.. sidebar::

    .. list-table:: **Ontology Card**
       :header-rows: 0

       * - **Domain**
         - General Knowledge
       * - **Category**
         - Metadata
       * - **Current Version**
         - 1.1
       * - **Last Updated**
         - February 17, 2017
       * - **Creator**
         - The Dublin Core Metadata Initiative
       * - **License**
         - Public Domain
       * - **Format**
         - rdf
       * - **Download**
         - `Download Dublin Core Vocabulary (DublinCore) <https://bioportal.bioontology.org/ontologies/DC>`_

Dublin Core Vocabulary (DublinCore)
========================================================================================================

The Dublin Core Schema is a small yet powerful vocabulary providing essential metadata elements for describing resources across diverse domains. Dublin Core Metadata can be used for multiple purposes including simple resource description, cross-standard metadata interoperability, and Linked Data cloud integration. It comprises fifteen core metadata elements (title, creator, subject, description, publisher, contributor, date, type, format, identifier, source, language, relation, coverage, rights) that are universally applicable across resource types. Dublin Core supports both simple and qualified metadata representation, enabling both basic and complex semantic annotation requirements. The vocabulary is language-independent and has become the de facto standard for resource description in digital libraries, institutional repositories, and data catalogs worldwide. Dublin Core facilitates semantic interoperability across heterogeneous information systems and enables automated resource discovery and management.

**Example Usage**:
Annotate a research dataset or publication with Dublin Core terms including title, creator (author), date, subject (keywords), description, format (data type), identifier (DOI/URL), and rights (license) to enable standardized discovery and citation across digital repositories.

Metrics & Statistics
--------------------------

.. tab:: Graph


    .. list-table:: Graph Statistics
        :widths: 50 50
        :header-rows: 0

        * - **Total Nodes**
          - 296
        * - **Total Edges**
          - 632
        * - **Root Nodes**
          - 1
        * - **Leaf Nodes**
          - 210
    ::


.. tab:: Coverage


    .. list-table:: Knowledge Coverage Statistics
        :widths: 50 50
        :header-rows: 0

        * - **Classes**
          - 11
        * - **Individuals**
          - 26
        * - **Properties**
          - 0

    ::

.. tab:: Hierarchy


    .. list-table:: Hierarchical Metrics
        :widths: 50 50
        :header-rows: 0

        * - **Maximum Depth**
          - 1
        * - **Minimum Depth**
          - 0
        * - **Average Depth**
          - 0.50
        * - **Depth Variance**
          - 0.25
    ::


.. tab:: Breadth


    .. list-table:: Breadth Metrics
        :widths: 50 50
        :header-rows: 0

        * - **Maximum Breadth**
          - 1
        * - **Minimum Breadth**
          - 1
        * - **Average Breadth**
          - 1.00
        * - **Breadth Variance**
          - 0.00
    ::

.. tab:: LLMs4OL


    .. list-table:: LLMs4OL Dataset Statistics
        :widths: 50 50
        :header-rows: 0

        * - **Term Types**
          - 30
        * - **Taxonomic Relations**
          - 0
        * - **Non-taxonomic Relations**
          - 0
        * - **Average Terms per Type**
          - 3.00
    ::

Usage Example
----------------
Use the following code to import this ontology programmatically:

.. code-block:: python

    from ontolearner.ontology import DublinCore

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