Environmental Noise Measurement Ontology (ENM)

The Environmental Noise Measurement Ontology (ENM) is an application ontology developed as part of the eNanoMapper (https://www.enanomapper.net/), NanoCommons (https://www.nanocommons.eu/), and ACEnano (http://acenano-project.eu/) projects to support toxicological data management for engineered nanomaterials (ENMs). ENM provides a comprehensive vocabulary for describing nanomaterial safety assessment, including experimental procedures, measurement techniques, material properties, and exposure scenarios. The ontology reuses and integrates terms from several established ontologies, such as the Nanoparticle Ontology (NPO), Chemical Information Ontology (CHEMINF), Chemical Entities of Biological Interest (ChEBI), and Environment Ontology (ENVO), to ensure semantic interoperability and data integration. ENM enables standardized annotation of nanomaterial safety data, facilitating data sharing, regulatory compliance, and advanced analysis across research projects and databases. By providing a common framework, ENM supports the development of computational infrastructure for toxicology, risk assessment, and environmental health studies. The ontology is actively maintained and extended to incorporate new concepts and requirements from the nanomaterial safety community.

Example Usage: Annotate a nanotoxicology study with ENM terms to specify the nanomaterial type, measurement methods, exposure conditions, and observed biological effects, enabling cross-study comparison and regulatory reporting.

Metrics & Statistics

Graph Statistics

Total Nodes

102719

Total Edges

226566

Root Nodes

11156

Leaf Nodes

64025
Knowledge Coverage Statistics

Classes

26142

Individuals

9

Properties

53
Hierarchical Metrics

Maximum Depth

130

Minimum Depth

0

Average Depth

1.74

Depth Variance

56.70
Breadth Metrics

Maximum Breadth

11156

Minimum Breadth

1

Average Breadth

206.70

Breadth Variance

1767707.90
LLMs4OL Dataset Statistics

Term Types

9

Taxonomic Relations

36933

Non-taxonomic Relations

84

Average Terms per Type

3.00

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import ENM

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