Date: 23/10/2011

Semantic Sensor Data Search in a Federated Sensor Network

Jean-Paul Calbimonte1, Hoyoung Jeung2,

Oscar Corcho1 and Karl Aberer2

1Ontology Engineering Group.

Facultad de Informática, Universidad Politécnica de Madrid. 2Distributed Information Systems Laboratory

School of Computer Science & Communication Systems, EPFL.

jp.calbimonte@upm.es

4th International Workshop on Semantic Sensor Networks ISWC 2011

Outline

2

• Introduction• Sensor data• Sensor metadata

• Ontological representation• Mapping sensor streams• Sensor data search• Query translation

• GSN URL API

• Conclusions

3

Swiss-Experiment

• FP7 Network of Excellence

GeoResearcher

Environmental and GeoScience researchSwiss Alps

...

...

...

Real-time data

Snow,Wind,Radiation.Lots of stuff

• How much snow is lost to evaporation?

• Snow redistribution by wind• Wind erosion of sand• ...

I want data to create my

models and compare

Swiss-Experiment Infrastructure

4

• Global Sensor Networks, deployment for SwissEx.

• Distributed environment: GSN Davos, GSN Zurich, etc.• In each site, a number of sensors available• Each one with different schema

• Metadata stored in wiki• Federated metadata management:• Jeung H., Sarni, S., Paparrizos, I., Sathe, S., Aberer, K., Dawes, N., Papaioannus, T.,

Lehning, M.Effective Metadata Management in federated Sensor Networks.  in SUTC, 2010

Sensor observations

Sensor metadata

Sensor Metadata

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station

location

model

sensors

properties

Sensor Metadata

• What properties are measured

• Which sensors available

• Where are they located

• How are they configured

• Who is responsible

6

Sensor Data: Observations

7

Heterogeneity

Integration

W3C SSN-XG Ontology

• SSN Ontology

8

ssn:FeatureOfInterest

ssn:Observation

ssn:isProducedByssn:SensorOutput

ssn:Sensor

ssn:featureOfInterest

ssn:ObservationValue

ssn:Property

ssn:observedByssn:observationResult ssn:hasValue

ssn:hasProperty

ssn:observedProperty

ssn:observes

xsd:datatype

quantityValue

W3C SSN-XG Ontology

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ssn:OperatingRange

ssn:SensingDevice

ssn:hasOperatingRange

ssn:Device

ssn:Sensor

ssn:MeasurementCapability

ssn:Sensing

ssn:System

ssn:Deployment

ssn:Platform

ssn:hasDeployment

ssn:deployedOnPlatformssn:implements

ssn:hasMeasurementCapability

ssn:onPlatform

Example

swissex:Sensor1

rdf:type ssn:Sensor;

ssn:onPlatform swissex:Station1;

ssn:observes [rdf:type sweetSpeed:WindSpeed].

swissex:Sensor2

rdf:type ssn:Sensor;

ssn:onPlatform swissex:Station1;

ssn:observes [rdf:type sweetTemp:Temperature].

swissex:Station1

:hasGeometry [ rdf:type wgs84:Point;

wgs84:lat "46.8037166";

wgs84:long "9.7780305"].

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station

senso

r1

senso

r2

Example

swissex:WindSpeedObservation1

rdf:type ssn:Observation;

ssn:featureOfInterest [rdf:type sweetAtmoWind:Wind];

ssn:observedProperty [rdf:type sweetSpeed:WindSpeed];

ssn:observationResult [rdf:type ssn:SensorOutput;

ssn:hasValue [qudt:numericValue "6.245"^^xsd:double]];

ssn:observationResultTime [time:inXSDDatatime "2011-10-26T21:32:52"];

ssn:observedBy swissex:Sensor1 ;

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WindSpeed : 6.245

At: 2011-10-26T21:32:52

Where is the Data?

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GSN

GSN server instance

wan7

timed: datetime PKsp_wind: float

..sensor1sensor2sensor3…

Virtual

senso

rs

ssn:Observation

Mappings

Creating Mappings

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wan7

timed: datetime PKsp_wind: float

ssn:ObservationValue

qudt:numericValue

xsd:decimal

http://swissex.ch/data#Wan7/WindSpeed/ObsValue{timed}

sp_wind

ssn:SensorOutput

ssn:Observation

ssn:hasValue

ssn:observationResulthttp://swissex.ch/data#

Wan7/WindSpeed/Observation{timed}   

http://swissex.ch/data#Wan7/ WindSpeed/ ObsOutput{timed}   

ssn:Property

ssn:observedProperty

sweetSpeed:WindSpeed

R2RML

• RDB2RDF W3C Group, R2RML Mapping language:• http://www.w3.org/2001/sw/rdb2rdf/r2rml/

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:Wan4WindSpeed a rr:TriplesMapClass; rr:tableName "wan7"; rr:subjectMap [ rr:template "http://swissex.ch/ns#WindSpeed/Wan7/{timed}"; rr:class ssn:ObservationValue; rr:graph ssg:swissexsnow.srdf ]; rr:predicateObjectMap [ rr:predicateMap [ rr:predicate ssn:hasQuantityValue ]; rr:objectMap[ rr:column "sp_wind" ] ]; .

