SPARQL Query Rewriting for Implementing Data Integration over Linked Data Gianluca Correndo, Manuel Salvadores, Ian Millard, Hugh Glaser, Nigel Shadbolt.

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SPARQL Query Rewriting for Implementing Data Integration over Linked Data Gianluca Correndo, Manuel Salvadores, Ian Millard, Hugh Glaser, Nigel Shadbolt

Linked Data access Retrieving RDF content via HTTP requests –Instance based vs. schema based access Accessing SPARQL endpoints –Schema based vs. instance based access 2 SPARQL+HTTP

Linked Data – Schema based integration 3 sourcetarget Data set Ontology(SPARQL) Query Co-reference OA = SO: Source Ontologies TO: Target Ontologies TD: Target Dataset EA: Entity Alignments Datasets can use more than one ontology for describing the data More than one dataset can use the same set of ontologies coherently (e.g. RKB) More than one ontology is used for defining a SPARQL query Ontologies contain many entities to be aligned

Query Rewriting Architecture 4 SPARQL query SPARQL query rewriter SPARQL query SPARQL query SPARQL query voiDAlignments

Ontology Alignment DL primitives are used to describe concept alignments (i.e. Equivalent, Subsume) –Implementation of the underneath ontological mediation usually not provided or relies on reasoners Ontological mediation usually applied to data, not queries –rule systems that exploit alignments to translate data –[Euzenat] SPARQL for integrating data CONSTRUCT { ?x rdf:type vc:VCard } WHERE { ?x rdf:type foaf:Person } How to write such queries? 5

Anatomy of a SPARQL query Query type: SELECT, DESCRIBE, CONSTRUCT, ASK Basic Graph Pattern (or BGP): graph pattern that resulting triples must satisfy Filter section: additional constraints over variables present in the BGP PREFIX id: PREFIX akt: SELECT DISTINCT ?a WHERE { ?paper akt:has-author id:person ?paper akt:has-author ?a. } 6

SPARQL BGP PREFIX id: PREFIX akt: SELECT DISTINCT ?a WHERE { ?paper akt:has-author id:person-02686, ?a. } “DISTINCT ?a” is not represented in this graph Constraints over nodes can be represented either as a graph and within FILTER section 7 ?paper id:person akt:has-author ?a akt:has-author

Entity Alignment as Graph Rewriting Query rewriting based on BGP graph rewriting Entity Alignment EA = –LHS : Triple to match (open variables to bind) –RHS : Set of triples to instantiate (depending on previous bindings on open variables) –FD : Functional dependencies (between variables) 8

Entity Alignment as Graph Rewriting Using the graph rewriting formalism we can rewrite queries defined for a dataset (or ontology) to integrate results from other data sets –But not only, we can also generate CONSTRUCT queries to integrate entire data sets 9

SPARQL Rewriting Each triple from the BGP is matched to the LHSs (generating variable bindings in the process) Eventual functional dependencies are solved (enriching the bindings with new associations) The respective RHS is instantiated with the given bindings and replace the original triple Unbounded variables generates new variables 10

SPARQL Rewriting Example: –LHS 1 = –RHS 1 = { } –FD 1 = {} = LHS 1 [_:1/?p] RHS 1 [_:1/?p]= _:1 it’s the RDF way to define blank nodes, that are treated, within a graph, as existentially quantified variables. Triple(v 1,rdf:type,source:A)  Triple(v 1,rdf:type,target:B) 11

SELECT * WHERE { ?s a source:User. … } SELECT * WHERE { ?s a target:Agent. … } Ontology Alignments – Class Eq. _:1 source:User rdf:type _:1 target:Agent rdf:type 12

SELECT * WHERE { ?s a source:WhiteWine. … } SELECT * WHERE { ?s a target:Vin; target:has-color … } Ontology Alignments – Class Partition _:1 source:WhiteWine rdf:type _:1 target:Vin rdf:type target:has-color 13

