# WorldKG: A World-Scale Geographic Knowledge Graph

arXiv: https://arxiv.org/abs/2109.10036 · HTML: https://mlsanity.com/paper/2109.10036/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Sep 2021.

## Built on by (most cited first, 11 of 11)

- [Construction of Knowledge Graphs: State and Challenges](https://mlsanity.com/paper/2302.11509/) (2023)
- [Self-Supervised Representation Learning for Geospatial Objects: A Survey](https://mlsanity.com/paper/2408.12133/) (2024)
- [Towards Interpretable Geo-localization: a Concept-Aware Global Image-GPS Alignment Framework](https://mlsanity.com/paper/2509.01910/) (2025)
- [Attention-Based Vandalism Detection in OpenStreetMap](https://mlsanity.com/paper/2201.10406/) (2022)
- [A Planet Scale Spatial-Temporal Knowledge Graph Based On OpenStreetMap And H3 Grid](https://mlsanity.com/paper/2405.15375/) (2024)
- [ASGM-KG: Unveiling Alluvial Gold Mining Through Knowledge Graphs](https://mlsanity.com/paper/2408.08972/) (2024)
- [Creating Knowledge Graphs for Geographic Data on the Web](https://mlsanity.com/paper/2302.08823/) (2023)
- [Linking Streets in OpenStreetMap to Persons in Wikidata](https://mlsanity.com/paper/2302.12907/) (2023)
- [Comprehensive Event Representations using Event Knowledge Graphs and Natural Language Processing](https://mlsanity.com/paper/2303.04794/) (2023)
- [GeoRDF2Vec Learning Location-Aware Entity Representations in Knowledge Graphs](https://mlsanity.com/paper/2504.17099/) (2025)
- [Efficient Identification of High Similarity Clusters in Polygon Datasets](https://mlsanity.com/paper/2509.23942/) (2025)

## Abstract (arXiv)

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.