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Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
Querying Linked Data with SPARQL (2010)
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Querying Linked Data with SPARQL (2010)

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This slideset was part of our "How to consume Linked Data" tutorial at the World Wide Web Conference (WWW), Apr. 2010

This slideset was part of our "How to consume Linked Data" tutorial at the World Wide Web Conference (WWW), Apr. 2010

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  • 1. Querying Linked Data with SPARQL WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 2. Brief Introduction to SPARQL ● SPARQL: Query Language for RDF data* ● Main idea: pattern matching ● Describe subgraphs of the queried RDF graph ● Subgraphs that match your description yield a result ● Mean: graph patterns (i.e. RDF graphs /w variables) ?v rdf:type http://.../Volcano * http://www.w3.org/TR/rdf-sparql-query/ WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 3. Brief Introduction to SPARQL Queried graph: rdf:type http://.../Mount_Baker http://.../Volcano p:lastEruption rdf:type "1880" http://.../Mount_Etna ?v rdf:type Results: http://.../Volcano ?v http://.../Mount_Baker http://.../Mount_Etna WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 4. SPARQL Endpoints ● Linked Data sources usually provide a SPARQL endpoint for their dataset(s) ● SPARQL endpoint: SPARQL query processing service that supports the SPARQL protocol* ● Send your SPARQL query, receive the result * http://www.w3.org/TR/rdf-sparql-protocol/ WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 5. SPARQL Endpoints Data Source Endpoint Address DBpedia http://dbpedia.org/sparql Musicbrainz http://dbtune.org/musicbrainz/sparql U.S. Census http://www.rdfabout.com/sparql Semantic Crunchbase http://cb.semsol.org/sparql More complete list: http://esw.w3.org/topic/SparqlEndpoints WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 6. Accessing a SPARQL Endpoint ● SPARQL endpoints: RESTful Web services ● Issuing SPARQL queries to a remote SPARQL endpoint is basically an HTTP GET request to the SPARQL endpoint with parameter query GET /sparql?query=PREFIX+rd... HTTP/1.1 Host: dbpedia.org User-agent: my-sparql-client/0.1 URL-encoded string with the SPARQL query WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 7. Query Results Formats ● SPARQL endpoints usually support different result formats: ● XML, JSON, plain text (for ASK and SELECT queries) ● RDF/XML, NTriples, Turtle, N3 (for DESCRIBE and CONSTRUCT queries) WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 8. Query Results Formats PREFIX dbp: <http://dbpedia.org/ontology/> PREFIX dbpprop: <http://dbpedia.org/property/> SELECT ?name ?bday WHERE { ?p dbp:birthplace <http://dbpedia.org/resource/Berlin> . ?p dbpprop:dateOfBirth ?bday . ?p dbpprop:name ?name . } name | bday ------------------------+------------ Alexander von Humboldt | 1769-09-14 Ernst Lubitsch | 1892-01-28 ... WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 9. <?xml version="1.0"?> <sparql xmlns="http://www.w3.org/2005/sparql-results#"> <head> <variable name="name"/> <variable name="bday"/> </head> <results distinct="false" ordered="true"> <result> <binding name="name"> <literal xml:lang="en">Alexander von Humboldt</literal> </binding> <binding name="bday"> <literal datatype="http://www.w3.org/2001/XMLSchema#date">1769-09-14</literal> </binding> </result> <result> <binding name="name"> <literal xml:lang="en">Ernst Lubitsch</literal> </binding> <binding name="bday"> <literal datatype="http://www.w3.org/2001/XMLSchema#date">1892-01-28</literal> </binding> </result> http://www.w3.org/TR/rdf-sparql-XMLres/ <!-- … --> </results> WWW 2010 Tutorial "How to Consume Linked Data on the Web" </sparql>
