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Tutorial Stream Reasoning SPARQLstream and Morph-streams

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Stream Reasoning
For Linked Data
M. Balduini, J-P Calbimonte, O. Corcho,
D. Dell'Aglio, E. Della Valle, and J.Z. Pan
http://streamreasoning.org/sr4ld2013

SPARQLStream: Ontologybased access to data streams
Jean-Paul Calbimonte, Oscar Corcho
jp.calbimonte@upm.es, ocorcho@fi.upm.es
http://www.oeg-upm.net/
Share, Remix, Reuse — Legally
 This work is licensed under the Creative Commons
Attribution 3.0 Unported License.
 You are free:
• to Share — to copy, distribute and transmit the work
• to Remix — to adapt the work

 Under the following conditions
• Attribution — You must attribute the work by inserting
– “[source http://streamreasoning.org/sr4ld2013]” at the end of
each reused slide
– a credits slide stating
-

These slides are partially based on “Streaming Reasoning for Linked
Data 2013” by M. Balduini, J-P Calbimonte, O. Corcho, D. Dell'Aglio,
E. Della Valle, and J.Z. Pan http://streamreasoning.org/sr4ld2013

 To view a copy of this license, visit
http://creativecommons.org/licenses/by/3.0/
http://streamreasoning.org/sr4ld2013

2
SPARQLStream
 Virtual RDF views over data streams
 Ontology-based access to data streams
•
•
•

Examples
Architecture
Underlying query processors

 SPARQLStream language
 Query rewriting
•

R2RML mappings

 Resources

http://streamreasoning.org/sr4ld2013

3
Querying RDF Streams
users, applications

RDF Stream
query processing

RDF Stream Processor

Where is the data coming from?

Existing streaming
data sources

DSMS

CEP

http://streamreasoning.org/sr4ld2013

Sensor
middleware

Wrap
Import
Load
Contino
usly

…
4
Virtual RDF views over data streams
users, applications

Virtual RDF Stream
query processing

RDF Stream Processor
queries

data layer

DSMS

CEP

http://streamreasoning.org/sr4ld2013

Sensor
middleware

…
5
Already seen somewhere…?

RDF

SPARQL Query Processor
Load,
import

R2RML
Mappings

DBMS
http://streamreasoning.org/sr4ld2013

6
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Tutorial Stream Reasoning SPARQLstream and Morph-streams

