Big data: the end of the scientific method?
Big data: the end of the scientific method?
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DOI：
10.1098/rsta.2018.0145
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发表时间：
2019-04-08
期刊：
影响因子：
5
通讯作者：
Coveney, Peter V.
中科院分区：
文献类型：
--
作者：
Succi, Sauro;Coveney, Peter V.
我们认为，鉴于从复杂系统科学中吸取的一些基本教训，大数据（BD）的最大胆的主张需要修改和淡化。我们指出，一旦最奢侈的索赔BD被适当丢弃，BD与大理论的协同合并提供了相当大的潜力，产生一个新的科学范式，能够克服一些主要的障碍所面临的现代科学方法起源于伽利略。这些障碍是由于存在的非线性，非局部性和hyperdimensions，其中一个经常遇到的多尺度建模的复杂systems.This文章的主题问题的一部分“多尺度建模，模拟和计算：从桌面到exascale”。
We argue that the boldest claims of big data (BD) are in need of revision and toning-down, in view of a few basic lessons learned from the science of complex systems. We point out that, once the most extravagant claims of BD are properly discarded, a synergistic merging of BD with big theory offers considerable potential to spawn a new scientific paradigm capable of overcoming some of the major barriers confronted by the modern scientific method originating with Galileo. These obstacles are due to the presence of nonlinearity, non-locality and hyperdimensions which one encounters frequently in multi-scale modelling of complex systems.This article is part of the theme issue 'Multiscale modelling, simulation and computing: from the desktop to the exascale'.