You are only missing 2 steps on you fuseki config, then it can work:
1) you need to use OWL reasoner, not an empty rule reasoner
2) you need to define a SPARQL service for your dataset
here is the required changes in "git diff" format:
diff --git a/data/config.ttl b/data/config.ttl
index 69c9cba..4b77ce7 100644
--- a/data/config.ttl
+++ b/data/config.ttl
@@ -28,6 +28,16 @@
## --------------------------- Added ------------------------------------
+:service rdf:type fuseki:Service ;
+ rdfs:label "Pizza Ontology Reasoning" ;
+ fuseki:name "pizza" ;
+ fuseki:dataset :dataset ;
+
+ fuseki:endpoint [ fuseki:operation fuseki:query ] ;
+ fuseki:endpoint [ fuseki:operation fuseki:update ] ;
+ fuseki:endpoint [ fuseki:operation fuseki:gsp-rw ] ;
+ .
+
# Dataset with only the default graph.
:dataset rdf:type ja:RDFDataset ;
ja:defaultGraph :model_inf ;
@@ -37,7 +47,7 @@
:model_inf a ja:InfModel ;
ja:baseModel :tdbGraph ;
ja:reasoner [
- ja:reasonerURL
<http://jena.hpl.hp.com/2003/GenericRuleReasoner>
+ ja:reasonerURL <http://jena.hpl.hp.com/2003/OWLFBRuleReasoner>
] .
:tdbGraph rdf:type tdb2:GraphTDB2 ;
On Thu, 2023-02-16 at 19:35 +0100, Yang-Min KIM wrote:
> Dear Jena community,
>
> I tried with Jena API and it works!
> I still can't apply the ontology inference via Fuseki server's config
> file.
>
> I'm happy to share my repo on GitHub containing a complete report,
> data
> and (my first) Java code.
> <https://github.com/0m1n0/jena_reasoner>
>
> Thank you for your help.
> Min
>
> Le jeu., févr. 9 2023 at 18:17:48 +0100, Yang-Min KIM
> <[email protected]> a écrit :
> > Thank you for your reply!
> >
> > @Lorenz
> >
> > I tried all reasoners: Generic Rule Reasoner, Transitive Reasoner,
> > RDFS Rule Reasoner, Full OWL Reasoner, Mini OWL Reasoner, and Micro
> > OWL Reasoner.
> > <<
> > https://jena.apache.org/documentation/fuseki2/fuseki-configuration.
> > html>>
> > -> "Possible reasoners" section
> > But unfortunately it didn't work... What I did:
> >
> > for i in list_of_all_possible_reasoners:
> > - update reasonerURL in config.ttl (where the data location link in
> > TDB refers to
> > `/opt/tomcat/fuseki/base/databases/test_ontology_pizza`)
> > - restart server
> > - create new dataset and upload data as default graph with two
> > options:
> > 1. create two separated datasets where ontology data stored
> > in
> > `test_ontology_pizza` dataset and test data stored in `test_pizza`
> > dataset
> > 2. create one dataset `test_ontology_pizza` where both
> > ontology
> > data and test data are stored
> > - run SPARQL query -> check if it works
> > - remove created dataset(s)
> >
> >
> > @Steve
> >
> > I'm sure we can apply the inference model by customising via Java
> > but
> > unfortunately I don't code in Java...
> >
> >
> > Le jeu., févr. 9 2023 at 05:11:15 -0600, Steve Vestal
> > <[email protected] <mailto:[email protected]>> a écrit
> > :
> > > Are you trying to issue a SPARQL query against a knowledge base
> > > that
> > > includes inferred as well as explicitly asserted information,
> > > such
> > > as an inverse of an asserted property? You can do this by
> > > issuing
> > > a query to an OntModel using QueryExecution.create(String
> > > queryStr,
> > > Syntax lang, Model model). If anyone knows how to do this for a
> > > DataSet (TDP2), please let me know.
> > >
> > > On 2/8/2023 10:45 AM, Yang-Min KIM wrote:
> > > > Dear Jena community,
> > > >
> > > > As a beginner in Jena (and I do not code in Java), I would like
> > > > to
> > > > ask you a question about ontology integration.
> > > >
> > > > - Data: small test data and corresponding OWL ontology
> > > > - Method: put data into GraphDB and Jena servers then run
> > > > SPARQL
> > > > query
> > > > - Expected result: initial missing information is complemented
> > > > by
> > > > ontology transitivity
> > > >
> > > > I will describe you step by step, the questions will come at
> > > > the
> > > > end of the mail.
> > > >
> > > > ///////////////////////////// Report: what I did
> > > > /////////////////////////////
> > > >
> > > > 1. Test data: pizza!
