Big Data in Geophysics and Other Earth Sciences

Abstract—The term “Big Data” has become very popular over the past decade. The frequency of its use in the research papers, reports, and broad press has been steadily increasing. This work describes the origin and development of the theory and practice of Big Data as a scientific discipline, outlines the main characteristics and methods for Big Data processing and analysis, discusses the formalism and family of Big Data V-characteristics, and presents the examples of the sources of the growing Big Data which have fundamental effect on the development of geophysics and related Earth sciences. The examples of the sources of Big Data in the Earth sciences are remote sensing, meteorology, geoecology (in terms of the global hierarchical network SMEAR (Stations Measuring Earth surfaces and Atmosphere Relations)), and seismic exploration. Besides, we discuss seismic monitoring data which can become Big Data when combined with other geophysical information and consider geomagnetic data which are not Big Data but nevertheless have a great scientific value.