Physico-chemical process ontology (REX)¶
REX is an ontology for the formal representation of physico-chemical processes, including both microscopic molecular transformations and macroscopic chemical phenomena [1] [2]. It provides a structured vocabulary for describing processes at different scales, such as molecular-level processes involving chemical bond changes, molecular rearrangements, and electron transfer, as well as macroscopic processes such as phase changes, dissolution, and crystallization [1] [2]. REX distinguishes between different process types and supports formal representation of chemical transformations in a standardized and machine-readable way [1] [2]. By providing explicit process definitions, the ontology supports knowledge integration across chemistry databases, computational chemistry platforms, and related scientific data systems [1] [2].
Example Usage: Represent a multi-step chemical transformation using REX terms to describe molecular-level processes such as oxidation or substitution, together with their sequence and relationships, enabling structured representation and semantic querying of complex physico-chemical processes [1] [2].
Metrics & Statistics¶
Total Nodes |
2461 |
Total Edges |
5630 |
Root Nodes |
356 |
Leaf Nodes |
1457 |
Classes |
552 |
Individuals |
0 |
Properties |
6 |
Maximum Depth |
6 |
Minimum Depth |
0 |
Average Depth |
1.35 |
Depth Variance |
0.97 |
Maximum Breadth |
978 |
Minimum Breadth |
5 |
Average Breadth |
304.57 |
Breadth Variance |
116930.53 |
Term Types |
0 |
Taxonomic Relations |
953 |
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 REX
ontology = REX()
ontology.load("path/to/REX-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