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XGSN: An Open-source 
Semantic Sensing Middleware 
for the Web of Things 
Some Afterthoughts 
@jpcik 
Jean-Paul Calbimonte, Sofiane Sarni, Julien Eberle, Karl Aberer 
LSIR EPFL 
Semantic Sensor Networks SSN 2014. International Semantic Web Conference ISWC 2014 
Riva del Garda, 20.10.2014
Sensor deployments everywhere 
Mountains 
Glaciers 
Snow regions 
Sea 
Coastal 
Agriculture 
… 
People want the data! 
DIY 
Mobile 
Participatory
So what can I do with it? 
• Get data from my sensors (API, web interface) 
• Store and archive the data 
• Put it online, available for download 
• Put it online, available for discovery and querying 
• Apply post-processing to the data 
• Combine different data sources 
• Use the data from an R script 
• More stuff…
OSPER - Swiss Experiment 
Open support platform for environmental research 
managing environmental 
sensor data &metadata Platform 
Multidisciplinary research team 
• Real world data + problems 
Facilitating research in: 
• Precipitation patterns in mountains 
• Evaporation in Africa 
• Return periods of Natural Hazards 
• Stream flows in Alpine catchments 
• Permafrost in the Alps 
acquisition 
processing 
Data 
heterogeneous 
sensing devices 
summarization, filtering, 
compression, interpolation 
continuous processing, 
streaming, geospatial, aggregation 
pattern discovery, 
correlation, regression 
metadata management, semantics 
data services, visualization, standards 
querying 
analysis 
discovery 
provision 
http://swiss-experiment.ch
OpenSense2 
Crowdsourcing High-Resolution Air Quality Sensing 
global concern 
highly location-dependent 
time-dependent 
Air Pollution 
Accurate location-dependent and real-time information on air pollution is needed 
Integrated air quality measurement platform 
Personal mobile sensors CrowdSense 
 Heterogeneous devices and data 
 Human activity assessment, lifestyle and health data 
• Link high-quality and low-quality data 
• Integration of pure statistical models and physical 
dispersion models 
• Better coverage through crowdsensing 
• Incentives for crowd data provision 
• Finer temporal and spatial resolutions 
• Utilitarian approach for trade-off between model 
complexity, privacy and accuracy 
• Higher accuracy of pollution maps models 
http://opensense.epfl.ch 
Institutional stations 
OpenSense infrastructure
OpenIoT FP7 
Open Source Cloud solution for the Internet of Things 
Established Open-source platform for IoT 
• Integrate sensors & things with cloud computing 
• Configure, deploy and use IoT services 
• Auditing/assessing privacy of IoT apps in the cloud 
• Semantic annotations of internet-connected objects 
• Energy-efficient data harvesting 
• Publish/subscribe for continuous processing and 
sensor data filtering 
• Mobility of sensors and QoS aspects in IoT 
http://openiot.eu 
https://github.com/OpenIotOrg/openiot 
Use cases and validation scenarios 
Smart 
Manufacturing Campus Guide Air Monitoring 
Agriculture 
Sensing
The OpenIoT Architecture 
Semantic data management 
Sensor data management 
X-GSN 
goes here
GSN: Global Sensor Networks 
Managing sensor datasets 
Publishing sensor observations 
Discovery and exploration of datasets 
Processing sensor time series
Open source project: Available in Github 
• Open Source License 
• Mainly in Java 
• Community Support 
• Used in several projects
Releases available in Github
The OpenIoT Architecture 
Semantic data management 
Sensor data management 
X-GSN 
goes here 
Discovery & Exploitations
Request Definition & Presentation 
12 
Everything nice if your data is also nice
Issues: here, there and everywhere 
13
GSN architecture 
14 
security 
data access interfaces 
query processing 
storage 
data acquisition 
preprocessing
GSN: distributed deployment 
15 
pluggable output 
pluggable input 
standards? 
discovery? 
vocabularies? 
semantics?
GSN REST interfaces: e.g JSON 
16 
Request all sensors in 
this GSN instance 
Standard vocabs? 
Semantics?
