From big data to important information

被引:33
|
作者
Bar-Yam, Yaneer [1 ]
机构
[1] New England Complex Syst Inst, 210 Broadway,Suite 101, Cambridge, MA 02139 USA
关键词
big data; information theory; renormalization group; GENETIC DIVERSITY; GLOBAL PATTERNS; CRITICAL-POINTS; EVOLUTION; MODEL; DYNAMICS; SYSTEMS; RANGE; SPECIATION; RESPONSES;
D O I
10.1002/cplx.21785
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Advances in science are being sought in newly available opportunities to collect massive quantities of data about complex systems. While key advances are being made in detailed mapping of systems, how to relate these data to solving many of the challenges facing humanity is unclear. The questions we often wish to address require identifying the impact of interventions on the system and that impact is not apparent in the detailed data that is available. Here, we review key concepts and motivate a general framework for building larger scale views of complex systems and for characterizing the importance of information in physical, biological, and social systems. We provide examples of its application to evolutionary biology with relevance to ecology, biodiversity, pandemics, and human lifespan, and in the context of social systems with relevance to ethnic violence, global food prices, and stock market panic. Framing scientific inquiry as an effort to determine what is important and unimportant is a means for advancing our understanding and addressing many practical concerns, such as economic development or treating disease. (c) 2016 Wiley Periodicals, Inc. Complexity 21: 73-98, 2016
引用
收藏
页码:73 / 98
页数:26
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