.. sidebar::

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

       * - **Domain**
         - Scholarly Knowledge
       * - **Category**
         - Workflows
       * - **Current Version**
         - 3.1
       * - **Last Updated**
         - 2014-12-22
       * - **Creator**
         - http://delicias.dia.fi.upm.es/members/DGarijo/#me, http://www.isi.edu/~gil/
       * - **License**
         - Creative Commons Attribution 2.0 Generic (CC BY 2.0)
       * - **Format**
         - owl
       * - **Download**
         - `Download Open Provenance Model for Workflows (OPMW) <https://www.opmw.org/model/OPMW_20141222/>`_

Open Provenance Model for Workflows (OPMW)
========================================================================================================

OPMW is a specialized ontology for comprehensive semantic description of computational workflow traces, executions, and their templates based on the Open Provenance Model (OPM) framework. It provides vocabulary for describing workflow components including processes, inputs/outputs, agents, and execution steps, along with provenance information tracking data flow and transformations. OPMW is designed as an OPM profile, extending and reusing OPM's core ontologies OPMV (OPM-Vocabulary) and OPMO (OPM-Ontology) to provide workflow-specific semantics. The ontology enables systematic documentation and sharing of scientific workflows, supporting reproducibility and reuse in data-intensive research disciplines. OPMW facilitates workflow management systems and scientific computing platforms by providing standardized provenance representations.

**Example Usage**: Annotate a bioinformatics workflow with OPMW terms to describe workflow steps (sequence alignment, variant calling), inputs (raw sequencing data), outputs (VCF files), and provenance tracking which software tools were used, parameter settings, and intermediate data transformations.

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

.. tab:: Graph


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

        * - **Total Nodes**
          - 539
        * - **Total Edges**
          - 1387
        * - **Root Nodes**
          - 33
        * - **Leaf Nodes**
          - 306
    ::


.. tab:: Coverage


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

        * - **Classes**
          - 59
        * - **Individuals**
          - 2
        * - **Properties**
          - 87

    ::

.. tab:: Hierarchy


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

        * - **Maximum Depth**
          - 6
        * - **Minimum Depth**
          - 0
        * - **Average Depth**
          - 2.14
        * - **Depth Variance**
          - 2.07
    ::


.. tab:: Breadth


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

        * - **Maximum Breadth**
          - 59
        * - **Minimum Breadth**
          - 5
        * - **Average Breadth**
          - 31.57
        * - **Breadth Variance**
          - 405.67
    ::

.. tab:: LLMs4OL


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

        * - **Term Types**
          - 0
        * - **Taxonomic Relations**
          - 77
        * - **Non-taxonomic Relations**
          - 4
        * - **Average Terms per Type**
          - 0.00
    ::

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

.. code-block:: python

    from ontolearner.ontology import OPMW

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