Crystallographic Information Framework Core Dictionary (CIFCore)¶
The Crystallographic Information Framework Core Dictionary (CIFCore) is a machine-readable dictionary developed to represent core crystallographic data within the Crystallographic Information Framework (CIF) [1]. It provides structured data names for archiving and exchanging raw data, processed data, and derived structural results in crystallography and related structural sciences [1].
The CIF Ontology provides an ontological representation of the CIF Dictionary Definition Language (DDLm) and the IUCr CIF core dictionary, supporting semantic annotation and machine-actionable use of CIF data [2]. CIFCore supports the standardized description of crystallographic information such as crystal structures, symmetry information, atomic coordinates, diffraction data, and experimental details [1] [2]. By providing a structured vocabulary, CIFCore supports data exchange, validation, interoperability, reproducibility, and integration with crystallographic and structural databases [1] [2].
Example Usage: Annotate a crystallographic dataset with CIFCore terms to specify crystal lattice parameters, atomic positions, symmetry information, diffraction experiment details, and derived structural results, enabling semantic search, validation, and integration with structural databases [1] [2].
Metrics & Statistics¶
Total Nodes |
4494 |
Total Edges |
15377 |
Root Nodes |
1 |
Leaf Nodes |
3310 |
Classes |
1182 |
Individuals |
0 |
Properties |
0 |
Maximum Depth |
1 |
Minimum Depth |
0 |
Average Depth |
0.75 |
Depth Variance |
0.19 |
Maximum Breadth |
3 |
Minimum Breadth |
1 |
Average Breadth |
2.00 |
Breadth Variance |
1.00 |
Term Types |
0 |
Taxonomic Relations |
27150 |
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 CIFCore
ontology = CIFCore()
ontology.load("path/to/CIFCore-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