SSN Ontology, for sure 
cf-feat:soil 
ssn:inDeployment ssn:SensingDevice 
dul:hasLocation 
17 
ssn:Sensor 
ssn:Platform 
ssn:FeatureOfInterest 
ssn:Deployment 
ssn:Property 
cf-prop:air_temperature 
ssn:observes 
ssn:onPlatform 
dul:Place 
qu:QuantityKind 
dim:Temperature 
ssn:MeasurementCapability 
ssn:MeasurementProperty 
geo:lat, geo:lng 
xsd:double 
ssn:hasMeasurementProperty 
ssn:Accuracy 
ssn:ofFeature 
aws:TemperatureSensor 
aws:Thermistor 
ssn:Latency 
cf-prop:soil_temperature 
cf-feat:Wind 
cf-feat:Surface 
cf-feat:Medium 
cf-feat:air 
dim:VelocityOrSpeed 
cf-prop:wind_speed 
cf-prop:rainfall_rate 
aws:CapacitiveBead … 
… 
… 
Where to look for vocabs? 
When do we set up the onto? 
Who sets it up? 
http://lsm.deri.ie/resource/40390026 
68863045 
http://lsm.deri.ie/ont/lsm.o 
wl#unit 
"Percent"
Ontologies in OpenIoT 
18 
‘configure’ ontologies 
here 
But sensors and wrappers configured here 
Virtual Sensors
Data in GSN through Wrappers 
19 
Common abstractions, independent of applications, hardware 
Simple integration & data correlation. 
5140 
GSN 
Various 
Applications 
Plug & Play 
deployment 
On-the-fly 
reconfiguration 
GSN 
GSN
Virtual Sensor configuration 
20 
<virtual-sensor name="room-monitor" > 
<addressing> 
<predicate key="geographical">BC143</predicate> 
<predicate key="usage"> 
room monitoring</predicate> 
</addressing> 
<life-cycle pool-size="10" /> 
<output-structure> 
<field name="image" type="binary:image/jpeg" /> 
<field name="temp" type="int" /> 
</output-structure> 
<storage permanent="true" history-size="10h" /> 
<input-streams> 
<input-stream name="cam"> 
<stream-source alias="cam" storage-size="1“ 
sampling-rate=“1”> 
<address wrapper=“tinyos2.x"> 
<predicate key=“host">tinybox.epfl.ch 
</predicate> 
<predicate key=“port">9001</predicate> 
</address> 
select * from WRAPPER 
</stream-source> 
<stream-source alias="temperature1“ 
storage-size="1m“ sampling-rate=“1”> 
<address wrapper="remote"> 
<predicate key="type">temperature</predicate> 
<predicate key="geographical">BC143-N 
</predicate> 
</address> 
select AVG(temp1) as T1 from WRAPPER 
</stream-source> 
<stream-source alias="temperature2“ 
storage-size="1m“> 
<address wrapper="remote"> 
<predicate key="type“>temperature</predicate> 
<predicate key="geographical“>BC143-S 
</predicate> 
</address> 
select AVG(temp2) as T2 from WRAPPER 
</stream-source> 
<query> 
select cam.picture as image, temperature.T1 
as temp from cam, temperature1 
where temperature1.T1 > 30 AND 
temperature1.T1 = temperature2.T2 
</query> 
</input-stream> 
</input-streams> 
</virtual-sensor> 
Some metadata is here 
Sensor metadata configuration
Some available mappings 
21 
• HTTP generic wrapper 
• devices accessible via HTTP GET or POST requests, e.g., the AXIS206W wireless camera 
• Serial forwarder wrapper 
• enables interaction with TinyOS compatible motes (standard access in TinyOS) 
• USB camera wrapper 
• local USB connection. 
• supports cameras with OV518 and OV511 chips. 
• RFID wrapper 
• access to Texas Instruments Series 6000 S6700 multi-protocol RFID readers 
• Alien Technologies long range RFID reader 8950 EU. 
• WiseNode wrapper 
• access to WiseNode sensors (CSEM, Switzerland, http://www.csem.ch/) 
• Generic UDP wrapper 
• any device using the UDP protocol 
• Generic serial/bluetooth wrapper 
• supports sensing devices which send data through the serial port, e.g., EPuck robots, etc.
Register metadata 
22 
If ontologies change… 
If we add new types of sensors? 
Do I have control over my sensor metadata?
