Mechanical Testing Ontology (MechanicalTesting)

The Mechanical Testing Ontology (MechanicalTesting) is a domain ontology developed to represent knowledge in the field of mechanical testing and is built on top of the Elementary Multiperspective Material Ontology (EMMO) [1] [2]. It provides a structured vocabulary for describing mechanical testing concepts, supporting semantic representation of experiments, models, software, and data in materials science [2].

The ontology supports semantic annotation, data integration, interoperability, and sharing of mechanical-testing information across materials science workflows [1] [2]. It is described as an EMMO-based domain ontology and was developed as part of efforts to create EMMO-compliant domain ontologies for materials science [1] [2]. By providing a standardized semantic framework, MechanicalTesting supports knowledge representation, data retrieval, and reuse in mechanical testing and digital-twin-related applications [2].

Example Usage: Annotate a mechanical testing dataset with MechanicalTesting terms to specify mechanical testing methods, experiment-related information, test data, models, software, and results, enabling semantic search and integration with materials informatics platforms [1] [2].

Metrics & Statistics

Graph Statistics

Total Nodes

1365

Total Edges

2569

Root Nodes

174

Leaf Nodes

713

Knowledge Coverage Statistics

Classes

369

Individuals

0

Properties

5

Hierarchical Metrics

Maximum Depth

18

Minimum Depth

0

Average Depth

2.14

Depth Variance

4.98

Breadth Metrics

Maximum Breadth

466

Minimum Breadth

1

Average Breadth

66.89

Breadth Variance

14051.46

LLMs4OL Dataset Statistics

Term Types

0

Taxonomic Relations

36

Non-taxonomic Relations

0

Average Terms per Type

0.00

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import MechanicalTesting

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