Geographical Entities Ontology (GEO)¶
The Geographical Entities Ontology (GEO) provides a comprehensive inventory and formal representation of geopolitical and geographical entities, including sovereign states, administrative subdivisions, and various geographical regions [1] [1]. GEO distinguishes between political entities, such as countries, provinces, and cities, and the territorial or regional entities associated with them, enabling precise semantic representation of geographic and geopolitical concepts [1]. The ontology uses hierarchical relationships to model administrative subdivisions and political jurisdictions at multiple levels, including national, state, regional, and local levels [1] [1]. GEO facilitates location-aware data annotation, enabling applications in geopolitical analysis, administrative reporting, and location-based services to unambiguously identify geographic and political entities [1]. The ontology is designed for integration with other geographic and spatial ontologies, supporting linked data applications in geography, governance, and international relations [1].
Example Usage: Annotate a political news article with GEO terms such as France as a sovereign state, linked to subdivisions such as Île-de-France and Paris as administrative entities, to enable geographic and political context discovery [1] [1].
Metrics & Statistics¶
Total Nodes |
108572 |
Total Edges |
246406 |
Root Nodes |
298 |
Leaf Nodes |
54170 |
Classes |
397 |
Individuals |
46948 |
Properties |
75 |
Maximum Depth |
13 |
Minimum Depth |
0 |
Average Depth |
1.91 |
Depth Variance |
3.77 |
Maximum Breadth |
356 |
Minimum Breadth |
2 |
Average Breadth |
95.79 |
Breadth Variance |
17126.60 |
Term Types |
34653 |
Taxonomic Relations |
430 |
Non-taxonomic Relations |
19 |
Average Terms per Type |
1386.12 |
Usage Example¶
Use the following code to import this ontology programmatically:
from ontolearner.ontology import GEO
ontology = GEO()
ontology.load("path/to/GEO-ontology.owl")
# 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