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|
/*
* Copyright 2020, 2021 KRR Oxford
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package uk.ac.ox.cs.rsacomb
/* Java imports */
import java.{util => ju}
import java.util.HashMap
import java.util.stream.{Collectors, Stream}
import java.io.File
import org.semanticweb.owlapi.apibinding.OWLManager
import org.semanticweb.owlapi.util.OWLOntologyMerger
import org.semanticweb.owlapi.model.{OWLOntology, OWLAxiom, OWLLogicalAxiom}
import org.semanticweb.owlapi.model.{
OWLClass,
OWLClassExpression,
OWLDataProperty,
OWLDataPropertyAssertionAxiom,
OWLObjectProperty,
OWLSubObjectPropertyOfAxiom,
OWLObjectPropertyExpression,
OWLObjectSomeValuesFrom,
OWLDataSomeValuesFrom,
OWLSubClassOfAxiom
}
import org.semanticweb.owlapi.model.parameters.Imports
import org.semanticweb.owlapi.reasoner.structural.StructuralReasonerFactory
import uk.ac.manchester.cs.owl.owlapi.OWLObjectPropertyImpl
import tech.oxfordsemantic.jrdfox.client.{
DataStoreConnection,
TransactionType,
UpdateType
}
import tech.oxfordsemantic.jrdfox.Prefixes
import tech.oxfordsemantic.jrdfox.logic.datalog.{
BodyFormula,
FilterAtom,
Negation,
Rule,
TupleTableAtom,
TupleTableName
}
import tech.oxfordsemantic.jrdfox.logic.expression.{
FunctionCall,
IRI,
Literal,
Resource,
Term,
Variable
}
import tech.oxfordsemantic.jrdfox.logic.sparql.statement.SelectQuery
/* Scala imports */
import scala.util.{Try, Success, Failure}
import scala.collection.JavaConverters._
import scala.collection.mutable.{Set, Map}
import scalax.collection.Graph
import scalax.collection.GraphPredef._, scalax.collection.GraphEdge._
/* Debug only */
import org.semanticweb.owlapi.dlsyntax.renderer.DLSyntaxObjectRenderer
import tech.oxfordsemantic.jrdfox.logic._
import org.semanticweb.owlapi.model.OWLObjectInverseOf
import uk.ac.ox.cs.rsacomb.approximation.Approximation
import uk.ac.ox.cs.rsacomb.converter._
import uk.ac.ox.cs.rsacomb.filtering.{FilteringProgram, FilterType}
import uk.ac.ox.cs.rsacomb.suffix._
import uk.ac.ox.cs.rsacomb.sparql._
import uk.ac.ox.cs.rsacomb.util.{RDFoxUtil, RSA}
import uk.ac.ox.cs.rsacomb.util.Logger
import uk.ac.ox.cs.rsacomb.ontology.Ontology
object RSAOntology {
import uk.ac.ox.cs.rsacomb.implicits.JavaCollections._
/** Manager instance to interface with OWLAPI */
val manager = OWLManager.createOWLOntologyManager()
/** Name of the RDFox data store used for CQ answering */
private val DataStore = "answer_computation"
/** Canonical model named graph */
private val CanonGraph: IRI =
RDFoxUtil.getNamedGraph(DataStore, "CanonicalModel")
/** Filtering program named graph
*
* @param query query associated with the returned named graph.
*
* @return named graph for the filtering program associated with the
* input query.