> > > >
> > > > 1.1. Pizza ontology
> > > > As example, we use Pizza ontology provided by "OWL Example with
> > > > RDF
> > > > Graph"
> > > > <<<
> > > > https://www.obitko.com/tutorials/ontologies-semantic-web/owl-
> > > > example-with-rdf-graph.html>>>
> > > >
> > > > <<<
> > > > https://i.postimg.cc/ZRjJy7XQ/Capture-d-cran-du-2023-02-08-15-
> > > > 07-19.png>>>
> > > >
> > > > We focus on the inverse relationships: `:isIngredientOf
> > > > owl:inverseOf :hasIngredient .` i.e. the property
> > > > `isIngredientOf` is the inverse of the property
> > > > `hasIngredient`.
> > > > -------------------------------------------
> > > > :isIngredientOf
> > > > a owl:TransitiveProperty , owl:ObjectProperty ;
> > > > owl:inverseOf :hasIngredient .
> > > > -------------------------------------------
> > > >
> > > >
> > > > 1.2. Pizza data
> > > > Two pizza `Margherita` and `Cheese Bacon`: the relationship
> > > > between
> > > > a pizza and an ingredient is declared by the property either
> > > > `isIngredientOf` or `hasIngredient`. In summary:
> > > > - Margherita contains tomato and basilic
> > > > - Cheese Bacon contains cheese, bacon, and tomato
> > > >
> > > > -------------------------------------------
> > > > @prefix ex: <<http://example.com/>> .
> > > > @prefix pizza: <<http://example.com/pizzas.owl#>> .
> > > > @prefix rdf: <<http://www.w3.org/1999/02/22-rdf-syntax-ns#>> .
> > > >
> > > > # Margherita
> > > > ex:margherita rdf:type pizza:Pizza .
> > > > ex:margherita rdf:type pizza:VegetarianPizza .
> > > > ex:tomato pizza:isIngredientOf ex:margherita .
> > > > ex:margherita pizza:hasIngredient ex:basilic .
> > > >
> > > > # Cheese Bacon
> > > > ex:cheese_bacon rdf:type pizza:Pizza .
> > > > ex:cheese_bacon rdf:type pizza:NonVegetarianPizza .
> > > > ex:cheese pizza:isIngredientOf ex:cheese_bacon .
> > > > ex:cheese_bacon pizza:hasIngredient ex:bacon .
> > > > ex:cheese_bacon pizza:hasIngredient ex:tomato .
> > > > -------------------------------------------
> > > >
> > > >
> > > >
> > > > 2. GraphDB
> > > >
> > > > 2.1. Dataset (repository) creation:
> > > > <<<
> > > > https://i.postimg.cc/k5QJ7Xsq/Capture-d-cran-du-2023-02-08-15-
> > > > 09-15.png>>>
> > > > As shown in the image, the `RDFS-Plus (Optimized)` are set up
> > > > by
> > > > default when creating a repository (dataset in Jena term).
> > > >
> > > > 2.2. Upload test data
> > > > Both test data and ontology are uploaded in a same repository
> > > > (as
> > > > default or named graphes, results are unchanged).
> > > > <<<
> > > > https://i.postimg.cc/qq501tJX/Capture-d-cran-du-2023-02-08-15-
> > > > 06-01.png>>>
> > > > We can see reciprocal relationships between pizza and
> > > > ingredients
> > > > (`hasIngredient` and `isIngredientOf`).
> > > >
> > > > 2.3. SPARQL query
> > > > <<<
> > > > https://i.postimg.cc/KcqZGWPk/Capture-d-cran-du-2023-02-08-15-
> > > > 05-47.png>>>
> > > > Got expected results: all ingredients are presents i.e. initial
> > > > missing information is complemented: `ex:tomato
> > > > pizza:isIngredientOf ex:margherita` is equivalent to
> > > > `ex:margherita pizza:hasIngredient ex:tomato`
> > > >
> > > >
> > > >
> > > > 3. Jena
> > > >
> > > > 3.1. Dataset creation
> > > > Fuseki UI does not allow to set default reasoner as seen in
> > > > 2.1.
> > > > It would be awesome if we could specify at this step!
> > > >
> > > > 3.2. Upload test data
> > > > Each data is uploaded on TDB as default graph into:
> > > > - A same dataset
> > > > - Separated dataset
> > > >
> > > > 3.3. SPARQL query
> > > > <<<
> > > > https://i.postimg.cc/Fz0cXJzm/Capture-d-cran-du-2023-02-08-15-
> > > > 38-30.png>>>
> > > > Misisng relationships are still missing, e.g. tomato is missing
> > > > as
> > > > Margherita's ingredient.
