s1) (EISPP_3_M_Fernandez_NLQ_2_OB)

We can also select one of the ontologies and perform a query using a triple pattern with terms from the ontology.
Using a method from the paper, "An Intelligent Query Interface Based on Ontology Navigation" by Enrico Franconi et 
al. We can browse the ontology to construct a query with no former knowledge of the ontology.

s2) (EISPP_3_M_Fernandez_NLQ_2_OB_b4subs)

We can start by clicking the OB button and then select the ontology we wish to query the RDF data with. In this case, we will select
the ontology with the Car_partOf prefix, which is referenced in the panel on the right hand side.

s3) (EISPP_3_M_Fernandez_NLQ_2_OB_subs2)

We can browse the menu to substitute Car for the generic Web Ontology Language class Thing.

s4) (EISPP_3_M_Fernandez_NLQ_2_OB_subs3)

Then I can select and add the hasPart_directly property in the Domain of Car.

s5) (EISPP_3_M_Fernandez_NLQ_2_OB_subs4)

Then I can select and add the headlight_of_car class in the domain of car and range of hasPart_directly.

s6) (EISPP_3_M_Fernandez_NLQ_2_OB_subs5)

I may want to weaken the property between Car and headlight_of_car to be less exclusive. By clicking weaken I get hasPart instead of hasPart_directly.

s7) (EISPP_3_M_Fernandez_NLQ_2_OB_subs6)

In can also substitute the Reflector class for headlight_of_car class.

s8) (EISPP_3_M_Fernandez_NLQ_2_OB_subs6_and_one_half)

Finally, clicking the query button allows me to execute the query.

s9) (EISPP_3_M_Fernandez_NLQ_2_OB_subs7)

This gives me three triples with six additional linked data triples related by the rdf:type property.

s10) (EISPP_3_M_Fernandez_NLQ_2_OB_subs8_back6)

I can also click the back button at the top of the screen to get back to the view before the query.

s11) (EISPP_3_M_Fernandez_NLQ_2_OB_subs9_delete)

Finally, clicking the delete button gets me back to specifying only the first class of the triple.

References Include:

Enrico Franconi et al., An Intelligent Query Interface Based on Ontology Navigation, Workshop on Visual Interfaces to the Social and Semantic Web (VISSW2010) , Hong Kong, China. http://ceur-ws.org/Vol-565/paper3.pdf