*/
private def FilterGraph(query: ConjunctiveQuery): IRI =
RDFoxUtil.getNamedGraph(DataStore, s"Filter${query.id}")
/** Filtering program for a given query
*
* @param query the query to derive the filtering program
* @return the filtering program for the given query
*/
def filteringProgram(query: ConjunctiveQuery): FilteringProgram =
Logger.timed(
{
val filter = FilteringProgram(FilterType.REVISED)
filter(CanonGraph, FilterGraph(query), query)
},
"Generating filtering program",
Logger.DEBUG
)
def apply(
origin: OWLOntology,
axioms: List[OWLLogicalAxiom],
datafiles: List[os.Path]
): RSAOntology = new RSAOntology(origin, axioms, datafiles)
// def apply(
// ontofile: File,
// datafiles: List[File],
// approx: Option[Approximation]
// ): RSAOntology = {
// val ontology = manager.loadOntologyFromOntologyDocument(ontofile)
// RSAOntology(ontology, datafiles, approx)
// }
// def apply(
// ontology: OWLOntology,
// datafiles: List[File],
// approx: Option[Approximation]
// ): RSAOntology = {
// val normalizer = new Normalizer()
// /** TBox axioms */
// var tbox: List[OWLLogicalAxiom] =
// ontology
// .tboxAxioms(Imports.INCLUDED)
// .collect(Collectors.toList())
// .collect { case a: OWLLogicalAxiom => a }
// .flatMap(normalizer.normalize)
// /** RBox axioms */
// var rbox: List[OWLLogicalAxiom] =
// ontology
// .rboxAxioms(Imports.INCLUDED)
// .collect(Collectors.toList())
// .collect { case a: OWLLogicalAxiom => a }
// .flatMap(normalizer.normalize)
// /** ABox axioms
// *
// * @note this represents only the set of assertions contained in the
// * ontology file. Data files specified in `datafiles` are directly
// * imported in RDFox due to performance issues when trying to import
// * large data files via OWLAPI.
// */
// var abox: List[OWLLogicalAxiom] =
// ontology
// .aboxAxioms(Imports.INCLUDED)
// .collect(Collectors.toList())
// .collect { case a: OWLLogicalAxiom => a }
// .flatMap(normalizer.normalize)
// /** Collection of logical axioms in the input ontology */
// var axioms: List[OWLLogicalAxiom] = abox ::: tbox ::: rbox
// new RSAOntology(
// approx match {
// case Some(a) => a.approximate(axioms, datafiles)
// case None => axioms
// },
// datafiles: _*
// )
// }
}
/** A wrapper for an RSA ontology
*
* @param ontology the input OWL2 ontology.
* @param datafiles additinal data (treated as part of the ABox)
*/
class RSAOntology(
origin: OWLOntology,
axioms: List[OWLLogicalAxiom],
datafiles: List[os.Path]
) extends Ontology(origin, axioms, datafiles) {
/** Simplify conversion between OWLAPI and RDFox concepts */
import implicits.RDFox._
import uk.ac.ox.cs.rsacomb.implicits.RSAAxiom._
/** Simplify conversion between Java and Scala collections */
import uk.ac.ox.cs.rsacomb.implicits.JavaCollections._
/** Set of axioms removed during the approximation to RSA */
//private var removed: Seq[OWLAxiom] = Seq.empty
/** Retrieve individuals/literals in the ontology */
private val individuals: List[IRI] =
ontology
.getIndividualsInSignature()
.asScala
.map(_.getIRI)
.map(implicits.RDFox.owlapiToRdfoxIri)
.toList
private val literals: List[Literal] =
axioms
.collect { case a: OWLDataPropertyAssertionAxiom => a }
.map(_.getObject)
.map(implicits.RDFox.owlapiToRdfoxLiteral)
/** Retrieve concepts/roles in the ontology */
val concepts: List[OWLClass] =
ontology.getClassesInSignature().asScala.toList
val objroles: List[OWLObjectPropertyExpression] =
axioms.flatMap(_.objectPropertyExpressionsInSignature).distinct
val dataroles: List[OWLDataProperty] = origin.getDataPropertiesInSignature
/** Unsafe roles of a given ontology.
*
* Unsafety conditions are the following:
*
* 1) For all roles r1 appearing in an axiom of type T5, r1 is unsafe
* if there exists a role r2 (different from top) appearing in an
* axiom of type T3 and r1 is a subproperty of the inverse of r2.
*
* 2) For all roles p1 appearing in an axiom of type T5, p1 is unsafe
* if there exists a role p2 appearing in an axiom of type T4 and
* p1 is a subproperty of either p2 or the inverse of p2.
