Geologic Timescale model (GTS)

The Geologic Timescale (GTS) is an RDF/OWL ontology representation of the standard geologic timescale model, adapted from the GeoSciML framework and compatible with geospatial information transfer standards [1] [2]. It provides a formal semantic model for representing geological time periods, epochs, eons, stages, and their boundaries [2]. GTS enables precise temporal annotation of geological data, allowing scientists to associate geological observations, samples, fossil records, stratigraphic units, and events with specific intervals in Earth’s history [1]. The ontology supports hierarchical relationships between geological time divisions, enabling both broad geological age classification and detailed temporal analysis [1] [2]. GTS facilitates integration of paleontological, stratigraphic, and geological survey data across diverse research institutions, databases, and linked data systems [2].

Example Usage: Annotate a rock sample or fossil record with GTS terms such as Cretaceous, Campanian, or specific geologic time boundary information to enable temporal querying, stratigraphic correlation, and integration with geological survey datasets [1] [2].

Metrics & Statistics

Graph Statistics

Total Nodes

311

Total Edges

743

Root Nodes

0

Leaf Nodes

92

Knowledge Coverage Statistics

Classes

40

Individuals

7

Properties

12

Hierarchical Metrics

Maximum Depth

0

Minimum Depth

0

Average Depth

0.00

Depth Variance

0.00

Breadth Metrics

Maximum Breadth

0

Minimum Breadth

0

Average Breadth

0.00

Breadth Variance

0.00

LLMs4OL Dataset Statistics

Term Types

7

Taxonomic Relations

77

Non-taxonomic Relations

2

Average Terms per Type

7.00

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import GTS

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

References