Materials Science and Engineering Ontology (MSEO)

The Materials Science and Engineering Ontology (MSEO) is a domain ontology developed to represent experiments and resulting data in materials science and engineering. It provides a structured vocabulary for describing materials, processes, and data, supporting both theoretical and experimental research in materials science.

The ontology employs a class-based modeling approach, defining classes for different types of materials, processes, and data, along with properties to describe their characteristics and interactions. Hierarchies are used to organize classes into categories, enabling efficient data retrieval and analysis. MSEO supports the integration of data from various sources, promoting interoperability and data-driven research in materials science.

Typical applications of MSEO include the integration of materials data from various sources, the development of new materials with specific properties, and the optimization of manufacturing processes. By providing a standardized vocabulary and framework, MSEO enhances collaboration and innovation in the field of materials science.

Example Usage: Annotate a materials science experiment with MSEO terms to specify material types, processes, and data, enabling semantic search and integration with materials informatics platforms.

Metrics & Statistics

Graph Statistics

Total Nodes

543

Total Edges

782

Root Nodes

12

Leaf Nodes

396
Knowledge Coverage Statistics

Classes

138

Individuals

0

Properties

2
Hierarchical Metrics

Maximum Depth

4

Minimum Depth

0

Average Depth

1.44

Depth Variance

1.58
Breadth Metrics

Maximum Breadth

18

Minimum Breadth

5

Average Breadth

9.60

Breadth Variance

24.24
LLMs4OL Dataset Statistics

Term Types

0

Taxonomic Relations

102

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 MSEO

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