Agronomy Ontology (AgrO)

The Agronomy Ontology (AgrO) provides terms from the agronomy domain that are semantically organized to support the collection, integration, and reuse of agronomic data across disciplinary domains [1]. To analyze the effects of varying practices within cropping systems, it is often necessary to integrate data from multiple disciplinary domains, including field management, soil, weather, and crop phenotype data. AgrO was developed to address the inconsistent description and storage of agronomic data, which can hinder comparison, interpretation, and reuse across studies and information systems [1]. The use of standards for metadata and data annotation plays a key role in addressing these challenges. AgrO enables the description of agronomic variables using standardized and semantically defined terms and covers agronomic practices, techniques, and variables used in agronomic experiments [1]. The ontology is available through AgroPortal for browsing and access [2].

Example Usage: Annotate agronomic field experiment data with AgrO terms for management practices, treatments, and measured variables to support standardized description, improved interoperability, and cross-study comparison across agricultural datasets [1] [2].

Metrics & Statistics

Graph Statistics

Total Nodes

31951

Total Edges

80144

Root Nodes

5369

Leaf Nodes

14046

Knowledge Coverage Statistics

Classes

5778

Individuals

326

Properties

209

Hierarchical Metrics

Maximum Depth

22

Minimum Depth

0

Average Depth

1.92

Depth Variance

6.01

Breadth Metrics

Maximum Breadth

7562

Minimum Breadth

6

Average Breadth

1033.17

Breadth Variance

4403827.97

LLMs4OL Dataset Statistics

Term Types

71

Taxonomic Relations

10931

Non-taxonomic Relations

1699

Average Terms per Type

4.18

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import AgrO

ontology = AgrO()
ontology.load("path/to/AgrO-ontology.rdf")

# 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

References