GeoNames Ontology (GeoNames)

The GeoNames Ontology provides a structured vocabulary and semantic framework for describing geographical features, places, and administrative regions, particularly those defined in the geonames.org database. It enables the representation of place names, geographic coordinates, feature types (such as cities, rivers, mountains), and hierarchical relationships between locations (e.g., country, state, city). The ontology supports multilingual place names and alternative spellings, facilitating global interoperability and data integration. GeoNames is widely used in geographic information systems (GIS), linked data applications, and knowledge graphs to enable geospatial search, mapping, and data enrichment. By providing standardized identifiers and relationships, GeoNames enhances the discoverability and linking of geographic data across datasets and platforms. The ontology is maintained collaboratively and is continuously updated to reflect changes in geographic information and administrative boundaries.

Example Usage: Annotate a dataset of cultural heritage sites with GeoNames terms to specify their geographic coordinates, administrative regions, and feature types, enabling geospatial search and integration with mapping services.

Metrics & Statistics

Graph Statistics

Total Nodes

4879

Total Edges

6631

Root Nodes

2

Leaf Nodes

4123
Knowledge Coverage Statistics

Classes

7

Individuals

699

Properties

30
Hierarchical Metrics

Maximum Depth

3

Minimum Depth

0

Average Depth

1.18

Depth Variance

0.43
Breadth Metrics

Maximum Breadth

21

Minimum Breadth

2

Average Breadth

7.00

Breadth Variance

65.50
LLMs4OL Dataset Statistics

Term Types

699

Taxonomic Relations

18

Non-taxonomic Relations

0

Average Terms per Type

349.50

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import GeoNames

ontology = GeoNames()
ontology.load("path/to/GeoNames-ontology.rdf")

# Extract datasets
data = ontology.extract()

# Access specific relations
term_types = data.term_typings
taxonomic_relations = data.type_taxonomies
non_taxonomic_relations = data.type_non_taxonomic_relations