Big spatial data modeling using data cube based on discrete global grid system

The authors describe an approach to modeling large volumes of heterogeneous spatial data in the form of a hypercube based on discrete global grid systems. Bibliometric analysis and literature review of academic publications, mapping and explanation of the scientific landscape on the subject of big data and data cubes in Earth sciences are carried out. The mentioned phenomenon is interpreted in Earth sciences in the view of the spatial data life cycle. The results show that its transformative impact on cartography and geoinformatics is mutual, and the resulting methodological problem is their heterogeneity, not volume. To model them, it is proposed to use a data cube in which the spatial dimension is represented using discrete global grid systems with advantages over raster and vector models in application to that phenomenon. The content of the data cube is analysis-ready information.