Agronomy Ontology (AgrO)

The Agronomy Ontology (AgrO) provides terms from the agronomy domain that are semantically organized and facilitate the collection, storage, and use of agronomic data, enabling easier interpretation and reuse by both humans and machines [1] [2]. To analyze the effects of varying practices within cropping systems, it is often necessary to integrate data from multiple disciplinary domains. For example, data on field management, soil, weather, and crop phenotypes may need to be combined to assess crop performance under different management interventions. However, agronomic data are often collected, described, and stored in inconsistent ways, which impedes data comparison, mining, interpretation, and reuse [1]. The use of standards for metadata and data annotation plays a key role in addressing these challenges. While the CG Core Metadata Schema provides a metadata standard to describe agricultural datasets, the Agronomy Ontology enables the description of agronomic variables using standardized and semantically defined terms [1] [3]. AgrO specifically covers agronomic practices, techniques, and variables used in agronomic experiments and reuses terms from other ontologies to support interoperability [2].

Example Usage: Annotate agronomic field experiment data with AgrO terms for management practices, treatments, and measured variables to enable standardized description, interoperable storage, and cross-study comparison of agricultural data [2] [3].

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