.. sidebar::

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

       * - **Domain**
         - Scholarly Knowledge
       * - **Category**
         - Administration
       * - **Current Version**
         - None
       * - **Last Updated**
         - None
       * - **Creator**
         - David Shotton
       * - **License**
         - Creative Commons 4.0
       * - **Format**
         - rdf
       * - **Download**
         - `Download Funding, Research Administration and Projects Ontology (FRAPO) <http://www.sparontologies.net/ontologies/frapo>`_

Funding, Research Administration and Projects Ontology (FRAPO)
========================================================================================================

The Funding, Research Administration and Projects Ontology (FRAPO) is an ontology for describing the administrative information of research projects, e.g., grant applications, funding bodies, project partners, etc. It provides a structured vocabulary for representing research administration, funding, and project information, supporting both theoretical and experimental research in research administration.

The ontology employs a class-based modeling approach, defining classes for different types of research administration, funding, and project information, along with properties to describe their characteristics and interactions. Hierarchies are used to organize classes into categories, enabling efficient data retrieval and analysis. FRAPO supports the integration of data from various sources, promoting interoperability and data-driven research in research administration.

Typical applications of FRAPO include the development of new research administration methods, the optimization of research project management practices, and the integration of diverse datasets to support advanced analytics and knowledge discovery. By providing a standardized vocabulary and framework, FRAPO enhances collaboration and innovation in the field of research administration.

**Example Usage**:
Annotate a research project with FRAPO terms to specify administrative information, funding details, and project partners, enabling semantic search and integration with research administration platforms.

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

.. tab:: Graph


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

        * - **Total Nodes**
          - 539
        * - **Total Edges**
          - 1076
        * - **Root Nodes**
          - 18
        * - **Leaf Nodes**
          - 274
    ::


.. tab:: Coverage


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

        * - **Classes**
          - 97
        * - **Individuals**
          - 25
        * - **Properties**
          - 125

    ::

.. tab:: Hierarchy


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

        * - **Maximum Depth**
          - 3
        * - **Minimum Depth**
          - 0
        * - **Average Depth**
          - 0.68
        * - **Depth Variance**
          - 1.08
    ::


.. tab:: Breadth


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

        * - **Maximum Breadth**
          - 18
        * - **Minimum Breadth**
          - 3
        * - **Average Breadth**
          - 7.00
        * - **Breadth Variance**
          - 40.50
    ::

.. tab:: LLMs4OL


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

        * - **Term Types**
          - 25
        * - **Taxonomic Relations**
          - 82
        * - **Non-taxonomic Relations**
          - 0
        * - **Average Terms per Type**
          - 8.33
    ::

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

.. code-block:: python

    from ontolearner.ontology import FRAPO

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