Refactored ontologies, added metrics, and automated docs generations #211

Author: HamedBabaei

docs/source/benchmarking/agricultural/agrovoc.rst

@@ -0,0 +1,71 @@
+AGROVOC Multilingual Thesaurus
+===================================
+
+Overview
+--------
+AGROVOC is a relevant Linked Open Data set about agriculture available for public use and facilitates
+access and visibility of data across domains and languages. It offers a structured collection of agricultural concepts,
+terms, definitions and relationships which are used to unambiguously identify resources, allowing standardized
+indexing processes and making searches more efficient.
+
+:Domain: Agricultural
+:Category: Agricultural Knowledge
+:Current Version: 2024-04
+:Last Updated: August 12, 2024
+:Creator: Food and Agriculture Organization of the United Nations
+:License: Creative Commons 4.0
+:Format: RDF, SKOS
+:Download: `AGROVOC Multilingual Thesaurus Homepage <https://agroportal.lirmm.fr/ontologies/AGROVOC>`_
+
+Graph Metrics
+-------------
+    - **Total Nodes**: 2279766
+    - **Total Edges**: 10140352
+    - **Root Nodes**: 59
+    - **Leaf Nodes**: 981249
+
+Knowledge coverage
+------------------
+    - Classes: 35
+    - Individuals: 1234769
+    - Properties: 209
+
+Hierarchical metrics
+--------------------
+    - **Maximum Depth**: 11
+    - **Minimum Depth**: 0
+    - **Average Depth**: 5.24
+    - **Depth Variance**: 2.31
+
+Breadth metrics
+------------------
+    - **Maximum Breadth**: 617543
+    - **Minimum Breadth**: 9
+    - **Average Breadth**: 189858.08
+    - **Breadth Variance**: 44142143480.08
+
+Dataset Statistics
+------------------
+Generated Benchmarks:
+    - **Term Types**: 1234769
+    - **Taxonomic Relations**: 13
+    - **Non-taxonomic Relations**: 7
+    - **Average Terms per Type**: 47491.12
+
+Usage Example
+-------------
+.. code-block:: python
+
+    from ontolearner.ontology import AGROVOC
+
+    # Initialize and load ontology
+    ontology = AGROVOC()
+    ontology.load("path/to/ontology.owl")
+
+    # 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

docs/source/benchmarking/agricultural/foodon.rst

@@ -0,0 +1,72 @@
+Food Ontology (FoodON)
+==========================
+
+Overview
+--------
+FoodOn, the food ontology, contains vocabulary for naming food materials and their anatomical and taxonomic origins,
+from raw harvested food to processed food products, for humans and domesticated animals.
+It provides a neutral and ontology-driven standard for government agencies,
+industry, nonprofits and consumers to name and reference food products and their components
+throughout the food supply chain.
+
+:Domain: Agricultural
+:Category: Diet, Metabolomics, and Nutrition
+:Current Version: None
+:Last Updated: 2025-01-16
+:Creator: None
+:License: Creative Commons 4.0
+:Format: OWL
+:Download: `Food Ontology (FoodON) Homepage <http://purl.obolibrary.org/obo/foodon.owl>`_
+
+Graph Metrics
+-------------
+    - **Total Nodes**: 176584
+    - **Total Edges**: 423840
+    - **Root Nodes**: 4834
+    - **Leaf Nodes**: 90848
+
+Knowledge coverage
+------------------
+    - Classes: 47261
+    - Individuals: 16
+    - Properties: 197
+
+Hierarchical metrics
+--------------------
+    - **Maximum Depth**: 23
+    - **Minimum Depth**: 0
+    - **Average Depth**: 2.24
+    - **Depth Variance**: 4.81
+
+Breadth metrics
+------------------
+    - **Maximum Breadth**: 11122
+    - **Minimum Breadth**: 2
+    - **Average Breadth**: 1217.12
+    - **Breadth Variance**: 6546794.36
+
+Dataset Statistics
+------------------
+Generated Benchmarks:
+    - **Term Types**: 16
+    - **Taxonomic Relations**: 98513
+    - **Non-taxonomic Relations**: 7924
+    - **Average Terms per Type**: 0.94
+
+Usage Example
+-------------
+.. code-block:: python
+
+    from ontolearner.ontology import FoodOn
+
+    # Initialize and load ontology
+    ontology = FoodOn()
+    ontology.load("path/to/ontology.owl")
+
+    # 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

docs/source/benchmarking/agricultural/po.rst

@@ -0,0 +1,69 @@
+Plant Ontology (PO)
+==========================
+
+Overview
+--------
+The Plant Ontology (PO) is a structured vocabulary and database resource that links plant anatomy,
+morphology and growth and development to plant genomics data.
+
+:Domain: Agricultural
+:Category: Plant Anatomy, Morphology, Growth and Development
+:Current Version: None
+:Last Updated: None
+:Creator: None
+:License: Creative Commons 4.0
+:Format: OWL, TTL, CSV, NT
+:Download: `Plant Ontology (PO) Homepage <https://github.com/Planteome/plant-ontology>`_
+
+Graph Metrics
+-------------
+    - **Total Nodes**: 20790
+    - **Total Edges**: 60638
+    - **Root Nodes**: 5936
+    - **Leaf Nodes**: 11639
+
+Knowledge coverage
+------------------
+    - Classes: 1874
+    - Individuals: 0
+    - Properties: 13
+
+Hierarchical metrics
+--------------------
+    - **Maximum Depth**: 5
+    - **Minimum Depth**: 0
+    - **Average Depth**: 1.07
+    - **Depth Variance**: 0.72
+
+Breadth metrics
+------------------
+    - **Maximum Breadth**: 8034
+    - **Minimum Breadth**: 82
+    - **Average Breadth**: 3462.50
+    - **Breadth Variance**: 11752362.58
+
+Dataset Statistics
+------------------
+Generated Benchmarks:
+    - **Term Types**: 0
+    - **Taxonomic Relations**: 5288
+    - **Non-taxonomic Relations**: 117
+    - **Average Terms per Type**: 0.00
+
+Usage Example
+-------------
+.. code-block:: python
+
+    from ontolearner.ontology import PO
+
+    # Initialize and load ontology
+    ontology = PO()
+    ontology.load("path/to/ontology.owl")
+
+    # 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