Marine Taxonomy and Life Ontology (MarineTLO)

MarineTLO is a top-level ontology for the marine domain, designed to provide consistent abstractions for concepts appearing across marine data models and ontologies. It provides the properties needed to make a distributed marine knowledge base a coherent source of facts, relating observational data to spatiotemporal context and categorical (systematic) domain knowledge [1] [3]. It can be used as a core schema for publishing linked data and for building integration systems for the marine domain [1] [3]. MarineTLO is generic enough to be extended to different levels of detail while preserving monotonicity, and it has been implemented in OWL 2 and evaluated through competency queries that capture domain requirements provided by related communities [1] [2]. By providing a shared top-level semantic framework, MarineTLO supports semantic interoperability and the integration of heterogeneous marine biodiversity and observation data across distributed sources [3] [1].

Example Usage: Use MarineTLO as a core schema to integrate marine species, observations, habitats, and sampling-event data from multiple sources, linking each observation to its taxonomic, spatial, and temporal context to enable semantic querying and interoperable analysis across marine biodiversity datasets [3] [1].

Metrics & Statistics

Graph Statistics

Total Nodes

372

Total Edges

1205

Root Nodes

3

Leaf Nodes

171

Knowledge Coverage Statistics

Classes

104

Individuals

3

Properties

94

Hierarchical Metrics

Maximum Depth

2

Minimum Depth

0

Average Depth

0.75

Depth Variance

0.44

Breadth Metrics

Maximum Breadth

4

Minimum Breadth

1

Average Breadth

2.67

Breadth Variance

1.56

LLMs4OL Dataset Statistics

Term Types

1

Taxonomic Relations

113

Non-taxonomic Relations

0

Average Terms per Type

1.00

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import MarineTLO

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

References