  • 10. { "head": { "link": [], "vars": ["name", "bday"] }, "results": { "distinct": false, "ordered": true, "bindings": [ { "name": { "type": "literal", "xml:lang": "en", "value": "Alexander von Humboldt" } , "bday": { "type": "typed-literal", "datatype": "http://www.w3.org/2001/XMLSchema#date", "value": "1769-09-14" } }, { "name": { "type": "literal", "xml:lang": "en", "value": "Ernst Lubitsch" } , "bday": { "type": "typed-literal", "datatype": "http://www.w3.org/2001/XMLSchema#date", "value": "1892-01-28" } }, // ... ] } http://www.w3.org/TR/rdf-sparql-json-res/ } WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 11. Query Result Formats ● Use the ACCEPT header to request the preferred result format: GET /sparql?query=PREFIX+rd... HTTP/1.1 Host: dbpedia.org User-agent: my-sparql-client/0.1 Accept: application/sparql-results+json WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 12. Query Result Formats ● As an alternative some SPARQL endpoint implementations (e.g. Joseki) provide an additional parameter out GET /sparql?out=json&query=... HTTP/1.1 Host: dbpedia.org User-agent: my-sparql-client/0.1 WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 13. Accessing a SPARQL Endpoint ● More convenient: use a library ● Libraries: ● SPARQL JavaScript Library http://www.thefigtrees.net/lee/blog/2006/04/sparql_calendar_demo_a_sparql.html ● ARC for PHP http://arc.semsol.org/ ● RAP – RDF API for PHP http://www4.wiwiss.fu-berlin.de/bizer/rdfapi/index.html WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 14. Accessing a SPARQL Endpoint ● Libraries (cont.): ● Jena / ARQ (Java) http://jena.sourceforge.net/ ● Sesame (Java) http://www.openrdf.org/ ● SPARQL Wrapper (Python) http://sparql-wrapper.sourceforge.net/ ● PySPARQL (Python) http://code.google.com/p/pysparql/ WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 15. Accessing a SPARQL Endpoint ● Example with Jena / ARQ: import com.hp.hpl.jena.query.*; String service = "..."; // address of the SPARQL endpoint String query = "SELECT ..."; // your SPARQL query QueryExecution e = QueryExecutionFactory.sparqlService( service, query ); ResultSet results = e.execSelect(); while ( results.hasNext() ) { QuerySolution s = results.nextSolution(); // … } e.close(); WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 16. ● Querying a single dataset is quite boring compared to: ● Issuing SPARQL queries over multiple datasets ● How can you do this? 1. Issue follow-up queries to different endpoints 2. Querying a central collection of datasets 3. Build store with copies of relevant datasets 4. Use query federation system WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 17. Follow-up Queries ● Idea: issue follow-up queries over other datasets based on results from previous queries ● Substituting placeholders in query templates WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 18. String s1 = "http://cb.semsol.org/sparql"; String s2 = "http://dbpedia.org/sparql"; String qTmpl = "SELECT ?c WHERE{ <%s> rdfs:comment ?c }"; String q1 = "SELECT ?s WHERE { ..."; QueryExecution e1 = QueryExecutionFactory.sparqlService(s1,q1); ResultSet results1 = e1.execSelect(); while ( results1.hasNext() ) { QuerySolution s1 = results.nextSolution(); String q2 = String.format( qTmpl, s1.getResource("s"),getURI() ); QueryExecution e2= QueryExecutionFactory.sparqlService(s2,q2); ResultSet results2 = e2.execSelect(); while ( results2.hasNext() ) { // ... } Find a list of companies e2.close(); } filtered by some criteria and e1.close(); return DBpedia URIs of them WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 19. Follow-up Queries ● Advantage: ● Queried data is up-to-date ● Drawbacks: ● Requires the existence of a SPARQL endpoint for each dataset ● Requires program logic ● Very inefficient WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 20. Querying a Collection of Datasets ● Idea: Use an existing SPARQL endpoint that provides access to a set of copies of relevant datasets ● Example: ● SPARQL endpoint by OpenLink SW over a majority of datasets from the LOD cloud at: http://lod.openlinksw.com/sparql WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 21. Querying a Collection of Datasets ● Advantage: ● No need for specific program logic ● Drawbacks: ● Queried data might be out of date ● Not all relevant datasets in the collection WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 22. Own Store of Dataset Copies ● Idea: Build your own store with copies of relevant datasets and query it ● Possible stores: ● Jena TDB http://jena.hpl.hp.com/wiki/TDB ● Sesame http://www.openrdf.org/ ● OpenLink Virtuoso http://virtuoso.openlinksw.com/ ● 4store http://4store.org/ ● AllegroGraph http://www.franz.com/agraph/ ● etc. WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 23. Populating Your Store ● Get RDF dumps provided for the datasets ● (Focussed) Crawling ● ldspider http://code.google.com/p/ldspider/ ● Multithreaded API for focused crawling ● Crawling strategies (breath-first, load-balancing) ● Flexible configuration with callbacks and hooks WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 24. Own Store of Dataset Copies ● Advantages: ● No need for specific program logic ● Can include all datasets ● Independent of the existence, availability, and efficiency of SPARQL endpoints ● Drawbacks: ● Requires effort to set up and to operate the store ● Ideally, data sources provide RDF dumps; if not? ● How to keep the copies in sync with the originals? ● Queried data might be out of date WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 25. Federated Query Processing ● Idea: Querying a mediator which ? distributes subqueries to relevant sources and integrates the results ? ? ? WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 26. Federated Query Processing ● Instance-based federation ● Each thing described by only one data source ● Untypical for the Web of Data ● Triple-based federation ● No restrictions ● Requires more distributed joins ● Statistics about datasets required (both cases) WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 27. Federated Query Processing ● DARQ (Distributed ARQ) http://darq.sourceforge.net/ ● Query engine for federated SPARQL queries ● Extension of ARQ (query engine for Jena) ● Last update: June 28, 2006 WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 28. Federated Query Processing ● Semantic Web Integrator and Query Engine (SemWIQ) http://semwiq.sourceforge.net/ ● Actively maintained by Andreas Langegger WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 29. Federated Query Processing ● Advantages: ● No need for specific program logic ● Queried data is up to date ● Drawbacks: ● Requires the existence of a SPARQL endpoint for each dataset ● Requires effort to set up and configure the mediator WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 30. In any case: ● You have to know the relevant data sources ● When developing the app using follow-up queries ● When selecting an existing SPARQL endpoint over a collection of dataset copies ● When setting up your own store with a collection of dataset copies ● When configuring your query federation system ● You restrict yourself to the selected sources WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 31. In any case: ● You have to know the relevant data sources ● When developing the app using follow-up queries ● When selecting an existing SPARQL endpoint over a collection of dataset copies ● When setting up your own store with a collection of dataset copies ● When configuring your query federation system ● You restrict yourself to the selected sources There is an alternative: Remember, URIs link to data WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 32. Automated Link Traversal WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 33. Automated Link Traversal ● Idea: Discover further data by looking up relevant URIs in your application ● Can be combined with the previous approaches WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 34. Link Traversal Based Query Execution ● Applies the idea of automated link traversal to the execution of SPARQL queries ● Idea: ● Intertwine query evaluation with traversal of RDF links ● Discover data that might contribute to query results during query execution ● Alternately: ● Evaluate parts of the query ● Look up URIs in intermediate solutions Queried data WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 35. Link Traversal Based Query Execution SELECT ?c ?u WHERE { <http://mymovie.db/movie2449> mov:filming_location ?c . ?c geo:statistics ?cStats . ?cStats stat:unempRate ?u . } ● Example: Return unemployment rate of the countries in which the movie http://mymovie.db/movie2449 was filmed. Queried data WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 36. Link Traversal Based Query Execution SELECT ?c ?u WHERE { <http://mymovie.db/movie2449> mov:filming_location ?c . ?c geo:statistics ?cStats . 