| 大数据助地质腾飞:岩石学报2018第11期大数据专题“序” |
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| 引用本文： | 张旗,周永章.大数据助地质腾飞:岩石学报2018第11期大数据专题“序”[J].岩石学报,2018,34(11):3167-3172. |
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| 作者姓名： | 张旗 周永章 |
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| 作者单位： | 中国科学院地质与地球物理研究所, 北京 100029;自然资源部地质信息技术重点实验室, 北京 100037,中山大学地球科学与工程学院, 广州 510275 |
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| 基金项目： | 本文受国家重点研发计划重点专项项目（2016YFC0600510）、中地调研项目（2018-427）、国家自然科学基金重大研究计划项目（91014001）、中国科学院地质与地球物理研究所岩石圈演化国家重点实验室项目（81300001）、国家自然科学基金项目（41273040）、中国地质调查局项目（12120113067600）和广东省地质过程与矿产资源探查重点实验室基金联合资助. |
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| 摘 要： | 文中提出,大数据有广义与狭义之分:狭义的大数据以4V特点为标志,而符合大数据三个技术取向的、采用全数据模式的、从数据出发的研究是广义的大数据研究。大数据为什么应运而生?是因为科学发展遇到了瓶颈,遇到了难以解决的问题,大数据不仅开辟了科学研究的新方法,新思路,还引发了对科学哲学的反思。文中强调从理论驱动模式到数据驱动模式的转变,是研究方法和研究思路一个巨大的转变,这种转变开辟了新的科学创新之路。文中指出,在大数据时代,凡是能够用数据化表述的学科才称之为科学,而不能用数据化表述的学科就不是科学,能否被数据化是科学与非科学的分水岭。文中讨论了矿床学研究的目的,认为矿床学研究应当专注于查明矿床形成的规律,指导矿床的找矿,提高经济价值。提出在矿床学研究中应当加强对相关关系的研究。一个矿床的成因大家究竟是如何关注的,与成矿有关的因素很多,成矿究竟与哪些因素有关,在许多情况下可能就是一个相关关系的命题,而大数据研究的就是相关关系。因此,大数据与矿床学研究的思路是天然相通的。
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| 关 键 词： | 大数据 方法 地质学 矿床学 危机 |
| 收稿时间： | 2018/8/30 0:00:00 |
| 修稿时间： | 2018/10/5 0:00:00 |
Big data helps geology develop rapidly |
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| ZHANG Qi and ZHOU YongZhang.Big data helps geology develop rapidly[J].Acta Petrologica Sinica,2018,34(11):3167-3172. |
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| Authors: | ZHANG Qi and ZHOU YongZhang |
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| Institution: | Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China;Key Laboratory of Geologial Information Technology, Ministry of Natural Resources, Beijing 100037, China and School of Earth Sciences & Engineering, Sun Yat-sen University, Guangzhou 510275, China |
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| Abstract: | The paper proposes that big data has a broad and narrow sense:big data in the narrow sense is marked by the characteristics of 4V, and the data-based research that conforms to the three technology orientations of big data and adopts the full data model is a broad-based big data research. Why did big data come into being? It is because scientific development has encountered bottlenecks and encountered difficult problems. Big data has not only opened up new methods of scientific research, but also triggered new reflections on philosophy of science. This paper explores the difference between theoretically driven and data-driven models and the crisis facing geology and mineralogy in the era of big data. The paper emphasizes the transformation from the theoretical-driven model to the data-driven model. It is a huge transformation of research methods and research ideas. This transformation has opened up a new path of scientific innovation. The article points out that in the era of big data, any discipline that can be expressed in terms of data is called science and a discipline that cannot be expressed in terms of data is not science. Whether it can be digitized is a watershed between science and non-science. The purpose of the study of mineral deposits is discussed in this paper. It is believed that the study of mineral deposits should focus on identifying the law of deposit formation, guiding the prospecting of deposits and improving economic value. It is proposed that research on correlation should be strengthened in the study of mineral deposits. The cause of a deposit is everyone''s concern. There are many factors related to mineralization. What factors are related to mineralization? In many cases, it may be a proposition of correlation, while big data studies correlation. Therefore, the idea of big data and mineral deposit research is naturally connected. |
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| Keywords: | Big data Method Geology Mineral deposit Crisis |
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