Allotrope Foundation Ontology (AFO)

The Allotrope Foundation Ontology (AFO) is a comprehensive ontology suite designed to standardize the representation of laboratory analytical processes. It provides a semantic model and controlled vocabulary for describing key domains such as Equipment, Material, Process, and Results. The AFO is aligned with the Basic Formal Ontology (BFO) at its upper layer, ensuring compatibility with other ontological frameworks. This ontology suite is particularly valuable for integrating data from diverse laboratory systems, enabling semantic interoperability and facilitating advanced data analysis. By providing explicit definitions and relationships, the AFO supports the automation of laboratory workflows, enhances data reproducibility, and improves the traceability of analytical processes. Researchers and organizations can use the AFO to annotate experimental data, describe laboratory protocols, and ensure compliance with data standards.

Example Usage: Annotate a laboratory experiment with AFO terms to specify the equipment used (e.g., “mass spectrometer”), the materials analyzed (e.g., “chemical sample”), and the processes performed (e.g., “chromatography”), along with the results obtained.

Metrics & Statistics

Graph Statistics

Total Nodes

15547

Total Edges

36699

Root Nodes

142

Leaf Nodes

8003
Knowledge Coverage Statistics

Classes

3871

Individuals

38

Properties

318
Hierarchical Metrics

Maximum Depth

24

Minimum Depth

0

Average Depth

5.14

Depth Variance

22.60
Breadth Metrics

Maximum Breadth

368

Minimum Breadth

1

Average Breadth

75.84

Breadth Variance

8251.25
LLMs4OL Dataset Statistics

Term Types

37

Taxonomic Relations

6904

Non-taxonomic Relations

34

Average Terms per Type

3.36

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import AFO

ontology = AFO()
ontology.load("path/to/AFO-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