<http://swissex.ch/ns#/WindSpeed/Wan7/2011-05-20:20:00 > a ssn:ObservationValue<http://swissex.ch/ns#/WindSpeed/Wan7/2011-05-20:20:00 > ssn:hasQuantityValue " 4.5"

Searching for Sensors

• Transformed wiki metadata to SSN instances in RDF• Generated R2RML mappings for all sensors• Numbers: 28 Deployments

• Aprox. 50 sensors in each deployment. More than 1500 sensors

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SELECT DISTINCT?lat ?long ?platformName ?deploymentName WHERE {

?sensor ssn:observes [a prop:MotionProperty]; ?system ssn:hasSubSystem ?sensor;

ssn:onPlatform ?platform; ssn:hasDeployment ?deployment.

?deployment foaf:name ?deploymentName. ?platform dul:hasLocation [swissex:hasGeometry ?link];

foaf:name ?platformName. ?link omgeo:within(46.3 8.7 47.2 9.8);

geo-pos:lat ?lat; geo-pos:long ?long. }

Sensor Data Portal Application

• Problems• Too many sensors• Too Heterogeneous

• Any sensors available in this region?• Sensors that measure wind speed?• How about getting the data?

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Playing with it

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Querying the Observations

• Implementation of Ontology-based querying over GSN

• Using the R2RML mappings• Fronting GSN with SPARQL-Stream queries• Query & Data translation process

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Query & Data Translation

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qQuery

translation

q’Query

Processing

Data translation

dd’

Clie

nt mappings

[tuple][tuple]

[triple]

Ontology-based sensor query service

SPARQLStream

Target query Se

nso

r Ne

two

rks

SSN Onto

logy

R2RM

L

GSN

???

SELECT ?waveheightFROM STREAM <www.ssg4env.eu/SensorReadings.srdf> [NOW -10 MINUTES TO NOW]WHERE { ?WaveObs a ssn:Observation; sea:hasValue ?waveheight; }

Data Access

• GSN Web Services• GSN URL API

• Compose the query as a URL:

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http://montblanc.slf.ch :22001/ multidata ?vs [0]= wan7 &field [0]= sp_wind &from =15/05/2011+05:00:00& to =15/05/2011+10:00:00&c_vs [0]= wan7 & c_field [0]= sp_wind & c_min [0]=10

SELECT sp_wind FROM wan7 [NOW -5 HOUR] WHERE sp_wind >10 ?

Calbimonte, J-P., Corcho O., Gray, A. Enabling Ontology-based Access to Streaming Data Sources. In ISWC 2010.

SPARQL-Stream

Using the Mappings

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SELECT ?waveheightFROM STREAM <www.ssg4env.eu/SensorReadings.srdf> [NOW – 5 HOUR TO NOW]WHERE { ?WaveObs a ssn:ObservationValue; qudt:numericalValue ?waveheight; FILTER (?waveheight>10) }

wan7

timed: datetime PKsp_wind: float

xsd:datatype

ssn:ObservationValue

qudt:numericalValue

sp_wind

http://swissex.ch/data#Wan7/WindSpeed/ObsValue{timed}

timed,sp_wind

π

ω

σsp_wind>10

5 Hour

wan7

Algebra expressions

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timed,sp_wind

π

ω

σ sp_wind>10

5 Hour

wan7

http://montblanc.slf.ch :22001/ multidata ?vs [0]= wan7 &field [0]= sp_wind &from =15/05/2011+05:00:00& to =15/05/2011+10:00:00&c_vs [0]= wan7 & c_field [0]= sp_wind & c_min [0]=10

SELECT sp_wind FROM wan7 [NOW -5 HOUR] WHERE sp_wind >10

Algebra construction

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timed,sp_wind

π

ω

σ sp_wind>10

5 Hour

wan7

windsensor1

windsensor2

Static optimization

24Sensors, Mappings and Queries

timed,sp_wind

π

ω

σ sp_wind>10

5 Hour

wan7

timed,windvalue

π

ω

σ windvalue>10

5 Hour

windsensor1

timed,windvalue

π

ω

σ windvalue>10

5 Hour

windsensor2

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Querying the ObservationsSELECT ?waveheightFROM STREAM <www.ssg4env.eu/SensorReadings.srdf> [NOW -10 MINUTES TO NOW STEP 1 MINUTE]WHERE { ?WaveObs a sea:WaveHeightObservation; sea:hasValue ?waveheight; }

Query translation

Query ProcessingC

lient

Mappings

SPARQLStream

[tuples]

Sensor Network

Data translation[triples]

GSN API

:Wan4WindSpeed a rr:TriplesMapClass; rr:tableName "wan7"; rr:subjectMap [ rr:template "http://swissex.ch/ns#WindSpeed/Wan7/{timed}"; rr:class ssn:ObservationValue; rr:graph ssg:swissexsnow.srdf ]; rr:predicateObjectMap [ rr:predicateMap [ rr:predicate ssn:hasQuantityValue ]; rr:objectMap[ rr:column "sp_wind" ] ];

R2RML Mappings

http://montblanc.slf.ch :22001/ multidata ?vs [0]= wan7 &field [0]= sp_wind

Translation overhead

26Sensors, Mappings and Queries

Conclusions

• Use of the SSN Ontology• Sensor metadata• Sensor observations

• Using R2RML mappings for virtual sensors• We can translate to query languages and APIs

• Abstract expressions for representing queries

• Applications• Improved sensor search• Federated environment• Schema heterogeneity

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TODO

• Explore expressivity of queries• Expose as Linked Stream Data• Integrate with stored RDF data• Apply to other environments

• Complex-event-processing engines• OGC SOS Services• Pachube• etc

• Experimentation• Latency• Performance• Tuple rates• Query complexity

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Thanks!

http://code.google.com/p/semanticstreams/

Questions, please.

jp.calbimonte@upm.es

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