Juso Ontology (Juso)

The Juso Ontology is a Web vocabulary for describing geographical addresses and geographical features using machine-readable semantic annotations [1] [2]. It provides a structured framework for representing core geographic and address-related concepts, including spatial things, features, geometries, points, addresses, names, official names, alternate names, and containment relationships [2]. Juso also defines address components such as full address, country, postal code, and multiple levels of administrative divisions, enabling more standardized representation of addresses across geographic datasets [2]. The ontology supports semantic description of political and administrative divisions, including countries, provinces, counties, municipalities, districts, towns, townships, neighborhoods, villages, and related regional units [2]. By providing explicit classes and properties for addresses, geographic features, and administrative hierarchies, Juso can support geocoding, location-based services, address validation, geographic lookup, and linked data integration [1] [2]. Juso can also be connected with broader geographic and web vocabularies through linked-data relationships, helping address information interoperate with geographic entities and spatial contexts [2].

Example Usage: Represent a complete address as a Juso address instance with properties for street name, building number, postal code, city, administrative division, and country, enabling automated address validation, geographic lookup, and integration with location-based services [1] [2]. Metrics & Statistics ————————–

Graph Statistics

Total Nodes

319

Total Edges

607

Root Nodes

19

Leaf Nodes

227

Knowledge Coverage Statistics

Classes

30

Individuals

0

Properties

24

Hierarchical Metrics

Maximum Depth

5

Minimum Depth

0

Average Depth

1.93

Depth Variance

1.85

Breadth Metrics

Maximum Breadth

37

Minimum Breadth

4

Average Breadth

21.33

Breadth Variance

132.89

LLMs4OL Dataset Statistics

Term Types

0

Taxonomic Relations

61

Non-taxonomic Relations

2

Average Terms per Type

0.00

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import Juso

ontology = Juso()
ontology.load("path/to/Juso-ontology.ttl")

# 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

References