Data Catalog Vocabulary (DCAT)

The Data Catalog Vocabulary (DCAT) is an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web [1] [2]. It provides a structured semantic model for describing catalogs, datasets, dataset series, data services, distributions, catalog records, and related metadata, enabling resource descriptions to be shared and processed in a machine-readable form [1]. DCAT supports data discovery by allowing metadata from different catalogs to be aggregated, exchanged, searched, and reused through a common vocabulary [1] [2].

The vocabulary defines classes and properties for describing catalog resources, including titles, descriptions, publishers, themes, keywords, access URLs, download URLs, formats, licenses, temporal coverage, spatial coverage, and relationships between datasets, distributions, and data services [1]. The evolution of DCAT has extended the vocabulary beyond the original catalog-and-dataset model to support additional concepts such as data services, dataset series, versioning, and richer relationships between cataloged resources [2] [1].

DCAT is used to support metadata interoperability and resource discovery across governmental, research, and other data infrastructures [2]. By providing a standardized semantic framework, it enables metadata aggregation, catalog integration, and exchange across heterogeneous data-management environments [1] [2].

Example Usage: Annotate a data catalog with DCAT terms to describe datasets, dataset series, data services, distributions, catalog records, publishers, access URLs, licenses, formats, and thematic categories. This enables standardized metadata exchange, aggregation, and discovery across different catalog systems [1] [2].

Metrics & Statistics

Graph Statistics

Total Nodes

987

Total Edges

1313

Root Nodes

7

Leaf Nodes

908
Knowledge Coverage Statistics

Classes

10

Individuals

0

Properties

39
Hierarchical Metrics

Maximum Depth

3

Minimum Depth

0

Average Depth

2.42

Depth Variance

0.58
Breadth Metrics

Maximum Breadth

121

Minimum Breadth

7

Average Breadth

54.50

Breadth Variance

2135.25
LLMs4OL Dataset Statistics

Term Types

0

Taxonomic Relations

8

Non-taxonomic Relations

0

Average Terms per Type

0.00

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import DCAT

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