A Planet Scale Spatial-Temporal Knowledge Graph Based On OpenStreetMap And H3 Grid
This work addresses the need for interconnected geospatial representations for applications relying on spatial data, but it appears incremental as it builds on existing methods like OpenStreetMap and H3 grids.
The paper tackles the problem of representing geospatial data by proposing a framework to transform OpenStreetMap data into a planet-scale spatial-temporal knowledge graph using H3 grid alignment, and it compares this graph to others without specifying concrete numerical results.
Geospatial data plays a central role in modeling our world, for which OpenStreetMap (OSM) provides a rich source of such data. While often spatial data is represented in a tabular format, a graph based representation provides the possibility to interconnect entities which would have been separated in a tabular representation. We propose in our paper a framework which supports a planet scale transformation of OpenStreetMap data into a Spatial Temporal Knowledge Graph. In addition to OpenStreetMap data, we align the different OpenStreetMap geometries on individual h3 grid cells. We compare our constructed spatial knowledge graph to other spatial knowledge graphs and outline our contribution in this paper. As a basis for our computation, we use Apache Sedona as a computational framework for our Spatial Temporal Knowledge Graph construction