Chemical Methods Ontology (ChMO)¶
The Chemical Methods Ontology (ChMO) is a structured ontology that provides a controlled vocabulary for describing chemical methods, experimental techniques, and analytical procedures used in chemistry and related sciences [1]. ChMO contains terms covering methods for data collection, sample preparation and separation, and material synthesis, together with associated instruments and experimental outputs [1]. The ontology is intended to support semantic annotation of chemical workflows and to improve interoperability across chemical databases, laboratory information systems, and computational tools [1]. By providing a standardized framework for chemical methods and related experimental information, ChMO supports data integration, reproducibility, and structured querying across chemical research datasets [1].
Example Usage: Annotate a chemical experiment with ChMO terms to specify the analytical method, such as liquid chromatography-mass spectrometry, the sample preparation steps, the instrument configuration, and the data outputs, enabling semantic search and integration with other chemical research datasets [1].
Metrics & Statistics¶
Total Nodes |
24075 |
Total Edges |
44651 |
Root Nodes |
3100 |
Leaf Nodes |
17250 |
Classes |
3202 |
Individuals |
0 |
Properties |
27 |
Maximum Depth |
7 |
Minimum Depth |
0 |
Average Depth |
1.49 |
Depth Variance |
0.63 |
Maximum Breadth |
13439 |
Minimum Breadth |
1 |
Average Breadth |
2993.88 |
Breadth Variance |
20855464.86 |
Term Types |
0 |
Taxonomic Relations |
3601 |
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 ChMO
ontology = ChMO()
ontology.load("path/to/ChMO-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