WorldKG: A World-Scale Geographic Knowledge Graph

TL;DR

WorldKG is a comprehensive geographic knowledge graph derived from OpenStreetMap, providing a high-precision semantic representation of diverse geographic entities to facilitate real-world applications.

Contribution

This paper introduces WorldKG, a novel semantic geographic knowledge graph with an ontology, extraction methods, and annotation enhancements for improved geographic data usability.

Findings

Large scale and high precision geographic dataset

Effective ontology and extraction procedures

Enhanced entity annotation methods

Abstract

OpenStreetMap is a rich source of openly available geographic information. However, the representation of geographic entities, e.g., buildings, mountains, and cities, within OpenStreetMap is highly heterogeneous, diverse, and incomplete. As a result, this rich data source is hardly usable for real-world applications. This paper presents WorldKG -- a new geographic knowledge graph aiming to provide a comprehensive semantic representation of geographic entities in OpenStreetMap. We describe the WorldKG knowledge graph, including its ontology that builds the semantic dataset backbone, the extraction procedure of the ontology and geographic entities from OpenStreetMap, and the methods to enhance entity annotation. We perform statistical and qualitative dataset assessment, demonstrating the large scale and high precision of the semantic geographic information in WorldKG.