Suggested Upper Merged Ontology (SUMO)

The Suggested Upper Merged Ontology (SUMO) is one of the largest and most widely used formal upper ontologies, providing a comprehensive framework for representing general concepts and relationships across many domains of knowledge [1] [2]. SUMO and its domain ontologies are used for research and applications in search, linguistics, automated reasoning, semantic interoperability, and artificial intelligence [2]. The ontology covers abstract and concrete entities, processes, attributes, relations, and events, supporting logical inference and knowledge discovery [1] [2]. SUMO is open source and maintained through the Ontology Portal project, with ongoing extensions and domain-specific modules for specialized applications [1]. By providing a rigorous semantic foundation, SUMO facilitates interoperability, data integration, and advanced reasoning in knowledge-based systems [2].

Example Usage: Use SUMO as an upper ontology for a domain knowledge graph, mapping domain entities such as Vehicle, Process, Agent, or Communication to SUMO classes and relations. This enables logical reasoning, semantic search, knowledge discovery, and integration across heterogeneous knowledge-based systems [1] [2].

Metrics & Statistics

Graph Statistics

Total Nodes

288016

Total Edges

496645

Root Nodes

77015

Leaf Nodes

197102

Knowledge Coverage Statistics

Classes

4525

Individuals

80034

Properties

587

Hierarchical Metrics

Maximum Depth

9

Minimum Depth

0

Average Depth

1.04

Depth Variance

1.39

Breadth Metrics

Maximum Breadth

77015

Minimum Breadth

10

Average Breadth

19045.20

Breadth Variance

739917637.16

LLMs4OL Dataset Statistics

Term Types

80280

Taxonomic Relations

7174

Non-taxonomic Relations

310

Average Terms per Type

165.53

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import SUMO

ontology = SUMO()
ontology.load("path/to/SUMO-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

References