Computational Material Sample Ontology (CMSO)¶
The Computational Material Sample Ontology (CMSO) is a domain ontology developed to describe computational materials science samples or structures, with a focus on machine-actionable representation of atomistic simulation data [1] [2]. It provides a structured vocabulary for representing computational samples, atomic-scale samples, crystal structures, chemical composition, simulation cells, geometry, and crystallographic defects [1] [2].
CMSO supports semantic annotation of computational materials data, enabling interoperability, data integration, and reuse across atomistic simulation workflows and materials databases [2]. The ontology is designed in a modular way and can be connected with related ontologies for crystallographic defects and atomistic simulation methods [2]. By providing a standardized framework, CMSO facilitates semantic search, cross-study comparison, and knowledge sharing in computational materials science [1] [2].
Example Usage: Annotate a computational materials science dataset with CMSO terms to specify the computational sample, atomic-scale structure, chemical composition, crystal structure, simulation cell, geometry, and crystallographic defects, enabling semantic search and integration with materials modelling databases [1] [2].
Metrics & Statistics¶
Total Nodes |
347 |
Total Edges |
556 |
Root Nodes |
40 |
Leaf Nodes |
192 |
Classes |
45 |
Individuals |
0 |
Properties |
51 |
Maximum Depth |
2 |
Minimum Depth |
0 |
Average Depth |
0.56 |
Depth Variance |
0.40 |
Maximum Breadth |
40 |
Minimum Breadth |
6 |
Average Breadth |
26.00 |
Breadth Variance |
210.67 |
Term Types |
0 |
Taxonomic Relations |
22 |
Non-taxonomic Relations |
1 |
Average Terms per Type |
0.00 |
Usage Example¶
Use the following code to import this ontology programmatically:
from ontolearner.ontology import CMSO
ontology = CMSO()
ontology.load("path/to/CMSO-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