*/
// val unsafeRoles: List[OWLObjectPropertyExpression] = {
// /* Checking for unsafety condition (1) */
// val unsafe1 = for {
// axiom <- axioms
// if axiom.isT5
// role1 <- axiom.objectPropertyExpressionsInSignature
// roleSuper = role1 +: reasoner.superObjectProperties(role1)
// roleSuperInv = roleSuper.map(_.getInverseProperty)
// axiom <- axioms
// if axiom.isT3 && !axiom.isT3top
// role2 <- axiom.objectPropertyExpressionsInSignature
// if roleSuperInv contains role2
// } yield role1
// /* Checking for unsafety condition (2) */
// val unsafe2 = for {
// axiom <- axioms
// if axiom.isT5
// role1 <- axiom.objectPropertyExpressionsInSignature
// roleSuper = role1 +: reasoner.superObjectProperties(role1)
// roleSuperInv = roleSuper.map(_.getInverseProperty)
// axiom <- axioms
// if axiom.isT4
// role2 <- axiom.objectPropertyExpressionsInSignature
// if roleSuper.contains(role2) || roleSuperInv.contains(role2)
// } yield role1
// unsafe1 ++ unsafe2
// }
/** Approximate a Horn-ALCHOIQ ontology to RSA
*
* This is done by gathering those axioms that prevent the ontology
* dependency graph `dependencyGraph` from being tree-shaped, and
* removing them.
*
* @param graph the graph used to compute the axioms to remove.
* @param nodemap map from graph nodes to ontology axioms.
*/
// def toRSA(): RSAOntology = Logger.timed(
// {
// /* Compute the dependency graph for the ontology */
// val (graph, nodemap) = this.dependencyGraph()
// /* Define node colors for the graph visit */
// sealed trait NodeColor
// case object Unvisited extends NodeColor
// case object Visited extends NodeColor
// case object ToDelete extends NodeColor
// /* Keep track of node colors during graph visit */
// var color = Map.from[Resource, NodeColor](
// graph.nodes.toOuter.map(k => (k, Unvisited))
// )
// for {
// component <- graph.componentTraverser().map(_ to Graph)
// edge <- component
// .outerEdgeTraverser(component.nodes.head)
// .withKind(BreadthFirst)
// } yield {
// val source = edge._1
// val target = edge._2
// color(source) match {
// case Unvisited | Visited => {
// color(target) match {
// case Unvisited =>
// color(source) = Visited;
// color(target) = Visited
// case Visited =>
// color(source) = ToDelete
// case ToDelete =>
// color(source) = Visited
// }
// }
// case ToDelete =>
// }
// }
// val toDelete = color.iterator.collect { case (resource: IRI, ToDelete) =>
// nodemap(resource.getIRI)
// }.toSeq
// /* Remove axioms from approximated ontology */
// ontology.removeAxioms(toDelete: _*)
// this.removed = toDelete
// /* Return RSA ontology */
// RSAOntology(ontology, datafiles: _*)
// },
// "Horn-ALCHOIQ to RSA approximation:",
// Logger.DEBUG
// )
// val edges1 = Seq('A ~> 'B, 'B ~> 'C, 'C ~> 'D, 'D ~> 'H, 'H ~>
// 'G, 'G ~> 'F, 'E ~> 'A, 'E ~> 'F, 'B ~> 'E, 'F ~> 'G, 'B ~> 'F,
// 'C ~> 'G, 'D ~> 'C, 'H ~> 'D)
// val edges2 = Seq('I ~> 'M, 'I ~> 'L, 'L ~> 'N, 'M ~> 'N)
// val edges3 = Seq('P ~> 'O)
// val graph = Graph.from(edges = edges1 ++ edges2 ++ edges3)
/** Top axiomatization rules
*
* For each concept/role *in the ontology file* introduce a rule to
* derive `owl:Thing`.
*
* @note this might not be enough in cases where data files contain
* concept/roles that are not in the ontology file. While this is
* non-standard, it is not forbidden either and may cause problems
* since not all individuals are considered part of `owl:Thing`.
*
* @note this is a naïve implementation of top axiomatization and
* might change in the future. The ideal solution would be for RDFox
* to take care of this, but at the time of writing this is not
* compatible with the way we are using the tool.
*/
private val topAxioms: List[Rule] = {
val varX = Variable.create("X")
val varY = Variable.create("Y")
val varZ = Variable.create("Z")
val graph = TupleTableName.create(RSAOntology.CanonGraph.getIRI)
Rule.create(
TupleTableAtom.create(graph, varX, IRI.RDF_TYPE, IRI.THING),
TupleTableAtom.create(graph, varX, IRI.RDF_TYPE, varY)
) :: objroles.map(r => {
val name = r match {
case x: OWLObjectProperty => x.getIRI.getIRIString
case x: OWLObjectInverseOf =>
x.getInverse.getNamedProperty.getIRI.getIRIString :: Inverse
}
Rule.create(
List(
TupleTableAtom.create(graph, varX, IRI.RDF_TYPE, IRI.THING),
TupleTableAtom.create(graph, varY, IRI.RDF_TYPE, IRI.THING)
),
List(TupleTableAtom.create(graph, varX, name, varY))
)
}) ::: dataroles.map(r => {
val name = r.getIRI.getIRIString
Rule.create(
List(
TupleTableAtom.create(graph, varX, IRI.RDF_TYPE, IRI.THING),
TupleTableAtom.create(graph, varY, IRI.RDF_TYPE, IRI.THING)
),
List(TupleTableAtom.create(graph, varX, name, varY))
)
})
}
/** Equality axiomatization rules
*
* Introduce reflexivity, simmetry and transitivity rules for a naïve
* equality axiomatization.
