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PRovenance Information in MAterials science (PRIMA)
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Overview
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An ontology that captures the provenance information in the materials science domain.
:Domain: Materials Science and Engineering
:Category: Materials Science
:Current Version: 2.0
:Last Updated: 2024-01-29
:Creator: Ahmad Zainul Ihsan, Mehrdad Jalali, Rossella Aversa
:License: Creative Commons Attribution 3.0 Unported (CC BY 3.0)
:Format: TTL
:Download: `PRovenance Information in MAterials science (PRIMA) Homepage <https://materials-data-science-and-informatics.github.io/MDMC-NEP-top-level-ontology/PRIMA/complete/ver_2_0/index.html>`_
Graph Metrics
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- **Total Nodes**: 444
- **Total Edges**: 1073
- **Root Nodes**: 18
- **Leaf Nodes**: 135
Knowledge coverage
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- Classes: 67
- Individuals: 0
- Properties: 67
Hierarchical metrics
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- **Maximum Depth**: 14
- **Minimum Depth**: 0
- **Average Depth**: 4.39
- **Depth Variance**: 16.39
Breadth metrics
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- **Maximum Breadth**: 27
- **Minimum Breadth**: 2
- **Average Breadth**: 7.80
- **Breadth Variance**: 48.56
Dataset Statistics
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Generated Benchmarks:
- **Term Types**: 0
- **Taxonomic Relations**: 186
- **Non-taxonomic Relations**: 1
- **Average Terms per Type**: 0.00
Usage Example
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.. code-block:: python
from ontolearner.ontology import PRIMA
# Initialize and load ontology
ontology = PRIMA()
ontology.load("path/to/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
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