Spatio-temporal graph data storage and calculation based on grid graph database
Bing Han, Tengteng Qu, Yuhao Huo, Guoyi Sun, Ruoyi Feng, Xiaochong Tong · International Journal of Digital Earth · 2025
How to store and calculate knowledge graph data is an important research direction in database management. As the fundamental elements of spatio-temporal knowledge graph (STKG), spatio-temporal graph data are characterized by large amounts of data, heterogeneous types, and strong sparsity, making them difficult to effectively express in the widely used key-value databases and graph databases. This paper proposes a grid graph database (GGD) to store and manage spatio-temporal graph data. Through the Geographic Coordination Subdivision Grid with One-Dimensional Integrated Coding on a 2n Tree (GeoSOT), GGD constructs a retrieval system for five types of child-tables, utilizing temporal and spatial grid codes to precisely identify and position the storage of spatio-temporal quadruplets. With the use of grid coding algebra, GGD can also calculate complex spatio-temporal relations and generate new quadruplets to answer dynamic spatio-temporal questions. Experimental results show that, compared with other databases, GGD has significantly higher query and calculation efficiency levels for spatio-temporal graph data, with an average improvement of 4–10 times. Moreover, spatially distributed parallel optimization-based strategy can further improve the speeds of large-scale spatio-temporal graph data calculations, confirming the high scalability and practicality of GGD.