  • 1. Stream Reasoning For Linked Data M. Balduini, J-P Calbimonte, O. Corcho, D. Dell'Aglio, E. Della Valle, and J.Z. Pan http://streamreasoning.org/sr4ld2013 SPARQLStream: Ontologybased access to data streams Jean-Paul Calbimonte, Oscar Corcho jp.calbimonte@upm.es, ocorcho@fi.upm.es http://www.oeg-upm.net/
  • 2. Share, Remix, Reuse — Legally  This work is licensed under the Creative Commons Attribution 3.0 Unported License.  You are free: • to Share — to copy, distribute and transmit the work • to Remix — to adapt the work  Under the following conditions • Attribution — You must attribute the work by inserting – “[source http://streamreasoning.org/sr4ld2013]” at the end of each reused slide – a credits slide stating - These slides are partially based on “Streaming Reasoning for Linked Data 2013” by M. Balduini, J-P Calbimonte, O. Corcho, D. Dell'Aglio, E. Della Valle, and J.Z. Pan http://streamreasoning.org/sr4ld2013  To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/ http://streamreasoning.org/sr4ld2013 2
  • 3. SPARQLStream  Virtual RDF views over data streams  Ontology-based access to data streams • • • Examples Architecture Underlying query processors  SPARQLStream language  Query rewriting • R2RML mappings  Resources http://streamreasoning.org/sr4ld2013 3
  • 4. Querying RDF Streams users, applications RDF Stream query processing RDF Stream Processor Where is the data coming from? Existing streaming data sources DSMS CEP http://streamreasoning.org/sr4ld2013 Sensor middleware Wrap Import Load Contino usly … 4
  • 5. Virtual RDF views over data streams users, applications Virtual RDF Stream query processing RDF Stream Processor queries data layer DSMS CEP http://streamreasoning.org/sr4ld2013 Sensor middleware … 5
  • 6. Already seen somewhere…? RDF SPARQL Query Processor Load, import R2RML Mappings DBMS http://streamreasoning.org/sr4ld2013 6
  • 7. Stream Processor Implementations Data Stream Management Systems (DSMS) CQL/Stream Borealis StreamMill NiagaraCQ TelegraphCQ Complex Event Processors (CEP) GEM Rapide Cayuga Stream Data Middleware CEDR GSN Oracle CEP IBM InfoSphere Microsoft StreamInsight Hourglass Cosm SStreamWare Esper Sybase CEP StreamBase Diverse query languages Different query capabilities Different query models http://streamreasoning.org/sr4ld2013 7
  • 8. Morph-streams: Overview SELECT ?proximity FROM STREAM π timed,prox <http://streamreasoning.org/SensorReadings.srdf> [NOW–5 S] WHERE { ?obs a ssn:ObservationValue; qudt:numericalValue ?proximity; FILTER (?proximity>10) } Client SPARQLStream ω5 Seconds sens Query rewriting R2RML Mappings [triples/bin dings] σprox>10 Data translation Algebra expression SELECT prox FROM sens.win:time(5 sec) WHERE prox >10 SNEE Esper Query Processing [tuples] GSN pull/push Cosm Other Morph-streams procesing SPARQLStream queries https://github.com/jpcik/morph-streams http://streamreasoning.org/sr4ld2013 8
  • 9. SPARQLStream Language ISTREAM DSTREAM RSTREAM FROM NAMED STREAM WINDOW Underlying data source restrictions http://streamreasoning.org/sr4ld2013 9
  • 10. SPARQLStream: examples SPARQLStream PREFIX sr4ld: <http://www.streamreasoning.org/ontologies/socialsensor,owl#> SELECT ?room FROM NAMED STREAM <http://www.streamreasoning.org/streams/socialsensor.srdf> [NOW-10 S] WHERE { ?obs sr4ld:observedBy ?sensor. ?obs sr4ld:where ?room. } All rooms where something was observed in the last 10s PREFIX sr4ld: <http://www.streamreasoning.org/ontologies/socialsensor,owl#> SELECT (COUNT(?person) AS ?nmb) ?room FROM NAMED STREAM <http://www.streamreasoning.org/streams/socialsensor.srdf> [NOW-10 S] WHERE { ?obs sr4ld:who ?pers. ?obs sr4ld:where ?room. } GROUP BY ?room Number of persons observed in each room in the last 10s http://streamreasoning.org/sr4ld2013 10
