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PROcess Chemistry Ontology (PROCO) |
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Overview |
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-------- |
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PROCO (PROcess Chemistry Ontology) is a formal ontology that aims to standardly represent entities |
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and relations among entities in the domain of process chemistry. |
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:Domain: Chemistry |
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:Category: Chemicals, Processes |
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:Current Version: 04-14-2022 |
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:Last Updated: 04-14-2022 |
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:Creator: Anna Dun, Wes A. Schafer, Yongqun "Oliver" He (YH), Zachary Dance |
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:License: Creative Commons 4.0 |
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:Format: OWL |
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:Download: `PROcess Chemistry Ontology (PROCO) Homepage <https://github.com/proco-ontology/PROCO>`_ |
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Graph Metrics |
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- **Total Nodes**: 6258 |
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- **Total Edges**: 11796 |
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- **Root Nodes**: 89 |
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- **Leaf Nodes**: 4646 |
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Knowledge coverage |
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- Classes: 970 |
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- Individuals: 14 |
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- Properties: 61 |
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Hierarchical metrics |
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- **Maximum Depth**: 15 |
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- **Minimum Depth**: 0 |
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- **Average Depth**: 3.35 |
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- **Depth Variance**: 8.54 |
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Breadth metrics |
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- **Maximum Breadth**: 228 |
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- **Minimum Breadth**: 1 |
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- **Average Breadth**: 60.19 |
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- **Breadth Variance**: 4521.40 |
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Dataset Statistics |
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Generated Benchmarks: |
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- **Term Types**: 14 |
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- **Taxonomic Relations**: 2975 |
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- **Non-taxonomic Relations**: 1 |
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- **Average Terms per Type**: 7.00 |
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Usage Example |
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.. code-block:: python |
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from ontolearner.ontology import PROCO |
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# Initialize and load ontology |
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ontology = PROCO() |
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ontology.load("path/to/ontology.owl") |
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# Extract datasets |
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data = ontology.extract() |
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# Access specific relations |
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term_types = data.term_typings |
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taxonomic_relations = data.type_taxonomies |
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non_taxonomic_relations = data.type_non_taxonomic_relations |
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