1 Center for Life Nano Sciences at La Sapienza , Istituto Italiano di Tecnologia , viale R. Margherita , 265 , 00161 , Roma , Italy.
2 Institute for Applied Computational Science , J. Paulson School of Engineering and Applied Sciences , Harvard University , 29 Oxford Street , Cambridge , USA.
Philos Trans A Math Phys Eng Sci. 2019 Apr 8;377(2142):20180145. doi: 10.1098/rsta.2018.0145.
For it is not the abundance of knowledge, but the interior feeling and taste of things, which is accustomed to satisfy the desire of the soul. (Saint Ignatius of Loyola). 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'.
因为习惯满足灵魂欲望的，不是知识的丰富，而是对事物的内在感觉和品味。（圣依纳爵·罗耀拉）。我们认为，鉴于从复杂系统科学中吸取的一些基本经验教训，大数据（BD）最激进的主张需要加以修正和淡化。我们指出，一旦正确地摒弃了 BD 的最夸大的主张，BD 与大理论的协同融合就有可能产生一个新的科学范式，克服现代科学方法（源于伽利略）所面临的一些主要障碍。这些障碍是由于非线性、非局部性和高维性的存在，在复杂系统的多尺度建模中经常会遇到这些问题。本文是“多尺度建模、模拟和计算：从桌面到 exascale”主题的一部分。
