Atomistic Simulation Methods Ontology (ASMO)¶
The Atomistic Simulation Methods Ontology (ASMO) is a domain ontology that formalizes concepts and relationships used to describe and classify atomic-scale computational simulation methods in materials science and computational chemistry [1] [2] [3]. It provides a structured vocabulary for representing common simulation methodologies, including density functional theory (DFT), molecular dynamics (MD), kinetic Monte Carlo methods, molecular statics, and ab initio molecular dynamics [1] [3].
ASMO captures important simulation-related concepts such as computational methods, simulation algorithms, simulation parameters, interatomic potentials, statistical ensembles, structure manipulation, mathematical operations, and calculated physical properties [1] [3]. The ontology also builds on the W3C Provenance Ontology (PROV-O) to describe simulation processes and provenance, enabling the representation of computational workflows, activities, inputs, generated results, agents, and software involved in simulations [2] [3].
ASMO facilitates reproducibility and interoperability in computational materials science by providing standardized semantic representations of simulation methods, parameters, workflows, calculated properties, and provenance across heterogeneous computational environments [1] [3].
Example Usage: Annotate a materials database entry with ASMO terms for the simulation method, such as DFT or MD, together with computational details such as simulation parameters, interatomic potentials, statistical ensembles, and resulting properties such as bulk modulus, formation energy, total energy, pressure, or magnetic moment [1] [3].
Metrics & Statistics¶
Total Nodes |
588 |
Total Edges |
1058 |
Root Nodes |
23 |
Leaf Nodes |
360 |
Classes |
99 |
Individuals |
30 |
Properties |
41 |
Maximum Depth |
5 |
Minimum Depth |
0 |
Average Depth |
1.71 |
Depth Variance |
1.87 |
Maximum Breadth |
27 |
Minimum Breadth |
3 |
Average Breadth |
15.17 |
Breadth Variance |
70.14 |
Term Types |
30 |
Taxonomic Relations |
99 |
Non-taxonomic Relations |
2 |
Average Terms per Type |
3.75 |
Usage Example¶
Use the following code to import this ontology programmatically:
from ontolearner.ontology import ASMO
ontology = ASMO()
ontology.load("path/to/ASMO-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