49 v ie24 ?cStats stat:unempRate ?u . } .d b/mo m ovie http ://my ? Queried data WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 37. Link Traversal Based Query Execution SELECT ?c ?u WHERE { <http://mymovie.db/movie2449> mov:filming_location ?c . ?c geo:statistics ?cStats . ?cStats stat:unempRate ?u . } Queried data WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 38. Link Traversal Based Query Execution SELECT ?c ?u WHERE { <http://mymovie.db/movie2449> mov:filming_location ?c . ?c geo:statistics ?cStats . ?cStats stat:unempRate ?u . } ... <http://mymovie.db/movie2449> mov:filming_location <http://geo.../Italy> . Queried data ... WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 39. Link Traversal Based Query Execution SELECT ?c ?u WHERE { <http://mymovie.db/movie2449> mov:filming_location ?c . ?c geo:statistics ?cStats . ?loc ?cStats stat:unempRate ?u . } http://geo.../Italy ... <http://mymovie.db/movie2449> mov:filming_location <http://geo.../Italy> . Queried data ... WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 40. Link Traversal Based Query Execution SELECT ?c ?u WHERE { <http://mymovie.db/movie2449> mov:filming_location ?c . ?c geo:statistics ?cStats . ?loc ?cStats stat:unempRate ?u . } http://geo.../Italy taly o.../I / / ge ? http: Queried data WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 41. Link Traversal Based Query Execution SELECT ?c ?u WHERE { <http://mymovie.db/movie2449> mov:filming_location ?c . ?c geo:statistics ?cStats . ?loc ?cStats stat:unempRate ?u . } ly http://geo.../Italy eo .../Ita http://g ? Queried data WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 42. Link Traversal Based Query Execution SELECT ?c ?u WHERE { <http://mymovie.db/movie2449> mov:filming_location ?c . ?c geo:statistics ?cStats . ?loc ?cStats stat:unempRate ?u . } http://geo.../Italy Queried data WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 43. Link Traversal Based Query Execution SELECT ?c ?u WHERE { <http://mymovie.db/movie2449> mov:filming_location ?c . ?c geo:statistics ?cStats . ?loc ?cStats stat:unempRate ?u . } http://geo.../Italy ... <http://geo.../Italy> geo:statistics <http://example.db/stat/IT> . ... Queried data WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 44. Link Traversal Based Query Execution SELECT ?c ?u WHERE { <http://mymovie.db/movie2449> mov:filming_location ?c . ?c geo:statistics ?cStats . ?loc ?cStats stat:unempRate ?u . } http://geo.../Italy ?loc ?stat http://geo.../Italy http://stats.db/../it ... <http://geo.../Italy> geo:statistics <http://example.db/stat/IT> . ... Queried data WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 45. Link Traversal Based Query Execution SELECT ?c ?u WHERE { <http://mymovie.db/movie2449> mov:filming_location ?c . ?c geo:statistics ?cStats . ?loc ?cStats stat:unempRate ?u . } http://geo.../Italy ?loc ?stat http://geo.../Italy http://stats.db/../it ● Proceed with this strategy (traverse RDF links during query execution) Queried data WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 46. Link Traversal Based Query Execution ● Advantages: ● No need to know all data sources in advance ● No need for specific programming logic ● Queried data is up to date ● Does not depend on the existence of SPARQL endpoints provided by the data sources ● Drawbacks: ● Not as fast as a centralized collection of copies ● Unsuitable for some queries ● Results might be incomplete WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 47. Implementations ● Semantic Web Client library (SWClLib) for Java http://www4.wiwiss.fu-berlin.de/bizer/ng4j/semwebclient/ ● SWIC for Prolog http://moustaki.org/swic/ WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 48. Implementations ● SQUIN http://squin.org ● Provides SWClLib functionality as a Web service ● Accessible like a SPARQL endpoint ● Public SQUIN service at: http://squin.informatik.hu-berlin.de/SQUIN/ ● Install package: unzip and start ● Convenient access with SQUIN PHP tools: $s = 'http:// …'; // address of the SQUIN service $q = new SparqlQuerySock( $s, '… SELECT ...' ); $res = $q->getJsonResult(); // or getXmlResult() WWW 2010 Tutorial "How to Consume Linked Data on the Web"
  • 49. Real-World Examples SELECT DISTINCT ?author ?phone WHERE { ?pub swc:isPartOf <http://data.semanticweb.org/conference/eswc/2009/proceedings> . ?pub swc:hasTopic ?topic . ?topic rdfs:label ?topicLabel . FILTER regex( str(?topicLabel), "ontology engineering", "i" ) . # of query results 2 ?pub swrc:author ?author . # of retrieved graphs 297 { ?author owl:sameAs ?authorAlt } # of accessed servers 16 UNION avg. execution time 1min 30sec { ?authorAlt owl:sameAs ?author } Return ?authorAlt foaf:phone ?phone . phone numbers of authors of ontology engineering papers } at ESWC'09. WWW 2010 Tutorial "How to Consume Linked Data on the Web"

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