Schema.org Ontology (SchemaOrg)¶
Schema.org is a collaborative, community-driven initiative that provides a shared vocabulary for structured data markup on the web, in email messages, and beyond [1] [2]. It enables webmasters, content creators, and developers to annotate digital resources with machine-readable semantic information that can be used by search engines and other applications [1].
Schema.org provides extensible schemas for describing entities, relationships, and actions across many domains, including people, organizations, places, products, events, creative works, publications, health and medical information, and other web resources [1]. The vocabulary can be expressed using formats such as JSON-LD, RDFa, and Microdata, making it flexible for different publishing and data integration scenarios [1] [2].
Schema.org is designed for broad applicability across industries while also supporting extension mechanisms for more specialized use cases [1]. Its markup is widely used by publishers and consumed by major web applications to support structured data exchange, enhanced search experiences, knowledge graph construction, content discovery, and interoperability across web-based services [2].
Example Usage: Annotate a restaurant website with Schema.org terms such as Organization, LocalBusiness, address, openingHours, telephone, and AggregateRating. This allows search engines and other applications to understand the restaurant’s location, contact details, opening hours, and review information, supporting richer search results and improved resource discovery [1] [2].
Metrics & Statistics¶
Total Nodes |
15044 |
Total Edges |
32425 |
Root Nodes |
0 |
Leaf Nodes |
2128 |
Classes |
3881 |
Individuals |
0 |
Properties |
1485 |
Maximum Depth |
0 |
Minimum Depth |
0 |
Average Depth |
0.00 |
Depth Variance |
0.00 |
Maximum Breadth |
0 |
Minimum Breadth |
0 |
Average Breadth |
0.00 |
Breadth Variance |
0.00 |
Term Types |
0 |
Taxonomic Relations |
1058 |
Non-taxonomic Relations |
635 |
Average Terms per Type |
0.00 |
Usage Example¶
Use the following code to import this ontology programmatically:
from ontolearner.ontology import SchemaOrg
ontology = SchemaOrg()
ontology.load("path/to/SchemaOrg-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