*
* @note that we are using a custom `congruent` predicate to indicate
* equality. This is to avoid interfering with the standard
* `owl:sameAs`.
*
* @note RDFox is able to handle equality in a "smart" way, but this
* behaviour is incompatible with other needed features like
* negation-as-failure and aggregates.
*
* @todo naïve substitution rules might not be very efficient. We
* should look into other ways of implementing this.
*/
private val equalityAxioms: List[Rule] = {
val varX = Variable.create("X")
val varY = Variable.create("Y")
val varZ = Variable.create("Z")
val varW = Variable.create("W")
val graph = TupleTableName.create(RSAOntology.CanonGraph.getIRI)
// Equality properties
val properties = List(
// Reflexivity
Rule.create(
TupleTableAtom.create(graph, varX, RSA.CONGRUENT, varX),
TupleTableAtom.create(graph, varX, IRI.RDF_TYPE, IRI.THING)
),
// Simmetry
Rule.create(
TupleTableAtom.create(graph, varY, RSA.CONGRUENT, varX),
TupleTableAtom.create(graph, varX, RSA.CONGRUENT, varY)
),
// Transitivity
Rule.create(
TupleTableAtom.create(graph, varX, RSA.CONGRUENT, varZ),
TupleTableAtom.create(graph, varX, RSA.CONGRUENT, varY),
TupleTableAtom.create(graph, varY, RSA.CONGRUENT, varZ)
)
)
/* Equality substitution rules */
val substitutions =
Rule.create(
TupleTableAtom.create(graph, varY, IRI.RDF_TYPE, varZ),
TupleTableAtom.create(graph, varX, RSA.CONGRUENT, varY),
TupleTableAtom.create(graph, varX, IRI.RDF_TYPE, varZ)
) :: objroles.flatMap(r => {
val name = r match {
case x: OWLObjectProperty => x.getIRI.getIRIString
case x: OWLObjectInverseOf =>
x.getInverse.getNamedProperty.getIRI.getIRIString :: Inverse
}
List(
Rule.create(
TupleTableAtom.create(graph, varZ, name, varY),
TupleTableAtom.create(graph, varX, RSA.CONGRUENT, varZ),
TupleTableAtom.create(graph, varX, name, varY)
),
Rule.create(
TupleTableAtom.create(graph, varY, name, varZ),
TupleTableAtom.create(graph, varX, RSA.CONGRUENT, varZ),
TupleTableAtom.create(graph, varY, name, varX)
)
)
})
properties ++ substitutions
}
/** Canonical model of the ontology */
lazy val canonicalModel = Logger.timed(
new CanonicalModel(this, RSAOntology.CanonGraph),
"Generating canonical model program",
Logger.DEBUG
)
/** Computes all roles conflicting with a given role
*
* @param role a role (object property expression).
* @return a set of roles conflicting with `role`.