  • 11. SPARQLStream Language  NamedStream  „FROM‟ [„NAMED‟] „STREAM‟ StreamIRI „[‟ Window „]‟  Window  „NOW-‟ Integer TimeUnit [UpperBound] [Slide]  UpperBound  „TO NOW-‟ Integer TimeUnit  Slide  „SLIDE‟ Integer TimeUnit  TimeUnit  „MS‟ | „S‟ | „MINUTES‟| „HOURS‟ | „DAY‟ SELECT ISTREAM ?room FROM NAMED STREAM <http://www.streamreasoning.org/streams/socialsensor.srdf> [NOW-10 S] WHERE {…  Select  „SELECT‟ [Xstream] [Distinct | Reduced] …  Xstream  „RSTREAM‟ | „ISTREAM‟ | „DSTREAM‟ http://streamreasoning.org/sr4ld2013 11
  • 12. Morph-streams: Overview SELECT ?proximity FROM STREAM π timed,prox <http://streamreasoning.org/SensorReadings.srdf> [NOW–5 S] WHERE { ?obs a ssn:ObservationValue; qudt:numericalValue ?proximity; FILTER (?proximity>10) } Client SPARQLStream ω5 Seconds sens Query rewriting R2RML Mappings [triples/bin dings] σprox>10 Data translation Algebra expression SELECT prox FROM sens.win:time(5 sec) WHERE prox >10 SNEE Esper Query Processing [tuples] GSN pull/push Cosm Other Morph-streams procesing SPARQLStream queries https://github.com/jpcik/morph-streams http://streamreasoning.org/sr4ld2013 12
  • 13. Now, where is the data? ... sensor (bob,room2) τi (alice,room3) τi+1 (carl,room1) τi (luke,room1) τi+1 (alice,room1) τi-1 ... ... stream tuples (person,room,…) τi Stream Schema DSMS, CEP, middleware can evaluate queries over this model http://streamreasoning.org/sr4ld2013 13
  • 14. Underlying Query Processors Esper • CEP/DSMS • EPL language SELECT prox FROM sensors.win:time(5 minute) WHERE prox >10 GSN • Sensor middleware • REST API http://montblanc.slf.ch:22001/multidata?vs[0]=sens ors& field[0]=proximity_field&c_min[0]=10& from=15/05/2012+05:00:00&to=15/05/2012+10:00: 00 http://streamreasoning.org/sr4ld2013 SNEE • DSMS/Sensor Network Query Evaluator • Compile queries to sensor code SELECT prox FROM sensors [FROM NOW-5 MINUTES TO NOW] WHERE prox >10 Cosm/Xively • Sensor middleware • Open platform • REST API http://api.cosm.com/v2/feeds/14321/datastreams/ 4?start=2012-05-15T05:00:00Z&end=2012-0515T10:00:00Z 14
  • 15. Underlying Query Processors SPARQLStream SELECT ?proximity FROM STREAM <http://streamreasoning.org/SensorReadings.srdf> [NOW–5 S] WHERE { ?obs a ssn:ObservationValue; qudt:numericalValue ?proximity; FILTER (?proximity>10) } R2RML prox Query rewriting SELECT prox FROM sensors [FROM NOW-5 MINUTES TO NOW] WHERE prox >10 SNEE (DSMS) SELECT prox FROM sensors.win:time(5 minute) WHERE prox >10 Esper (CEP) http://montblanc.slf.ch:22001/multidata?vs[0]=sensors&field[0]=proximi ty_field&c_min[0]=10& from=15/05/2012+05:00:00&to=15/05/2012+10:00:00 GSN (middlwr) http://api.cosm.com/v2/feeds/14321/datastreams/4?start=2012-0515T05:00:00Z&end=2012-05-15T10:00:00Z Cosm Xively http://streamreasoning.org/sr4ld201315 πtimed, σprox>10 ω 5 Seconds sensors
  • 16. Underlying query processors Features Esper SNEE GSN Cosm/Xively Projection ✔ ✔ ✔ Fixed Proj expression ✔ ✔ ✖ ✖ Joins ✔ ✔✖ only window ✖ ✖ Union ✖ ✔✖ not windows ✔ ✖ Selection ✔ ✔ ✔ ✖✔ limited Aggregates ✔ ✔ ✔✖ ✖ Time window ✔ ✔ ✔ ✔ Tuple window ✔ ✔ ✔ ✖ R2S ✔ ✔ ✖ ✖ Conjunction, Disj ✔ ✖ ✖ ✖ Repetition pattern ✔ ✖ ✖ ✖ Sequence ✔ ✖ ✖ ✖ http://streamreasoning.org/sr4ld2013 16
  • 17. Configuring Morph-streams  Main ingredients: 1. Data streams 2. Ontology (network) Link both models 3. R2RML mappings http://streamreasoning.org/sr4ld2013 17
  • 18. SSN Ontology with other ontologies W3C SSN Ontology modeling our streaming data combine with domain ontologies http://streamreasoning.org/sr4ld2013 18
  • 19. Our simpler ontology… subClassOf Observation where Room observes subPropOf who Post Sensor discusses subClassOf authorOf Person We can use different ontologies for the same data http://streamreasoning.org/sr4ld2013 19
  • 20. Our simpler ontology… Observation where Room observes detections (person, room,…) Sensor subClassOf who Define mappings Person http://streamreasoning.org/sr4ld2013 20