> > > >
> > > > 3.4. Set inference model via config
> > > > According to your previous suggestions (thank you Dave and
> > > > Lorenz!), I have tried to follow the configuration steps
> > > > mentioned in Fuseki's configuration documentation.
> > > > <<<
> > > > https://jena.apache.org/documentation/fuseki2/fuseki-configurat
> > > > ion.html>>>
> > > > -> section "Inference"
> > > > I uploaded ontology file into a separated TDB dataset named
> > > > "test_ontology_pizza".
> > > > Then I modified Fuseki's `config.ttl` by adding the part after
> > > > ##
> > > > ----------- as below.
> > > > The results are the same as the previous ones despite
> > > > restarting
> > > > the server.
> > > >
> > > > -------------------------------------------
> > > > # Licensed under the terms of
> > > > <<<http://www.apache.org/licenses/LICENSE-2.0>>>
> > > >
> > > > ## Fuseki Server configuration file.
> > > >
> > > > @prefix : <#> .
> > > > @prefix fuseki: <<http://jena.apache.org/fuseki#>> .
> > > > @prefix rdf: <<http://www.w3.org/1999/02/22-rdf-syntax-ns#>> .
> > > > @prefix rdfs: <<http://www.w3.org/2000/01/rdf-schema#>> .
> > > > @prefix ja: <<http://jena.hpl.hp.com/2005/11/Assembler#>> .
> > > > @prefix tdb2: <<http://jena.apache.org/2016/tdb#>> .
> > > >
> > > > [] rdf:type fuseki:Server ;
> > > > # Example::
> > > > # Server-wide query timeout.
> > > > #
> > > > # Timeout - server-wide default: milliseconds.
> > > > # Format 1: "1000" -- 1 second timeout
> > > > # Format 2: "10000,60000" -- 10s timeout to first result,
> > > > # then 60s timeout for the rest of
> > > > query.
> > > > #
> > > > # See javadoc for ARQ.queryTimeout for details.
> > > > # This can also be set on a per dataset basis in the dataset
> > > > assembler.
> > > > #
> > > > # ja:context [ ja:cxtName "arq:queryTimeout" ; ja:cxtValue
> > > > "30000" ] ;
> > > >
> > > > # Add any custom classes you want to load.
> > > > # Must have a "public static void init()" method.
> > > > # ja:loadClass "your.code.Class" ;
> > > >
> > > > # End triples.
> > > > .
> > > >
> > > > ## --------------------------- Added
> > > > ------------------------------------
> > > >
> > > > # Dataset with only the default graph.
> > > > :dataset rdf:type ja:RDFDataset ;
> > > > ja:defaultGraph :model_inf ;
> > > > .
> > > >
> > > > # The inference model, data is taken from TDB
> > > > :model_inf a ja:InfModel ;
> > > > ja:baseModel :tdbGraph ;
> > > > ja:reasoner [
> > > > ja:reasonerURL
> > > > <<<<http://jena.hpl.hp.com/2003/RDFSExptRuleReasoner>>>>
> > > > ] .
> > > >
> > > > :tdbGraph rdf:type tdb2:GraphTDB2 ;
> > > > tdb2:dataset :tdbDataset .
> > > >
> > > > ## Base data in TDB.
> > > > :tdbDataset rdf:type tdb2:DatasetTDB2 ;
> > > > tdb2:location
> > > > "/opt/tomcat/fuseki/base/databases/test_ontology_pizza" ;
> > > > # If the unionDefaultGraph is used, then the "update"
> > > > service
> > > > should be removed.
> > > > # tdb:unionDefaultGraph true ;
> > > > .
> > > > -------------------------------------------
> > > >
> > > >
> > > > ///////////////////////////// Questions
> > > > /////////////////////////////
> > > >
> > > > Q1. Where and how should the data (pizza test data and pizza
> > > > ontology) be stored? Separated dataset? As default graph?
> > > >
> > > > Q2. Is it better to configure at the global server level
> > > > (congif.ttl) or dataset level (dataset_name.ttl) ?
> > > >
> > > > Q3. Should we restart tomcat or redeploy war each time we
> > > > update
> > > > gobal config or per dataset config ?
> > > >
> > > > Q4. I'm pretty sure there are errors in my configuration...,
> > > > but
> > > > where?
> > > >
> > > > Q5. Side question. Is it possible to trigger from command line
> > > > one
> > > > of those predefined rule engine () on a given dataset ?
> > > >
> > > >
> > > > Thank you for reading my long story and for your insights!
> > > >
> > > > Best Regards,
> > > > Min
> > > >
> > > >
> > > >
> >
>
