Material Ontology (MatOnto)

The Material Ontology (MatOnto) is a domain ontology based on the Basic Formal Ontology (BFO) designed to provide a structured vocabulary for representing materials, their properties, and relationships in materials science and engineering. MatOnto supports semantic annotation of materials data, enabling interoperability, data integration, and advanced analysis across research databases, digital twins, and manufacturing systems. The ontology covers key concepts such as material types, compositions, processing methods, properties, and applications. MatOnto is designed for extensibility, allowing researchers and engineers to describe new materials, characterization techniques, and performance metrics. By providing a standardized framework, MatOnto facilitates cross-study comparison, materials selection, and knowledge sharing in materials research and industry. The ontology is actively maintained and extended to incorporate new materials, technologies, and research requirements.

Example Usage: Annotate a materials database with MatOnto terms to specify material types (e.g., polymer, alloy), composition, processing methods, and properties (e.g., tensile strength, thermal conductivity), enabling semantic search and integration with materials informatics platforms.

Metrics & Statistics

Graph Statistics

Total Nodes

4753

Total Edges

11287

Root Nodes

33

Leaf Nodes

1063
Knowledge Coverage Statistics

Classes

1307

Individuals

122

Properties

95
Hierarchical Metrics

Maximum Depth

129

Minimum Depth

0

Average Depth

38.24

Depth Variance

1437.88
Breadth Metrics

Maximum Breadth

155

Minimum Breadth

1

Average Breadth

18.92

Breadth Variance

522.53
LLMs4OL Dataset Statistics

Term Types

122

Taxonomic Relations

1215

Non-taxonomic Relations

167

Average Terms per Type

1.94

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import MatOnto

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