*/
def confl(
role: OWLObjectPropertyExpression
): Set[OWLObjectPropertyExpression] = {
reasoner
.superObjectProperties(role)
.collect(Collectors.toSet())
.asScala
.addOne(role)
.map(_.getInverseProperty)
.flatMap(x =>
reasoner
.subObjectProperties(x)
.collect(Collectors.toSet())
.asScala
.addOne(x)
)
.filterNot(_.isOWLBottomObjectProperty())
.filterNot(_.getInverseProperty.isOWLTopObjectProperty())
}
/** Selfloop detection for a given axiom
*
* @param axiom an axiom of type [[OWLSubClassOfAxiom]]
* @return unfold set for the axiom
*/
def self(axiom: OWLSubClassOfAxiom): Set[Term] = {
val role = axiom.objectPropertyExpressionsInSignature(0)
if (this.confl(role).contains(role)) {
Set(RSA("v0_" ++ axiom.hashed), RSA("v1_" ++ axiom.hashed))
} else {
Set()
}
}
/** Cycle detection for a give axiom
*
* @param axiom an axiom of type [[OWLSubClassOfAxiom]]
* @return unfold set for the axiom
*
* @todo we can actually use `toTriple` from `RSAAxiom` to get the
* classes and the role for a given axiom
*/
def cycle(axiom: OWLSubClassOfAxiom): Set[Term] = {
val classes =
axiom.classesInSignature.collect(Collectors.toList()).asScala
val classA = classes(0)
val roleR = axiom
.objectPropertyExpressionsInSignature(0)
.asInstanceOf[OWLObjectProperty]
val classB = classes(1)
cycle_aux(classA, roleR, classB)
}
/** Auxiliary function for [[RSAOntology.cycle]] */
private def cycle_aux(
classA: OWLClass,
roleR: OWLObjectProperty,
classB: OWLClass
): Set[Term] = {
val conflR = this.confl(roleR)
// TODO: technically we just need the TBox here
val terms = for {
axiom1 <- axioms
if axiom1.isT5
// We expect only one role coming out of a T5 axiom
roleS <- axiom1.objectPropertyExpressionsInSignature
// Triples ordering is among triples involving safe roles.
if !unsafe.contains(roleS)
if conflR.contains(roleS)
tripleARB = RSAAxiom.hashed(classA, roleR, classB)
tripleDSC = axiom1.hashed
individual =
if (tripleARB > tripleDSC) {
RSA("v1_" ++ tripleDSC)
} else {
// Note that this is also the case for
// `tripleARB == tripleDSC`
RSA("v0_" ++ tripleDSC)
}
} yield individual
terms to Set
}
/** Returns unfold set for self-loop and cycle for the input axiom
*
* @param axiom an axiom of type [[OWLSubClassOfAxiom]]
* @return unfold set for the axiom
*/
def unfold(axiom: OWLSubClassOfAxiom): Set[Term] =
this.self(axiom) | this.cycle(axiom)
/** Returns the answers to a single query
*
* @param queries a sequence of conjunctive queries to answer.
* @return a collection of answers for each query.
*/
def ask(query: ConjunctiveQuery): ConjunctiveQueryAnswers = this._ask(query)
/** Returns the answers to a collection of queries
*
* @param queries a sequence of conjunctive queries to answer.
* @return a collection of answers for each query.
*/
def ask(queries: Seq[ConjunctiveQuery]): Seq[ConjunctiveQueryAnswers] =
queries map _ask
private lazy val _ask: ConjunctiveQuery => ConjunctiveQueryAnswers = {
val (server, data) = RDFoxUtil.openConnection(RSAOntology.DataStore)
/* Upload data from data file */
RDFoxUtil.addData(data, RSAOntology.CanonGraph, datafiles: _*)
/* Top/equality axiomatization */
RDFoxUtil.addRules(data, topAxioms ++ equalityAxioms)
Logger.write(topAxioms.mkString("\n"), "canonical_model.datalog")
Logger.write(equalityAxioms.mkString("\n"), "canonical_model.datalog")
/* Introduce `rsacomb:Named` concept */
data.evaluateUpdate(
null, // the base IRI for the query (if null, a default is used)
RSA.Prefixes,
s"""
INSERT {
GRAPH ${RSAOntology.CanonGraph} { ?X a ${RSA.NAMED} }
} WHERE {
GRAPH ${RSAOntology.CanonGraph} { ?X a ${IRI.THING} }
}
""",
new java.util.HashMap[String, String]
)
/* Add canonical model */
Logger print s"Canonical model facts: ${this.canonicalModel.facts.length}"
RDFoxUtil.addFacts(data, RSAOntology.CanonGraph, this.canonicalModel.facts)
Logger print s"Canonical model rules: ${this.canonicalModel.rules.length}"
Logger.write(canonicalModel.rules.mkString("\n"), "canonical_model.datalog")
RDFoxUtil.addRules(data, this.canonicalModel.rules)
RDFoxUtil.closeConnection(server, data)
(query => {
val (server, data) = RDFoxUtil.openConnection(RSAOntology.DataStore)
val filter = RSAOntology.filteringProgram(query)
/* Add filtering program */
Logger print s"Filtering program rules: ${filter.rules.length}"
Logger.write(filter.rules.mkString("\n"), s"filter${query.id}.datalog")
RDFoxUtil.addRules(data, filter.rules)
// TODO: We remove the rules, should we drop the tuple table as well?