Metadata properties 
23 
sensorID="http://lsm.deri.ie/resource/1099207032411018" 
sensorName=closedsense 
source=“Some source" 
sourceType=lausanne 
sensorType=lausanne 
information=Air Quality Sensors from Lausanne station 1 
author=opensense 
feature="http://lsm.deri.ie/OpenIoT/opensensefeature" 
fields="humidity,temperature" 
field.temperature.propertyName="http://lsm.deri.ie/OpenIoT/ 
Temperature" 
field.temperature.unit=C 
field.humidity.propertyName="http://lsm.deri.ie/OpenIoT/Hu 
midity" 
field.humidity.unit=Percent 
field.co.propertyName="http://lsm.deri.ie/OpenIoT/CO" 
field.co.unit=PPM 
latitude=46.529838 
longitude=6.596818
Turtle RDF registration 
24 
<sensor/5010> rdf:type aws:CapacitiveBead,ssn:Sensor; 
rdfs:label "Sensor 5010"; 
ssn:observes aws:air_temperature ; 
phenonet:hasSerialNumber 
<sensor/5010/serial/serial2> ; 
ssn:onPlatform <site/narrabri/Pweather> ; 
ssn:ofFeature <site/narrabri/sf/sf_narrabri> ; 
ssn:hasMeasurementProperty 
<sensor/5010/accuracy/acc_1> ; 
prov:wasGeneratedBy "AuthorName"; 
DUL:hasLocation <place/location1>; 
lsm:hasSensorType <sensorType1>; 
lsm:hasSourceType "SourceType". 
<sensorType1> rdfs:label "TypeName". 
<sensor/5010/serial/serial2> rdf:type phenonet:SerialNumber; 
phenonet:hasId "5010" . 
A bit more of semantics 
Need tools for this
OpenIoT Schema Editor 
25
Mobile sensors issues 
ssn:inDeployment 
dul:hasLocation 
26 
ssn:FeatureOfInterest 
ssn:ofFeature 
ssn:Property 
ssn:observes 
ssn:Sensor 
ssn:SensingDevice 
ssn:Deployment 
ssn:Platform 
dul:Place 
geo:lat, geo:lng 
xsd:double 
But sensors move! 
‘Mobility context’ 
Places where the sensor is usually in…
URI issues 
• Auto-generated URIs: problematic naming 
• Generate a sensor URI: templating 
• Producing Duplicated Sensor registrations 
27
28 
Push observations 
Push observations 
there?
Push observations 
29
RDF observation annotations 
30 
CQELS stream processing 
When to store, when to stream? 
A-priori knowledge of the data usage
Why Streams? 
Web standards 
Data discovery 
Data sharing 
Web queries 
Go Web 
Semantics 
Vocabularies 
Data Harvesting 
Data linking 
Matching 
Integration 
Ontologies 
Expressivity 
Inference 
Rule processing 
Knowledge bases 
Reasoning 
Query languages 
Query answering 
Efficient processing 
Query Federation 
Processing 
Do we always 
require these? 
31 
In Practice?
Discussion 
• Annotation in IoT 
• Dynamic sensor data streams 
• Scalability 
• Ontologies & Vocabularies 
• Reuse, definition, policies 
• OpenIoT platform 
• Modules available 
• System integration 
32
Muchas 
gracias! 
@jpcik 
Jean-Paul Calbimonte 
LSIR EPFL

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An Open-source Semantic Sensing Middleware for the Web of Things

  • 1. XGSN: An Open-source Semantic Sensing Middleware for the Web of Things Some Afterthoughts @jpcik Jean-Paul Calbimonte, Sofiane Sarni, Julien Eberle, Karl Aberer LSIR EPFL Semantic Sensor Networks SSN 2014. International Semantic Web Conference ISWC 2014 Riva del Garda, 20.10.2014
  • 2. Sensor deployments everywhere Mountains Glaciers Snow regions Sea Coastal Agriculture … People want the data! DIY Mobile Participatory
  • 3. So what can I do with it? • Get data from my sensors (API, web interface) • Store and archive the data • Put it online, available for download • Put it online, available for discovery and querying • Apply post-processing to the data • Combine different data sources • Use the data from an R script • More stuff…
  • 4. OSPER - Swiss Experiment Open support platform for environmental research managing environmental sensor data &metadata Platform Multidisciplinary research team • Real world data + problems Facilitating research in: • Precipitation patterns in mountains • Evaporation in Africa • Return periods of Natural Hazards • Stream flows in Alpine catchments • Permafrost in the Alps acquisition processing Data heterogeneous sensing devices summarization, filtering, compression, interpolation continuous processing, streaming, geospatial, aggregation pattern discovery, correlation, regression metadata management, semantics data services, visualization, standards querying analysis discovery provision http://swiss-experiment.ch
