Difference between revisions of "SPARQL Examples"

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  PREFIX ex: <http://example.org/>  
 
  PREFIX ex: <http://example.org/>  
  
===select all triplets in graph===
+
===Select all triplets in graph===
  
 
  SELECT ?s ?p ?o
 
  SELECT ?s ?p ?o
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     ?s ?p ?o .
 
     ?s ?p ?o .
 
  }  
 
  }  
===select the interestes of Cade===
+
 
 +
or
 +
 
 +
SELECT *
 +
WHERE {
 +
    ?s ?p ?o .
 +
}
 +
 
 +
===Select the interestes of Cade===
  
 
  SELECT ?cadeInterest
 
  SELECT ?cadeInterest
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     ex:Cade ex:interest ?cadeInterest .
 
     ex:Cade ex:interest ?cadeInterest .
 
  }  
 
  }  
===select the country and city where Emma lives===
+
===Select the country and city where Emma lives===
  
 
  SELECT ?emmaCity ?emmaCountry
 
  SELECT ?emmaCity ?emmaCountry
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     ?address ex:country ?emmaCountry .
 
     ?address ex:country ?emmaCountry .
 
  }  
 
  }  
===select the people who are over 26 years old===
+
 
 +
All address info to Emma.
 +
 
 +
SELECT ?person ?city ?country ?postalcode ?street WHERE{
 +
        ex:Emma ex:address ?address.
 +
        ?person ex:address ?address.
 +
        ?address ex:city ?city.
 +
        ?address ex:country ?country.
 +
        ?address ex:postalCode ?postalcode.
 +
        ?address ex:street ?street.
 +
}
 +
 
 +
Selecting all address info, to everyone.
 +
 
 +
SELECT ?name ?city ?country ?postalcode ?street WHERE{
 +
        ?person foaf:name ?name.
 +
        ?person ex:address ?address.
 +
        ?address ex:city ?city.
 +
        ?address ex:country ?country.
 +
        ?address ex:postalCode ?postalcode.
 +
        ?address ex:street ?street.
 +
}
 +
 
 +
===Select the people who are over 26 years old===
  
 
  SELECT ?person ?age
 
  SELECT ?person ?age
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     FILTER(?age > 26) .     
 
     FILTER(?age > 26) .     
 
  }  
 
  }  
===select people who graduated with Bachelor===
+
===Select people who graduated with Bachelor===
  
 
  SELECT ?person ?degree
 
  SELECT ?person ?degree
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  }  
 
  }  
===delete cades photography interest===
+
===Delete cades photography interest===
  
 
  DELETE DATA
 
  DELETE DATA
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     ex:Cade ex:interest ex:Photography .
 
     ex:Cade ex:interest ex:Photography .
 
  }  
 
  }  
===delete and insert university of valencia===
+
===Delete and insert university of valencia===
  
 
  DELETE { ?s ?p ex:University_of_Valencia }
 
  DELETE { ?s ?p ex:University_of_Valencia }
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  WHERE  { ?s ?p ex:University_of_Valencia }  
 
  WHERE  { ?s ?p ex:University_of_Valencia }  
  
===check if the deletion worked===
+
===Check if the deletion worked===
  
 
  SELECT ?s ?o2
 
  SELECT ?s ?o2
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       }
 
       }
  
===insert Sergio===
+
===Insert Sergio===
  
 
  INSERT DATA {
 
  INSERT DATA {
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         ex:Machine_learning;
 
         ex:Machine_learning;
 
     foaf:name "Sergio_Pastor"^^xsd:string .
 
     foaf:name "Sergio_Pastor"^^xsd:string .
}
+
}
 
        
 
        
===describe Sergio===
+
===Describe Sergio===
  
 
  DESCRIBE ex:Sergio ?o
 
  DESCRIBE ex:Sergio ?o
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   }
 
   }
  
===construct that any city is in the country in an address===  
+
===Construct that any city is in the country in an address===  
  
 
  CONSTRUCT {?city ex:locatedIn ?country}
 
  CONSTRUCT {?city ex:locatedIn ?country}
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   }
 
   }
  
<!--
+
 
+
==The data are available in this Blazegraph triple store:==
The data are available in this Blazegraph triple store:
 
 
[http://sandbox.i2s.uib.no http://sandbox.i2s.uib.no] , but you may need to be inside the UiB network (or on VPN.)
 
[http://sandbox.i2s.uib.no http://sandbox.i2s.uib.no] , but you may need to be inside the UiB network (or on VPN.)
  
Line 309: Line 339:
  
 
(Actually, these years are xsd:integer- s, not quite xsd:gYear-s.)
 
