minimalKB is a SQLite-backed minimalistic knowledge base, initially designed for robots (in particular human-robot interaction or multi-robot interaction).

It stores triples (like RDF/OWL triples), and provides a mostly conformant KB-API API accessible via a simple socket protocol.

pykb provides an idiomatic Python binding, making easy to integrate the knowledge base in your applications.

It has almost no features, except it is fast and simple. Basic RDFS reasoning is provided (cf below for details).

Written in Python. The only required dependency is sqlite3. If rdflib is also available, you can easily import existing ontologies in RDF/OWL/n3/Turtle formats in the knowledge base.

$ git clone https://github.com/severin-lemaignan/minimalkb.git
$ cd minimalkb
$ python setup.py install
$ minimalkb

Run minimalkb --help for available options.

minimalKB can be run as a stand-alone (socket) server, or directly embedded in Python applications.

minimalKB is intended for dynamic environments, with possibly several contexts/agents requiring separate knowledge models.

New models can be created at any time and each operation (like knowledge addition/retractation/query) can operate on a specific subset of models.

Each models are also independently classified by the reasoner.

minimalKB provides a mechanism to subscribe to some conditions (like: an instance of a given type is added to the knowledge base, some statement becomes true, etc.) and get notified back.

minimalKB only provides basic RDFS/OWL reasoning capabilities:

• it honors the transitive closure of the rdfs:subClassOf relation.
• functional predicates (child of owl:functionalProperty) are properly handled when updating the model (ie, if <S P O> is asserted with P a functional predicate, updating the model with <S P O'> will first cause <S P O> to be retracted).
• owl:equivalentClass is properly handled.

The reasoner runs in its own thread, and classify the model at a given rate, by default 5Hz. It is thus needed to wait ~200ms before the results of the classification become visible in the model.

minimalKB allows to attach 'lifespans' to statements: after a given duration, they are automatically collected.

minimalKB exposes several methods to explore the different ontological models of the knowledge base. It is compatible with the visualization tool oro-view.