel B.3; Sinatra, Roberta4,5,6,7 | |
2017-02-03 | |
发表期刊 | SCIENCE |
ISSN | 0036-8075 |
EISSN | 1095-9203 |
出版年 | 2017 |
卷号 | 355期号:6324页码:477-480 |
文章类型 | Editorial Material |
语种 | 英语 |
国家 | USA; Hungary |
英文摘要 | The desire to predict discoveries-to have some idea, in advance, of what will be discovered, by whom, when, and where-pervades nearly all aspects of modern science, from individual scientists to publishers, from funding agencies to hiring committees. In this Essay, we survey the emerging and interdisciplinary field of the "science of science" and what it teaches us about the predictability of scientific discovery. We then discuss future opportunities for improving predictions derived from the science of science and its potential impact, positive and negative, on the scientific community. |
领域 | 地球科学 ; 气候变化 ; 资源环境 |
收录类别 | SCI-E ; SSCI |
WOS记录号 | WOS:000393183100032 |
WOS关键词 | SLEEPING BEAUTIES ; IMPACT |
WOS类目 | Multidisciplinary Sciences |
WOS研究方向 | Science & Technology - Other Topics |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/195347 |
专题 | 地球科学 资源环境科学 气候变化 |
作者单位 | 1.Univ Colorado, Dept Comp Sci, Boulder, CO 80309 USA; 2.Univ Colorado, BioFrontiers Inst, Boulder, CO 80309 USA; 3.Santa Fe Inst, Santa Fe, NM 87501 USA; 4.Cent European Univ, Ctr Network Sci, Budapest, Hungary; 5.Cent European Univ, Dept Math, Budapest, Hungary; 6.Northeastern Univ, Ctr Complex Network Res, Boston, MA 02115 USA; 7.Northeastern Univ, Dept Phys, Boston, MA 02115 USA |
推荐引用方式 GB/T 7714 | Clauset, Aaron,Larremore, Daniel B.,Sinatra, Roberta. Data-driven predictions in the science of science[J]. SCIENCE,2017,355(6324):477-480. |
APA | Clauset, Aaron,Larremore, Daniel B.,&Sinatra, Roberta.(2017).Data-driven predictions in the science of science.SCIENCE,355(6324),477-480. |
MLA | Clauset, Aaron,et al."Data-driven predictions in the science of science".SCIENCE 355.6324(2017):477-480. |
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