DataCite Ontology (DataCite)

The DataCite Ontology is an RDF/OWL-based representation of the DataCite Metadata Schema, providing a standardized semantic structure for describing research data and other digital research outputs with citation and identification metadata [1] [2]. It enables formal representation of metadata properties including identifiers, creators, titles, publishers, publication years, contributors, subjects, funding references, resource types, and relationships to other research outputs [2]. The ontology allows DataCite-related metadata concepts to be represented in RDF, supporting machine-readable identification, citation, linking, and integration of research resources [1]. The DataCite Metadata Schema supports the description of diverse research outputs, including datasets, software, textual resources, and other scholarly objects [2]. By combining persistent identifiers with structured descriptive and relational metadata, DataCite supports discovery, citation, linking, and reuse across research repositories and scholarly information systems [2]. The DataCite Ontology extends this model into a Semantic Web representation that can be integrated with other scholarly communication vocabularies and linked-data infrastructures [1].

Example Usage: Represent a published research dataset with DataCite terms for its persistent identifier, such as a DOI; creators and contributors, including ORCID identifiers where available; title, publisher, publication year, subject areas, funding information, resource type, and relationships to associated publications or other research outputs. This supports machine-readable citation, discovery, linking, and reuse across research repositories and scholarly information systems [2] [1].

Metrics & Statistics

Graph Statistics

Total Nodes

260

Total Edges

519

Root Nodes

14

Leaf Nodes

120
Knowledge Coverage Statistics

Classes

19

Individuals

70

Properties

10
Hierarchical Metrics

Maximum Depth

8

Minimum Depth

0

Average Depth

3.21

Depth Variance

5.93
Breadth Metrics

Maximum Breadth

14

Minimum Breadth

3

Average Breadth

7.56

Breadth Variance

9.80
LLMs4OL Dataset Statistics

Term Types

71

Taxonomic Relations

27

Non-taxonomic Relations

2

Average Terms per Type

8.88

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import DataCite

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