.. sidebar::

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

       * - **Domain**
         - Chemistry
       * - **Category**
         - Chemicals, Processes
       * - **Current Version**
         - 04-14-2022
       * - **Last Updated**
         - 04-14-2022
       * - **Creator**
         - Anna Dun, Wes A. Schafer, Yongqun "Oliver" He (YH), Zachary Dance
       * - **License**
         - Creative Commons 4.0
       * - **Format**
         - owl
       * - **Download**
         - `Download PROcess Chemistry Ontology (PROCO) <https://github.com/proco-ontology/PROCO>`_

PROcess Chemistry Ontology (PROCO)
========================================================================================================

PROCO (PROcess Chemistry Ontology) is a formal ontology that standardizes representation of entities, relationships, and processes in process chemistry and chemical manufacturing. It provides comprehensive vocabulary for describing chemical reactions, reaction conditions, reactants, products, catalysts, and process equipment used in industrial and laboratory chemical processes. PROCO captures essential process chemistry concepts including reaction parameters (temperature, pressure, time, stirring), process steps (mixing, heating, separation), material flows, and safety-critical information for chemical synthesis. The ontology enables semantic interoperability across chemical engineering databases, laboratory information management systems (LIMS), and process simulation tools by providing explicit, unambiguous definitions. PROCO supports knowledge integration and reasoning in process chemistry research, enabling automated workflow design, process optimization, and risk assessment.

**Example Usage**: Represent a multi-step synthesis process with PROCO terms for each reaction step including reactants, reaction conditions (temperature and pressure ranges), catalysts, solvents, workup procedures, and desired products with yield information.

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

.. tab:: Graph


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

        * - **Total Nodes**
          - 6258
        * - **Total Edges**
          - 11796
        * - **Root Nodes**
          - 89
        * - **Leaf Nodes**
          - 4646
    ::


.. tab:: Coverage


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

        * - **Classes**
          - 970
        * - **Individuals**
          - 14
        * - **Properties**
          - 61

    ::

.. tab:: Hierarchy


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

        * - **Maximum Depth**
          - 15
        * - **Minimum Depth**
          - 0
        * - **Average Depth**
          - 3.35
        * - **Depth Variance**
          - 8.54
    ::


.. tab:: Breadth


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

        * - **Maximum Breadth**
          - 228
        * - **Minimum Breadth**
          - 1
        * - **Average Breadth**
          - 60.19
        * - **Breadth Variance**
          - 4521.40
    ::

.. tab:: LLMs4OL


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

        * - **Term Types**
          - 14
        * - **Taxonomic Relations**
          - 1757
        * - **Non-taxonomic Relations**
          - 1
        * - **Average Terms per Type**
          - 7.00
    ::

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

.. code-block:: python

    from ontolearner.ontology import PROCO

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