(Actually, these years are xsd:integer- s, not quite xsd:gYear-s.)
 +
 +
<!--
  
 
== SPARQL Examples from Session 7: RDFS==
 
== SPARQL Examples from Session 7: RDFS==
Line 387: Line 419:
 
* view the ontologies online using [http://www.visualdataweb.de/webvowl/ WebVOWL] or  
 
* view the ontologies online using [http://www.visualdataweb.de/webvowl/ WebVOWL] or  
 
* download the [https://protege.stanford.edu/products.php#desktop-protege Protegé-OWL] ontology editor.
 
* download the [https://protege.stanford.edu/products.php#desktop-protege Protegé-OWL] ontology editor.
 +
<!--
 
-->
 
-->

Latest revision as of 13:53, 10 March 2022

This page will be updated with SPARQL examples as the course progresses.


SPARQL Examples from Session 3: SPARQL

Prefixes used

The examples below will assume that these are in place (some examples aren't yet visible).

PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX owl: <http://www.w3.org/2002/07/owl#>
PREFIX dc: <http://purl.org/dc/terms/>
PREFIX bibo: <http://purl.org/ontology/bibo/>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX skos: <http://www.w3.org/2004/02/skos/core#>
PREFIX ss: <http://semanticscholar.org/>
PREFIX kg: <http://i2s.uib.no/kg4news/>
PREFIX sp: <http://i2s.uib.no/kg4news/science-parse/>
PREFIX th: <http://i2s.uib.no/kg4news/theme/>
PREFIX xml: <http://www.w3.org/XML/1998/namespace> 
PREFIX ex: <http://example.org/> 

Select all triplets in graph

SELECT ?s ?p ?o
WHERE {
   ?s ?p ?o .
} 

or

SELECT *
WHERE {
   ?s ?p ?o .
} 

Select the interestes of Cade

SELECT ?cadeInterest
WHERE {
   ex:Cade ex:interest ?cadeInterest .
} 

Select the country and city where Emma lives

SELECT ?emmaCity ?emmaCountry
WHERE {
   ex:Emma ex:address ?address .
   ?address ex:city ?emmaCity .
   ?address ex:country ?emmaCountry .
} 

All address info to Emma.

SELECT ?person ?city ?country ?postalcode ?street WHERE{
       ex:Emma ex:address ?address. 
       ?person ex:address ?address.
       ?address ex:city ?city.
       ?address ex:country ?country.
       ?address ex:postalCode ?postalcode.
       ?address ex:street ?street.
}

Selecting all address info, to everyone.

SELECT ?name ?city ?country ?postalcode ?street WHERE{ 
       ?person foaf:name ?name. 
       ?person ex:address ?address.
       ?address ex:city ?city.
       ?address ex:country ?country.
       ?address ex:postalCode ?postalcode.
       ?address ex:street ?street.
}

Select the people who are over 26 years old

SELECT ?person ?age
WHERE {
   ?person ex:age ?age .
    FILTER(?age > 26) .     
} 

Select people who graduated with Bachelor

SELECT ?person ?degree
WHERE {
   ?person ex:degree ?degree .
   ?degree ex:degreeLevel "Bachelor" .
         
} 

Delete cades photography interest

DELETE DATA
{
   ex:Cade ex:interest ex:Photography .
} 

Delete and insert university of valencia

DELETE { ?s ?p ex:University_of_Valencia }
INSERT { ?s ?p ex:Universidad_de_Valencia }
WHERE  { ?s ?p ex:University_of_Valencia } 

Check if the deletion worked

SELECT ?s ?o2
WHERE  { 
 ?s ex:degree ?o .
 ?o ex:degreeSource ?o2 .
      	}

Insert Sergio

INSERT DATA {
 ex:Sergio a foaf:Person ;
   ex:address [ a ex:Address ;
           ex:city ex:Valenciay ;
           ex:country ex:Spain ;
           ex:postalCode "46021"^^xsd:string ;
           ex:state ex:California ;
           ex:street "4_Carrer_del_Serpis"^^xsd:string ] ;
   ex:degree [ ex:degreeField ex:Computer_science ;
           ex:degreeLevel "Master"^^xsd:string ;
           ex:degreeSource ex:University_of_Valencia ;
           ex:year "2008"^^xsd:gYear ] ;
   ex:expertise ex:Big_data,
       ex:Semantic_technologies,
       ex:Machine_learning;
   foaf:name "Sergio_Pastor"^^xsd:string .
}
     

Describe Sergio

DESCRIBE ex:Sergio ?o
WHERE {
 ex:Sergio ?p ?o .
 ?o ?p2 ?o2 .
 }

Construct that any city is in the country in an address

CONSTRUCT {?city ex:locatedIn ?country}
Where {
 ?s rdf:type ex:Address .
 ?s ex:city ?city .
 ?s ex:country ?country.
 }


The data are available in this Blazegraph triple store:

http://sandbox.i2s.uib.no , but you may need to be inside the UiB network (or on VPN.)

