Holger,
At the moment I'm adding my domain ontology and the OWL RL models into
an OntModel:
private OntModel model;
model = ModelFactory.createOntologyModel(OntModelSpec.OWL_MEM);
InputStream input = FileManager.get().open("/home/gerrit/code/
TBCFreeWorkspace/TopBraid/BondingDevice3.owl");
model.read(input,"http://sofia.gotdns.com/ontologies/
BondingDevice.owl");
model.read("http://topbraid.org/spin/owlrl-all";);
model.read("http://topbraid.org/spin/owlrl";);
and then invoke the inference engine:
SPINModuleRegistry.get().init();
model.addSubModel(newTriples);
SPINModuleRegistry.get().registerAll(model);
SPINInferences.run(model, newTriples, null, null, false, null);
System.out.println("Inferred SPIN triples: " + newTriples.size());
On each query to the triple store I first invoke the inferencing
engine and then add the new triples to the model:
SPINInferences.run(model, newTriples, null, null, false, null);
System.out.println("Inferred SPIN triples: " + newTriples.size());
model.addSubModel(newTriples);
Obviously this is horribly ineffective, but I can't quite follow your
explanation below on how to use a hash map to store or pre-compute the
rules.
Regards,
Gerrit
On Apr 6, 9:54 am, Holger Knublauch <[email protected]> wrote:
> On Apr 6, 2011, at 5:38 PM, Gerrit wrote:
>
> > It looks like the SPIN API performs a lock while reasoning, and has to
> > do this multiple times in order to perform all the inferments that is
> > produced by adding topbraid/spin/owlrl-all and topbraid/spin/owlrl.
>
> I am not aware of the SPIN API performing a lock. Do you have any insights as
> to which Java methods would do this?
>
>
>
> > Adding just those two files to the model creates 10491 inferred
> > triples. Is this the kind of behavior I should expect when using SPIN
> > rules to infer OWL2 RL?
>
> This depends on your set-up, i.e. how you invoke the inference engine. If you
> just put all triples including the OWL RL models into the same Jena Model,
> then the system will run inferences over all triples, including the OWL RL
> ontology, SPIN system triples etc. This will include a lot of uninteresting
> inferences and slow down the whole process.
>
> What I usually do is to create a Jena OntModel / MultiUnion graph that has
> the domain ontology as base graph, and the OWL RL models and other rule bases
> as "imports". Then it's possible to build up a complete list of available
> rules, and put it into a HashMap that is used as input to the actual
> inferencing step. The following code (from SPINInferences.run()) shows how to
> get those rules
>
> Map<CommandWrapper, Map<String,RDFNode>>
> initialTemplateBindings = new HashMap<CommandWrapper, Map<String,RDFNode>>();
> Map<Resource,List<CommandWrapper>> cls2Query =
> SPINQueryFinder.getClass2QueryMap(queryModel, queryModel, rulePredicate,
> true, initialTemplateBindings, false);
> Map<Resource,List<CommandWrapper>> cls2Constructor =
> SPINQueryFinder.getClass2QueryMap(queryModel, queryModel, SPIN.constructor,
> true, initialTemplateBindings, false);
> SPINRuleComparator comparator = new
> DefaultSPINRuleComparator(queryModel);
> return run(queryModel, newTriples, cls2Query,
> cls2Constructor, initialTemplateBindings, explanations, statistics,
> singlePass, rulePredicate, comparator, monitor);
>
> Then, the queryModel itself can be a sub-set of the whole union model. It
> could simply be the base model that you want to query. TopSPIN usually does
> this as well, and uses all spin:LibraryOntologies to collect the rules (and
> constraints) only, but ignores them in the query model. This way, you can
> even pre-compute all rules once and keep them in a HashMap for the life time
> of your application.
>
> I will try to clarify this with a fully worked out example for the next SPIN
> API release, but the ideas above may point you in the right direction in the
> meantime.
>
> Regards,
> Holger
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