Crystallography Ontology (EMMOCrystallography)¶
The Crystallography Domain Ontology (EMMOCrystallography) is an EMMO-based domain ontology for representing crystallographic knowledge [1] [2]. It provides a formal vocabulary for describing crystallographic concepts such as crystal structures, crystallographic information, symmetry-related concepts, and structural data used in materials science [1] [2].
The ontology supports semantic annotation of crystallographic datasets, enabling interoperability, data integration, and reuse of crystallographic information across materials science and modelling workflows [2]. By connecting crystallographic concepts with the wider EMMO ontology ecosystem, EMMOCrystallography provides a standardized semantic framework for describing crystallographic structures and related data [1] [2].
Example Usage: Annotate a crystallographic dataset with EMMOCrystallography terms to specify crystal structures, symmetry information, lattice-related data, atomic positions, and crystallographic metadata, enabling semantic search and integration with materials databases and modelling tools [1] [2].
Metrics & Statistics¶
Total Nodes |
337 |
Total Edges |
586 |
Root Nodes |
29 |
Leaf Nodes |
166 |
Classes |
61 |
Individuals |
0 |
Properties |
5 |
Maximum Depth |
14 |
Minimum Depth |
0 |
Average Depth |
5.20 |
Depth Variance |
9.99 |
Maximum Breadth |
74 |
Minimum Breadth |
1 |
Average Breadth |
22.07 |
Breadth Variance |
290.60 |
Term Types |
0 |
Taxonomic Relations |
0 |
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 EMMOCrystallography
ontology = EMMOCrystallography()
ontology.load("path/to/EMMOCrystallography-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