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A Data Cube Metamodel for Geographic Analysis Involving Heterogeneous Dimensions
2021
ISPRS International Journal of Geo-Information
Due to their multiple sources and structures, big spatial data require adapted tools to be efficiently collected, summarized and analyzed. For this purpose, data are archived in data warehouses and explored by spatial online analytical processing (SOLAP) through dynamic maps, charts and tables. Data are thus converted in data cubes characterized by a multidimensional structure on which exploration is based. However, multiple sources often lead to several data cubes defined by heterogeneous
doi:10.3390/ijgi10020087
fatcat:fxqcduvxzzap3pjksyvre2usxu