SELECT * WHERE { ?s source:has-name ?n. … } SELECT * WHERE { ?s target:fullName ?n. … } Ontology Alignments – Property Eq. _:1 source:has-name _:1 target:fullName _:2 14

SELECT * WHERE { ?p akt:has-author ?a. … } SELECT * WHERE { ?s kisti:CreatorInfo ?i. ?i kisti:hasCreator ?a … } Ontology Alignments – Property Eq. _:1 akt:has-author _:1 kisti:CreatorInfo _:2 _:3 _:2 kisti:hasCreator 15

SELECT * WHERE { ?p source:temp ”10”^^C. … } SELECT * WHERE { ?p target:farenheit ”50”^^F … } Ontology Alignments – Property Eq. _:1 source:temp _:1 target:farenheit _:2 binding directly Celsius values to Fahrenheit is wrong, the two values are linked by a functional dependency. _:3 celsius2farenheit 16

SPARQL Rewriting PREFIX id: PREFIX akt: SELECT DISTINCT ?a WHERE { ?paper akt:has-author id:person ?paper akt:has-author ?a. } 17 ?paper id:person akt:has-author ?a akt:has-author _:1 akt:has-author _:1 kisti:CreatorInfo _:2 _:3 _:2 kisti:hasCreator

SPARQL Rewriting 18 ?paper id:person akt:has-author ?a akt:has-author ?paper id:person kisti:CreatorInfo ?new1 akt:has-author ?a kisti:hasCreator ?paper id:person kisti:CreatorInfo ?new1 kisti:hasCreator ?a kisti:hasCreator ?new2 kisti:CreatorInfo Problem in KISTI dataset is unknown.

Co-reference integration Constants in the query (like URIs) must be translated in order to retrieve correct results URI equivalences are maintained by co-reference services like accessible via REST interface. Modeled as functional dependency within variables –Function returns the equivalent URI that satisfy a regex pattern –Datasets maintain URIs that are recognizable by a common schema (prefix for sure, e.g. ) 19

Co-reference integration 20 _:11 akt:has-author _:12 kisti:CreatorInfo _:21 _:3 _:22 kisti:hasCreator sameas id:person kisti:PER_

Implementation Java package based on Jena API for SPARQL Query rewriting Code not released yet (planning to integrate it with INRIA ontology alignment API) 21

Progress report Contact with Francois Schraffe and Jerome Euzenat Partial mapping to EDOAL ontology alignment specification (work in progress) SPARQL query rewriter to be implemented in the Alignment API (partially done) 22

EDOAL - Expressive and Declarative Ontology Alignment Language Construction of entities from other entities can be expressed through algebraic operators Restrictions can be expressed on entities in order to narrow their scope. Transformations of property values can be specified. Property values using different encoding or units can be aligned using transformations. 23

EDOAL - Example 24 :entity1 wine:Bordeaux ; :entity2 [ edoal:and (vin:Vin [ a edoal:AttributeValueRestriction edoal:comparator xsd:equals ; edoal:onAttribute [ edoal:compose (vin:hasTerroir proton:locatedIn ) ; a edoal:Relation ] ; edoal:value vin:Aquitaine ] ) ; a edoal:Class ] ; :measure "1."^^xsd:float ; :relation "SubsumedBy" ; a :Cell.

Internal Representation 25 _:6 rdf:type _:6 rdf:type wine:Bordeaux vin:Vin vin:Aquitaine vin:hasTerroir _:9 proton:locatedIn

Progress report Graph pattern rewriting can be used also for creating CONSTRUCT queries for translate RDF graphs with different ontologies. 26 CONSTRUCT { ?9. ?6 ?9. ?6.} WHERE { ?6.}

Outline Linked Data –Data topology –Data access Query Rewriting –Ontology Alignment –Entity Alignment –SPARQL rewriting 28

Linked Data topology Foreign URIs for referring to external entities Co-references for referring to instance “equivalence” 29