.. sidebar::

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

       * - **Domain**
         - General Knowledge
       * - **Category**
         - Information, Data, Knowledge
       * - **Current Version**
         - None
       * - **Last Updated**
         - 2022-11-07
       * - **Creator**
         - None
       * - **License**
         - Creative Commons 4.0
       * - **Format**
         - owl
       * - **Download**
         - `Download Information Artifact Ontology (IAO) <https://terminology.tib.eu/ts/ontologies/IAO>`_

Information Artifact Ontology (IAO)
========================================================================================================

The Information Artifact Ontology (IAO) is a comprehensive ontology for formal representation of information entities, information artifacts, and abstract information objects. It provides structured definitions of concepts such as documents, data items, information content, and the relationships between information artifacts and their physical realizations. IAO distinguishes between abstract information objects (the content) and their concrete realizations (documents, files, databases), enabling precise semantic representation of information resources. The ontology captures properties of information artifacts including authorship, creation date, version history, and relationships to the entities they describe or represent. IAO is widely used in biomedical informatics, scientific data management, and linked data applications for annotating information resources with formal semantic types.

**Example Usage**: Annotate a scientific publication with IAO terms such as "document" for the artifact type, "author" relationships, and "has content" linking to abstract information objects representing the scientific claims and data presented.

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

.. tab:: Graph


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

        * - **Total Nodes**
          - 2303
        * - **Total Edges**
          - 4720
        * - **Root Nodes**
          - 151
        * - **Leaf Nodes**
          - 1523
    ::


.. tab:: Coverage


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

        * - **Classes**
          - 292
        * - **Individuals**
          - 18
        * - **Properties**
          - 57

    ::

.. tab:: Hierarchy


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

        * - **Maximum Depth**
          - 13
        * - **Minimum Depth**
          - 0
        * - **Average Depth**
          - 2.05
        * - **Depth Variance**
          - 4.06
    ::


.. tab:: Breadth


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

        * - **Maximum Breadth**
          - 280
        * - **Minimum Breadth**
          - 1
        * - **Average Breadth**
          - 63.00
        * - **Breadth Variance**
          - 8210.29
    ::

.. tab:: LLMs4OL


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

        * - **Term Types**
          - 18
        * - **Taxonomic Relations**
          - 347
        * - **Non-taxonomic Relations**
          - 19
        * - **Average Terms per Type**
          - 6.00
    ::

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

.. code-block:: python

    from ontolearner.ontology import IAO

    ontology = IAO()
    ontology.load("path/to/IAO-ontology.owl")

    # 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