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Current Release Version Test and Build Documentation Status PyPI License Code Style

ontor logo

ONTology editOR (ontor)

ontology editor built on Owlready2

functionality

each instance of the ontor class represents an individual ontology and provides support for:

  • creating new, loading existing, and saving ontologies
  • modifying ontologies:
    • import other ontologies
    • simply extract information such as axioms and class restrictions
    • insert classes, properties, instances, relations, and restrictions
    • insert general class axioms using a workaround for Owlready2
    • delete classes, properties, instances, relations, and restrictions but preserve the ontology's structure by reassigning subclasses and instances appropriately
  • reasoning over ontologies and debugging by interactively deleting problematic axioms
  • visualizing the entire ontology or selected parts thereof

ontor provides a tuple based syntax with JSON and CSV support for ontology editing to facilitate focusing on the ontology's content

requirements and installation

  • Python 3.9+
  • install ontor using pip
    • from PyPI: pip install ontor
    • from GitHub, in editable mode: pip install -e .
  • generate documentation via sphinx using the makefile in docs/: make html

demo

the directory example/ includes a demo application inspired by Protégé's pizza example

general class axioms

in addition to class axioms, General Class Axioms (GCAs) can express more complex statements - the generic axioms are equivalented using helper classes
in the example, a uniform price of 5 is set for all pizzas with seafood toppings without making use of an explicitly defined class for these pizzas:\

[
  ["has_topping",null,"min",1,"seafood_topping",null,null,null,null,null,null,null,true],
  ["has_price",null,"value",null,null,"float",null,null,5,null,null,null,true]
]

this allows a reasoner to infer that the price for all instances of seafood_pizza as well as for the instance Another_pizza is 5

interactive debugging

interactively debug an ontology
in the example: ontor3.debug_onto()

interactive ontology debugging

visualization

visualize selected instances, classes, and properties in a given radius around a focus node; e.g., all nodes in a radius of two relations around the node "John"
in the example: ontor3.visualize(classes=["human", "pizza"], properties=["likes", "diameter_in_cm"], focusnode="John", radius=2)

visualize selected ontology parts

workflow

When creating ontologies from scratch, note that some functions have to be called in a specific order:

  1. add_taxo - the taxonomy has to be created first to ensure that all classes are defined, which are required by the properties, axioms, and individuals
  2. add_ops, add_dps - properties must be defined before axioms can be specified
  3. add_axioms, add_gcas, add_instances - axioms and instances can only be added when all the necessary classes and properties have been defined

license

GPL v3.0

contact

Felix Ocker - [email protected]