.. sidebar::

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

       * - **Domain**
         - Geography
       * - **Category**
         - geospatial Information, Geology
       * - **Current Version**
         - 1.0
       * - **Last Updated**
         - 2020-05-31
       * - **Creator**
         - Simon J D Cox (simon.cox@csiro.au) of CSIRO
       * - **License**
         - Creative Commons 1.0
       * - **Format**
         - ttl
       * - **Download**
         - `Download Geologic Timescale model (GTS) <https://raw.githack.com/CGI-IUGS/timescale-ont/master/html/gts.html>`_

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. It provides a formal semantic model for representing geological time periods, epochs, eons, and their boundaries based on the Global Stratotype Section and Point (GSSP) framework established by the International Commission on Stratigraphy. GTS enables precise temporal annotation of geological data, enabling scientists to associate geological observations, samples, and events with specific time periods in Earth's history. The ontology supports hierarchical relationships between time divisions, enabling both broad geological age classification and detailed temporal analysis. GTS facilitates integration of paleontological, stratigraphic, and geological survey data across diverse research institutions and databases.

**Example Usage**:
Annotate a rock sample or fossil record with GTS terms such as "Cretaceous" (era), "Campanian" (stage), or specific GSSP boundary ages to enable temporal querying and stratigraphic correlation.

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

.. tab:: Graph


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

        * - **Total Nodes**
          - 311
        * - **Total Edges**
          - 743
        * - **Root Nodes**
          - 0
        * - **Leaf Nodes**
          - 92
    ::


.. tab:: Coverage


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

        * - **Classes**
          - 40
        * - **Individuals**
          - 7
        * - **Properties**
          - 12

    ::

.. tab:: Hierarchy


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

        * - **Maximum Depth**
          - 0
        * - **Minimum Depth**
          - 0
        * - **Average Depth**
          - 0.00
        * - **Depth Variance**
          - 0.00
    ::


.. tab:: Breadth


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

        * - **Maximum Breadth**
          - 0
        * - **Minimum Breadth**
          - 0
        * - **Average Breadth**
          - 0.00
        * - **Breadth Variance**
          - 0.00
    ::

.. tab:: LLMs4OL


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

        * - **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:

.. code-block:: python

    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