Geospatial Knowledge Graphs

Geospatial Knowledge Graphs (GeoKGs) organize geospatial data and knowledge into graph structures, in which entities like places and events serve as nodes and their relationships form the edges. They are complemented with expressive metadata in the form of ontologies defining concepts (classes) and their relationships (properties). This structure underpins the powerful capabilities of GeoKGs in addressing challenges such as data integration, retrieval, and knowledge formalization. This entry first introduces the fundamentals of knowledge graphs, focusing on their implementation via Semantic Web technologies. It then explores GeoKGs, covering their advantages, relevant techniques, prominent examples, and a few key application areas. The entry concludes with an outlook on emerging trends, underscoring the convergence of machine learning and GeoKGs as a promising avenue for Geospatial Artificial Intelligence (GeoAI).