.. sidebar::

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

       * - **Domain**
         - Biology and Life Sciences
       * - **Category**
         - Microscopy
       * - **Current Version**
         - 2.0
       * - **Last Updated**
         - None
       * - **Creator**
         - https://orcid.org/0000-0002-3717-7104,https://orcid.org/0000-0002-7094-5371
       * - **License**
         - Creative Commons Attribution 4.0 International (CC BY 4.0)
       * - **Format**
         - ttl
       * - **Download**
         - `Download Microscopy Ontology (MO) <https://github.com/materialdigital/microscopy-ontology?tab=readme-ov-file>`_

Microscopy Ontology (MO)
========================================================================================================

The Microscopy Ontology (MO) is a domain ontology developed to provide a
structured framework for describing microscopy and microanalysis
experiments, data, and equipment. It extends the PMD Core Ontology
(PMDco) and was developed within the Platform MaterialDigital ecosystem
to support semantic integration and interoperability of microscopy data
[#mo-repo]_ [#mo-paper]_. The ontology covers microscopy-specific
concepts and relationships needed to describe processes, equipment, and
parameters in microscopy and microanalysis workflows [#mo-paper]_
[#mo-overview]_. MO is intended to improve the semantic representation
of microscopy knowledge and support better query results and logical
linking among related terms and data objects [#mo-paper]_ [#mo-repo]_.
By providing a standardized vocabulary grounded in PMDco, the ontology
supports interoperable data description and integration across
materials-science microscopy datasets and related digital research
infrastructures [#mo-overview]_ [#pmdco-paper]_.

**Example Usage**: Annotate a microscopy dataset with MO terms to specify
the imaging modality (for example scanning electron microscopy or
transmission electron microscopy), relevant equipment and parameters,
sample-related descriptors, and analysis-related concepts, enabling
semantic search, interoperable data integration, and improved querying
across microscopy data sources [#mo-paper]_ [#mo-repo]_.

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

.. tab:: Graph


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

        * - **Total Nodes**
          - 931
        * - **Total Edges**
          - 1776
        * - **Root Nodes**
          - 10
        * - **Leaf Nodes**
          - 693
    ::


.. tab:: Coverage


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

        * - **Classes**
          - 217
        * - **Individuals**
          - 0
        * - **Properties**
          - 3

    ::

.. tab:: Hierarchy


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

        * - **Maximum Depth**
          - 1
        * - **Minimum Depth**
          - 0
        * - **Average Depth**
          - 0.09
        * - **Depth Variance**
          - 0.08
    ::


.. tab:: Breadth


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

        * - **Maximum Breadth**
          - 10
        * - **Minimum Breadth**
          - 1
        * - **Average Breadth**
          - 5.50
        * - **Breadth Variance**
          - 20.25
    ::

.. tab:: LLMs4OL


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

        * - **Term Types**
          - 0
        * - **Taxonomic Relations**
          - 130
        * - **Non-taxonomic Relations**
          - 0
        * - **Average Terms per Type**
          - 0.00
    ::

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

.. code-block:: python

    from ontolearner.ontology import MO

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

References
----------

.. [#mo-paper] Bayerlein, B., Schilling, M., Curran, M., and Lau, J. W.
   2024. "Natural Language Processing-Driven Microscopy Ontology
   Development."
   *Integrating Materials and Manufacturing Innovation*.
   doi:10.1007/s40192-024-00378-y

.. [#mo-repo] materialdigital. n.d. "Microscopy Ontology (MO)."
   GitHub repository.
   Available at: `https://github.com/materialdigital/microscopy-ontology <https://github.com/materialdigital/microscopy-ontology>`_

.. [#mo-overview] Bayerlein, B., Schilling, M., Bruns, S., and others.
   2024. "Concepts for a Semantically Accessible Materials Data Space:
   Overview over Specific Implementations in Materials Science."
   *Advanced Engineering Materials*.
   Available at: `https://advanced.onlinelibrary.wiley.com/doi/10.1002/adem.202401092 <https://advanced.onlinelibrary.wiley.com/doi/10.1002/adem.202401092>`_

.. [#pmdco-paper] Schilling, M., Bayerlein, B., Birkholz, H., and others.
   2024. "PMD Core Ontology: Achieving Semantic Interoperability in
   Materials Science."
   *Materials & Design* 237: 112563.