  • 23. Encoding in R2RML the stream name Mapping definition :triplesMap a rr:TriplesMap; rr:logicalTable [ rr:tableName ”sensors"; ] stream attributes subject URI rr:subjectMap [ rr:template "http://streamreasoning.org/data/Observation/{person}{timed}"; rr:class sr4ld:Observation; rr:graph sr4ld:socialstream.srdf ]; triple predicate + object rr:predicateObjectMap [ rr:predicate sr4ld:who ; rr:objectMap [ rr:template “http://streamreasoning.org/data/Person/{person}” ]];. the object (a URI in this case) http://streamreasoning.org/sr4ld2013 23
  • 24. Now some code Morph-streams:  Coded in Scala  JAR bundle, use it from Scala or Java code  Maven, Sbt  Examples • • • • • One off query Register continuous query Pull data Push Basic REST  https://github.com/jpcik/morph-streams http://streamreasoning.org/sr4ld2013 24
  • 25. Code examples  Parse SPARQLStream val query= “PREFIX sr4ld: <…>. SELECT ?a …” val syntax= StreamQueryFactory.create(query);  Execute One-off query Mapping val query= “PREFIX sr4ld: <…>. SELECT ?a …” mapping=Mapping(new URI(mappings/social.ttl)) val adapter:QueryEvaluator=Application.adapter(system) val results= adapter.executeQuery(query,mapping) Bindings http://streamreasoning.org/sr4ld2013 25
  • 26. Code examples  Register and Pull val queryid= adapter.registerQuery(query,mapping) val results1=adapter.pull(queryid) val results2=adapter.pull(queryid) Query identifier  Register and Push Implement receiver class ExampleReceiver extends StreamReceiver{ override def receiveData(s:SparqlResults):Unit= Logger.debug("got: "+res) } val receiver=new ExampleReceiver val queryid= adapter.listenToQuery(query,mapping,receiver) http://streamreasoning.org/sr4ld2013 26
  • 27. SPARQLStream from command line • encoded_value=$(python -c "import urllib; print urllib.quote('''SELECT DISTINCT ?timeto ?obs FROM NAMED STREAM <http://emt.linkeddata.es/data#busstops.srdf> [NOW - 30 S] WHERE { ?obs a <http://emt.linkeddata.es/data#BusObservation>. ?obs <http://purl.oclc.org/NET/ssnx/ssn#observedBy><http://transporte.li nkeddata.es/emt/busstop/id/2018>. ?obs <http://purl.oclc.org/NET/ssnx/ssn#observationResult> ?output. ?output <http://emt.linkeddata.es/data#timeToBusValue> ?av. ?av <http://data.nasa.gov/qudt/owl/qudt#numericValue> ?timeto. }''')") Just encoding query • curl "http://streams.linkeddata.es/emt/sparqlstream?query=$encoded_val ue” Disclaimer: Simplistic, not implementing all of the SPARQL protocol http://streamreasoning.org/sr4ld2013 27
  • 28. Sample result { "head": { "vars": [ "timeto" , "obs" ] }, "results": { "bindings": [ Bindings in JSON { "timeto": { "datatype": "http://www.w3.org/2001/XMLSchema#string" , "type": "typedliteral" , "value": "0" } , "obs": { "type": "uri" , "value": "http://transporte.linkeddata.es/emt/busstop/id/2018/busline/9/observation/20/09/2013%2010:2 8:19%20%2B0200" } } ] } } http://streamreasoning.org/sr4ld2013 28
  • 29. Resources  Morph-Streams • https://github.com/jpcik/morph-streams  See demos • • http://transporte.linkeddata.es/ (SPARQL-Stream tab) Check our Madrid buses demo at SSN2013 workshop tomorrow  Read out more • Enabling Query Technologies for the Semantic Sensor Web. J.-P. Calbimonte, H. Jeung, O. Corcho and K. Aberer. International Journal on Semantic Web and Information Systems IJSWIS, Volume 8(1)., 2012  Contact point • • jp.calbimonte@upm.es ocorcho@fi.upm.es http://streamreasoning.org/sr4ld2013 29
  • 30. Stream Reasoning For Linked Data M. Balduini, J-P Calbimonte, O. Corcho, D. Dell'Aglio, E. Della Valle, and J.Z. Pan http://streamreasoning.org/sr4ld2013 SPARQLStream: Ontologybased access to data streams Jean Paul Calbimonte, Oscar Corcho jp.calbimonte@upm.es, ocorcho@fi.upm.es http://www.oeg-upm.net/
  • 31. RDF Streams 〈s,p,o 〉 <aemet:observation1, ssn:observedBy, aemet:Sensor3> <aemet:observation1, qudt:hasNumericValue, “15.5”> For streams? (〈s,p,o〉,τ) (<aemet:observation1, qudt:hasNumericValue, “15.5”>,34532) timestamped triples • Gutierrez et al. (2007) Introducing time into RDF. IEEE TKDE • Rodríguez et al. (2009) Semantic management of streaming data. SSN http://streamreasoning.org/sr4ld2013 31