SELECT DISTINCT ?p WHERE {
  ?s rdf:type ss:Paper .
  ?s ?p ?o .
 } LIMIT 100

Explain all types and properties

SELECT ?pt ?e WHERE {
  ?pt rdfs:comment ?e .
} LIMIT 100

List main papers

SELECT * WHERE {
 
  ?paper rdf:type kg:MainPaper .
  ?paper dc:date ?year .
 
}

List properties

SELECT DISTINCT ?p WHERE {
  ?s ?p ?o .
} LIMIT 100

List types

PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>

SELECT DISTINCT ?t WHERE {
  ?s rdf:type ?t .
} LIMIT 100

List authors

PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT DISTINCT ?p WHERE {
  ?s rdf:type foaf:Person .
  ?s ?p ?o .
} LIMIT 100

Add this to show datatypes!

  BIND ( DATATYPE(?year) AS ?type )

Add this to only show years with the right type.

  FILTER ( DATATYPE(?year) = xsd:gYear )

Group and count main papers by year

SELECT ?year (COUNT(?paper) AS ?count) WHERE {

  ?paper rdf:type kg:MainPaper .
  ?paper dc:date ?year .
  FILTER ( DATATYPE(?year) = xsd:gYear )

}
GROUP BY ?year

Add this to order the results

ORDER BY ?year

Add this to order and only show years with more than 5 papers.

HAVING (?count > 5)
ORDER BY DESC(?count)

Show papers

SELECT ?paper ?year WHERE {

  ?paper rdf:type kg:MainPaper .
  ?paper dc:date ?year .
  FILTER ( DATATYPE(?year) = xsd:gYear )

}

Change last lines to show papers without an xsd:gYear too.

  OPTIONAL {
      ?paper dc:date ?year .
      FILTER ( DATATYPE(?year) = xsd:gYear )
  }

Alternative values for variables

SELECT ?p ?n ?year WHERE {
  ?p rdf:type kg:MainPaper .
  ?p dc:contributor ?a .
  ?a foaf:name ?n .
  ?p dc:date ?year .
  FILTER ( CONTAINS( ?n, ?str ) )
  FILTER ( CONTAINS( STR(?year), ?yr) )
 
  VALUES ?str { "Andreas" "David" }
  VALUES ?yr { "2020" "2019" }
}

Property paths (composite properties)

This query:

SELECT ?p ?n WHERE {
  ?p rdf:type kg:MainPaper .
  ?p dc:contributor ?c .
  ?c foaf:name ?n .
}

Can be simplified by eliminating ?c:

SELECT ?p ?n WHERE {
  ?p rdf:type kg:MainPaper .
  ?p dc:contributor / foaf:name ?n .
}

Can be further simplified by first reversing rdf:type:

SELECT ?p ?n WHERE {
  kg:MainPaper ^rdf:type ?p .
  ?p dc:contributor / foaf:name ?n .
}

...and the eliminating ?p:

SELECT ?n WHERE {
  kg:MainPaper ^rdf:type / dc:contributor / foaf:name ?n .
}

Retrieve titles of papers that mention SPARQL

Get papers with topics labelled "SPARQL":

SELECT ?t WHERE {
  ?t ^dc:title / dc:subject / skos:prefLabel "SPARQL" .
}

Some labels also go via a theme:

SELECT ?t WHERE {
  ?t ^dc:title / dc:subject / th:theme / skos:prefLabel "SPARQL" .
}

We can get both using a path with an optional element (the '?'):

SELECT ?t WHERE {
  ?t ^dc:title / dc:subject / th:theme? / skos:prefLabel "SPARQL" .
}

Using an external SPARQL endpoint

We limit to a single label to avoid time-outs and rate limitations:

SELECT ?a ?n ?r WHERE {
  ?a rdf:type ss:Topic .
  ?a skos:prefLabel ?n .
  FILTER ( ?n = "SPARQL" )
  BIND ( STRLANG( ?n, "en" ) AS ?n2 )
    SERVICE <https://dbpedia.org/sparql> {
    ?r rdfs:label ?n2 .
    }
} LIMIT 1

Insert 4-digit years for all main papers

Main papers that do not have an xsd:gYear:

SELECT * WHERE {
 
  ?p rdf:type kg:MainPaper .
  ?p dc:date ?d .
  FILTER ( DATATYPE(?d) = xsd:gYear )
 
}

Show the datatypes:

SELECT * WHERE {
 
  ?p rdf:type kg:MainPaper .
  ?p dc:date ?d .
  FILTER ( DATATYPE(?d) = xsd:dateTime )
  BIND ( year( ?d ) AS ?dt )
 
}

Insert 4-digit years:

INSERT { ?paper dc:date ?year } 
WHERE {
  
 ?paper rdf:type kg:MainPaper .
 ?paper dc:date ?date .
  FILTER( DATATYPE(?date) != xsd:gYear )
  BIND ( YEAR(?date) AS ?year ) 
  
}

(Actually, these years are xsd:integer- s, not quite xsd:gYear-s.)