data.clearRulesAxiomsExplicateFacts()
/* Gather answers to the query */
val answers = RDFoxUtil
.submitQuery(data, filter.answerQuery, RSA.Prefixes)
.map(new ConjunctiveQueryAnswers(query, query.variables, _))
.get
RDFoxUtil.closeConnection(server, data)
answers
})
}
//def ask(query: ConjunctiveQuery): ConjunctiveQueryAnswers = Logger.timed(
// {
// val (server, data) = RDFoxUtil.openConnection(RSAOntology.DataStore)
// val canon = this.canonicalModel
// val filter = RSAOntology.filteringProgram(query)
// /* Upload data from data file */
// RDFoxUtil.addData(data, datafiles: _*)
// RDFoxUtil printStatisticsFor data
// /* Top / equality axiomatization */
// RDFoxUtil.addRules(data, topAxioms ++ equalityAxioms)
// /* Generate `named` predicates */
// RDFoxUtil.addFacts(data, (individuals ++ literals) map RSA.Named)
// data.evaluateUpdate(
// null, // the base IRI for the query (if null, a default is used)
// RSA.Prefixes,
// "INSERT { ?X a rsa:Named } WHERE { ?X a owl:Thing }",
// new java.util.HashMap[String, String]
// )
// /* Add canonical model */
// Logger print s"Canonical model rules: ${canon.rules.length}"
// RDFoxUtil.addRules(data, canon.rules)
// Logger print s"Canonical model facts: ${canon.facts.length}"
// RDFoxUtil.addFacts(data, canon.facts)
// RDFoxUtil printStatisticsFor data
// //{
// // import java.io.{PrintStream, FileOutputStream, File}
// // val rules1 = new FileOutputStream(new File("rules1-lubm200.dlog"))
// // val facts1 = new FileOutputStream(new File("facts1-lubm200.ttl"))
// // RDFoxUtil.export(data, rules1, facts1)
// // val rules2 = new PrintStream(new File("rules2-q34.dlog"))
// // rules2.print(filter.rules.mkString("\n"))
// //}
// /* Add filtering program */
// Logger print s"Filtering program rules: ${filter.rules.length}"
// RDFoxUtil.addRules(data, filter.rules)
// RDFoxUtil printStatisticsFor data
// /* Gather answers to the query */
// val answers = {
// val ans = filter.answerQuery
// RDFoxUtil
// .submitQuery(data, ans, RSA.Prefixes)
// .map(new ConjunctiveQueryAnswers(query, query.variables, _))
// .get
// }
// RDFoxUtil.closeConnection(server, data)
// answers
// },
// "Answers computation",
// Logger.DEBUG
//)
/** Query the RDFox data store used for query answering.
*
* @note This method does not add any facts or rules to the data
* store. It is most useful after the execution of a query using
* [[RSAOntology.ask]].
*
* @param query query to be executed against the environment
* @param prefixes additional prefixes for the query. It defaults to
* an empty set.
* @param opts additional options to RDFox.
* @return a collection of answers to the input query.
*
* @note This method has been introduced mostly for debugging purposes.
*/
def queryDataStore(
query: String,
prefixes: Prefixes = new Prefixes(),
opts: ju.Map[String, String] = new ju.HashMap[String, String]()
): Option[Seq[(Long, Seq[Resource])]] = {
val (server, data) = RDFoxUtil.openConnection(RSAOntology.DataStore)
val answers = RDFoxUtil.submitQuery(data, query, prefixes, opts)
RDFoxUtil.closeConnection(server, data)
answers
}
/** Returns set of unfiltered answers.
*
* This is equivalent to quering just the canonical model.
*
* @note this method does not load any data to RDFox. The return
* value is considered well defined only after
* [[uk.ac.ox.cs.rsacomb.RSAOntology.ask RSAOntology.ask]]
* for the corresponding query has been called.
*/
// def askUnfiltered(
// cq: ConjunctiveQuery
// ): Option[Seq[(Long, Seq[Resource])]] = {
// val query = RDFoxUtil.buildDescriptionQuery("QM", cq.variables.length)
// queryDataStore(query, RSA.Prefixes)
// }
}
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