  • 5. OpenSense2 Crowdsourcing High-Resolution Air Quality Sensing global concern highly location-dependent time-dependent Air Pollution Accurate location-dependent and real-time information on air pollution is needed Integrated air quality measurement platform Personal mobile sensors CrowdSense  Heterogeneous devices and data  Human activity assessment, lifestyle and health data • Link high-quality and low-quality data • Integration of pure statistical models and physical dispersion models • Better coverage through crowdsensing • Incentives for crowd data provision • Finer temporal and spatial resolutions • Utilitarian approach for trade-off between model complexity, privacy and accuracy • Higher accuracy of pollution maps models http://opensense.epfl.ch Institutional stations OpenSense infrastructure
  • 6. OpenIoT FP7 Open Source Cloud solution for the Internet of Things Established Open-source platform for IoT • Integrate sensors & things with cloud computing • Configure, deploy and use IoT services • Auditing/assessing privacy of IoT apps in the cloud • Semantic annotations of internet-connected objects • Energy-efficient data harvesting • Publish/subscribe for continuous processing and sensor data filtering • Mobility of sensors and QoS aspects in IoT http://openiot.eu https://github.com/OpenIotOrg/openiot Use cases and validation scenarios Smart Manufacturing Campus Guide Air Monitoring Agriculture Sensing
  • 7. The OpenIoT Architecture Semantic data management Sensor data management X-GSN goes here
  • 8. GSN: Global Sensor Networks Managing sensor datasets Publishing sensor observations Discovery and exploration of datasets Processing sensor time series
  • 9. Open source project: Available in Github • Open Source License • Mainly in Java • Community Support • Used in several projects
  • 11. The OpenIoT Architecture Semantic data management Sensor data management X-GSN goes here Discovery & Exploitations
  • 12. Request Definition & Presentation 12 Everything nice if your data is also nice
  • 13. Issues: here, there and everywhere 13
  • 14. GSN architecture 14 security data access interfaces query processing storage data acquisition preprocessing
  • 15. GSN: distributed deployment 15 pluggable output pluggable input standards? discovery? vocabularies? semantics?
  • 16. GSN REST interfaces: e.g JSON 16 Request all sensors in this GSN instance Standard vocabs? Semantics?
  • 17. SSN Ontology, for sure cf-feat:soil ssn:inDeployment ssn:SensingDevice dul:hasLocation 17 ssn:Sensor ssn:Platform ssn:FeatureOfInterest ssn:Deployment ssn:Property cf-prop:air_temperature ssn:observes ssn:onPlatform dul:Place qu:QuantityKind dim:Temperature ssn:MeasurementCapability ssn:MeasurementProperty geo:lat, geo:lng xsd:double ssn:hasMeasurementProperty ssn:Accuracy ssn:ofFeature aws:TemperatureSensor aws:Thermistor ssn:Latency cf-prop:soil_temperature cf-feat:Wind cf-feat:Surface cf-feat:Medium cf-feat:air dim:VelocityOrSpeed cf-prop:wind_speed cf-prop:rainfall_rate aws:CapacitiveBead … … … Where to look for vocabs? When do we set up the onto? Who sets it up? http://lsm.deri.ie/resource/40390026 68863045 http://lsm.deri.ie/ont/lsm.o wl#unit "Percent"
  • 18. Ontologies in OpenIoT 18 ‘configure’ ontologies here But sensors and wrappers configured here Virtual Sensors
  • 19. Data in GSN through Wrappers 19 Common abstractions, independent of applications, hardware Simple integration & data correlation. 5140 GSN Various Applications Plug & Play deployment On-the-fly reconfiguration GSN GSN
  • 20. Virtual Sensor configuration 20 <virtual-sensor name="room-monitor" > <addressing> <predicate key="geographical">BC143</predicate> <predicate key="usage"> room monitoring</predicate> </addressing> <life-cycle pool-size="10" /> <output-structure> <field name="image" type="binary:image/jpeg" /> <field name="temp" type="int" /> </output-structure> <storage permanent="true" history-size="10h" /> <input-streams> <input-stream name="cam"> <stream-source alias="cam" storage-size="1“ sampling-rate=“1”> <address wrapper=“tinyos2.x"> <predicate key=“host">tinybox.epfl.ch </predicate> <predicate key=“port">9001</predicate> </address> select * from