OntoEnv is a simple tool for managing a collection of ontology definitions (instances of owl:Ontology) and dependencies (owl:imports statements). This is functionality that is often provided by modeling IDEs such as Protégé and TopBraid Composer, but seems currently lacking in the Python/RDFlib ecosystem. Once initialized in a directory, OntoEnv will search for all RDF files and resolve their owl:imports statements, downloading remote files or resolving from local definitions as needed.

OntoEnv provides Python bindings which will import the ontology definitions for all owl:imports statements into an rdflib.Graph.

Typical Usage

Typical usage looks as follows.

First, tell OntoEnv to figure out the dependency graph and cache the ontology/graph definitions.

$ ontoenv init # resolving imports can take a few seconds, depending on the number of dependencies
$ ontoenv refresh # run 'refresh' if any dependencies change

Then, use the Python bindings to import ontology definitions into a graph

import rdflib
import ontoenv

# initialize environment
env = ontoenv.OntoEnv()

g = rdflib.Graph()
g.parse("my_graph.ttl", format="ttl")

Other commands:

  • dump: print the locations of all URIs known by ontoenv


pip install ontoenv


An RDF graph can be associated with a URI by including a statement in the graph that the URI is an instance of owl:Ontology.

@prefix owl:  .

 a owl:Ontology .
# ... other triples

Other RDF graphs can import the contents of http://example.com/my/graph in their own owl:Ontology definitions:

@prefix owl:  .

 a owl:Ontology ;
    owl:imports  .

OntoEnv has the option of transitively resolving these dependencies.