| Battery Value Chain Ontology (BVCO) |
| ======================================================================================================================== |
|
|
| Overview |
| -------- |
| Basically, Battery Value Chain Ontology (BVCO) aims to model processes along the Battery value chain. Processes are |
| holistic perspective elements that transform inputs/educts (matter, energy, information) |
| into output/products (matter, energy, information) with the help of tools (devices, algorithms). |
| They can be decomposed into sub-processes and have predecessor and successor processes. |
|
|
| :Domain: Materials Science and Engineering |
| :Category: Materials Science |
| :Current Version: 0.4.3 |
| :Last Updated: None |
| :Creator: Lukas Gold, Simon Stier |
| :License: Creative Commons Attribution 4.0 International (CC BY 4.0) |
| :Format: TTL |
| :Download: `Battery Value Chain Ontology (BVCO) Homepage <https://github.com/Battery-Value-Chain-Ontology/ontology>`_ |
|
|
| Graph Metrics |
| ------------- |
| - **Total Nodes**: 804 |
| - **Total Edges**: 1719 |
| - **Root Nodes**: 85 |
| - **Leaf Nodes**: 283 |
|
|
| Knowledge coverage |
| ------------------ |
| - Classes: 262 |
| - Individuals: 0 |
| - Properties: 6 |
|
|
| Hierarchical metrics |
| -------------------- |
| - **Maximum Depth**: 14 |
| - **Minimum Depth**: 0 |
| - **Average Depth**: 2.47 |
| - **Depth Variance**: 5.27 |
|
|
| Breadth metrics |
| ------------------ |
| - **Maximum Breadth**: 230 |
| - **Minimum Breadth**: 2 |
| - **Average Breadth**: 52.20 |
| - **Breadth Variance**: 4920.43 |
|
|
| Dataset Statistics |
| ------------------ |
| Generated Benchmarks: |
| - **Term Types**: 0 |
| - **Taxonomic Relations**: 0 |
| - **Non-taxonomic Relations**: 0 |
| - **Average Terms per Type**: 0.00 |
|
|
| Usage Example |
| ------------- |
| .. code-block:: python |
|
|
| from ontolearner.ontology import BVCO |
|
|
| # Initialize and load ontology |
| ontology = BVCO() |
| 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 |
|
|