WRAPPER </stream-source> <stream-source alias="temperature1“ storage-size="1m“ sampling-rate=“1”> <address wrapper="remote"> <predicate key="type">temperature</predicate> <predicate key="geographical">BC143-N </predicate> </address> select AVG(temp1) as T1 from WRAPPER </stream-source> <stream-source alias="temperature2“ storage-size="1m“> <address wrapper="remote"> <predicate key="type“>temperature</predicate> <predicate key="geographical“>BC143-S </predicate> </address> select AVG(temp2) as T2 from WRAPPER </stream-source> <query> select cam.picture as image, temperature.T1 as temp from cam, temperature1 where temperature1.T1 > 30 AND temperature1.T1 = temperature2.T2 </query> </input-stream> </input-streams> </virtual-sensor> Some metadata is here Sensor metadata configuration
  • 21. Some available mappings 21 • HTTP generic wrapper • devices accessible via HTTP GET or POST requests, e.g., the AXIS206W wireless camera • Serial forwarder wrapper • enables interaction with TinyOS compatible motes (standard access in TinyOS) • USB camera wrapper • local USB connection. • supports cameras with OV518 and OV511 chips. • RFID wrapper • access to Texas Instruments Series 6000 S6700 multi-protocol RFID readers • Alien Technologies long range RFID reader 8950 EU. • WiseNode wrapper • access to WiseNode sensors (CSEM, Switzerland, http://www.csem.ch/) • Generic UDP wrapper • any device using the UDP protocol • Generic serial/bluetooth wrapper • supports sensing devices which send data through the serial port, e.g., EPuck robots, etc.
  • 22. Register metadata 22 If ontologies change… If we add new types of sensors? Do I have control over my sensor metadata?
  • 23. Metadata properties 23 sensorID="http://lsm.deri.ie/resource/1099207032411018" sensorName=closedsense source=“Some source" sourceType=lausanne sensorType=lausanne information=Air Quality Sensors from Lausanne station 1 author=opensense feature="http://lsm.deri.ie/OpenIoT/opensensefeature" fields="humidity,temperature" field.temperature.propertyName="http://lsm.deri.ie/OpenIoT/ Temperature" field.temperature.unit=C field.humidity.propertyName="http://lsm.deri.ie/OpenIoT/Hu midity" field.humidity.unit=Percent field.co.propertyName="http://lsm.deri.ie/OpenIoT/CO" field.co.unit=PPM latitude=46.529838 longitude=6.596818
  • 24. Turtle RDF registration 24 <sensor/5010> rdf:type aws:CapacitiveBead,ssn:Sensor; rdfs:label "Sensor 5010"; ssn:observes aws:air_temperature ; phenonet:hasSerialNumber <sensor/5010/serial/serial2> ; ssn:onPlatform <site/narrabri/Pweather> ; ssn:ofFeature <site/narrabri/sf/sf_narrabri> ; ssn:hasMeasurementProperty <sensor/5010/accuracy/acc_1> ; prov:wasGeneratedBy "AuthorName"; DUL:hasLocation <place/location1>; lsm:hasSensorType <sensorType1>; lsm:hasSourceType "SourceType". <sensorType1> rdfs:label "TypeName". <sensor/5010/serial/serial2> rdf:type phenonet:SerialNumber; phenonet:hasId "5010" . A bit more of semantics Need tools for this
  • 26. Mobile sensors issues ssn:inDeployment dul:hasLocation 26 ssn:FeatureOfInterest ssn:ofFeature ssn:Property ssn:observes ssn:Sensor ssn:SensingDevice ssn:Deployment ssn:Platform dul:Place geo:lat, geo:lng xsd:double But sensors move! ‘Mobility context’ Places where the sensor is usually in…
  • 27. URI issues • Auto-generated URIs: problematic naming • Generate a sensor URI: templating • Producing Duplicated Sensor registrations 27
  • 28. 28 Push observations Push observations there?
  • 30. RDF observation annotations 30 CQELS stream processing When to store, when to stream? A-priori knowledge of the data usage
  • 31. Why Streams? Web standards Data discovery Data sharing Web queries Go Web Semantics Vocabularies Data Harvesting Data linking Matching Integration Ontologies Expressivity Inference Rule processing Knowledge bases Reasoning Query languages Query answering Efficient processing Query Federation Processing Do we always require these? 31 In Practice?
  • 32. Discussion • Annotation in IoT • Dynamic sensor data streams • Scalability • Ontologies & Vocabularies • Reuse, definition, policies • OpenIoT platform • Modules available • System integration 32
  • 33. Muchas gracias! @jpcik Jean-Paul Calbimonte LSIR EPFL