Increasingly, people's digital identities are attached to, and expressed through, their mobile devices. At the same time digital sensors pervade smart environments in which people are immersed. This paper explores different perspectives in which users' modelling features can be expressed through the information obtained by their attached personal sensors. We introduce the PreSense Ontology, which is designed to assign meaning to sensors' observations in terms of user modelling features. We believe that the Sensing Presence PreSense Ontology is a first step toward the integration of user modelling and "smart environments". In order to motivate our work we present a scenario and demonstrate how the ontology could be applied in order to enable context-sensitive services.

1. Sensing Presence (PreSense) Ontology –
User Modelling in the Seman3c Sensor Web
A.E. Cano, A.‐S. Dadzie, V.S. Uren, F. Ciravegna
The Oak Group,
Department of Computer Science,
The University of Sheffield
PreSense: User Modelling in the Seman3c Sensor Web

2. Outline
• Introduc3on/Mo3va3on
• Related Work
• Sensors & User Context
• Aims & Challenges
– Scenario of Use
• PreSense Ontology
– Requirements
– Design
– Usage
• Conclusions
PreSense: User Modelling in the Seman3c Sensor Web

3. Introduc3on/Mo3va3on –
Mobiles, Sensors & Smart Environments
PreSense: User Modelling in the Seman3c Sensor Web

4. Outline
• Introduc3on/Mo3va3on
• Related Work
• Sensors & User Context
• Aims & Challenges
– Scenario of Use
• PreSense Ontology
– Requirements
– Design
– Usage
• Conclusions
PreSense: User Modelling in the Seman3c Sensor Web

5. Introduc3on/Mo3va3on
• the need to iden3fy:
– users’ aVached sensors
– the observa3ons of these sensors as physical and online resources
• address the data streams generated as users’ feature proper3es
• exis3ng ontologies address some of the requirements to handle
this:
PreSense: User Modelling in the Seman3c Sensor Web

6. Outline
• Introduc3on/Mo3va3on
• Related Work
• Sensors & User Context
• Aims & Challenges
– Scenario of Use
• PreSense Ontology
– Requirements
– Design
– Usage
• Conclusions
PreSense: User Modelling in the Seman3c Sensor Web

7. Sensors & User Context
Static/Stable Features
Work place
Name
PreSense: User Modelling in the Seman3c Sensor Web

8. Sensors & User Context
Static/Stable Features
Name
Work place
Highly changing Features
Position
Interests
PreSense: User Modelling in the Seman3c Sensor Web

9. Outline
• Introduc3on/Mo3va3on
• Related Work
• Sensors & User Context
• Aims & Challenges
– Scenario of Use
• PreSense Ontology
– Requirements
– Design
– Usage
• Conclusions
PreSense: User Modelling in the Seman3c Sensor Web

10. Aims & Challenges
• current user modelling methods
– depict the digital iden3ty of a given person
– consider sensor informa3on distributed across physical and online worlds
• explore new techniques for combining:
– sta3c/stable features
– dynamic or highly changing features
• explore different perspec3ves in which the aVachment of sensor
data feeds into user models
– capture interac3on with smart objects and environments
– make use of surrounding, real‐3me context
– by aVaching sensor data streams (physical and virtual) to user profiles
PreSense: User Modelling in the Seman3c Sensor Web

11. Outline
• Introduc3on/Mo3va3on
• Related Work
• Sensors & User Context
• Aims & Challenges
– Scenario of Use
• PreSense Ontology
– Requirements
– Design
– Usage
• Conclusions
PreSense: User Modelling in the Seman3c Sensor Web

12. Scenario
PreSense: User Modelling in the Seman3c Sensor Web

13. Scenario – Challenges Portrayed
• access to networks
– WAN/LAN
– bluetooth, other local wireless networks
• currency and validity of informa3on
• physical presence data vs online presence data
• verifica3on of iden3ty
– associa3on of sensor data with en33es/individuals
– trust, privacy – what informa3on should be shared, and with
whom
PreSense: User Modelling in the Seman3c Sensor Web

14. Outline
• Introduc3on/Mo3va3on
• Related Work
• Sensors & User Context
• Aims & Challenges
– Scenario of Use
• PreSense Ontology
– Requirements
– Design
– Usage
• Conclusions
PreSense: User Modelling in the Seman3c Sensor Web

15. PreSense Ontology ‐ Requirements
• Iden3fica3on and Addressability
• Sensor Ownership and Provenance
• Associa3on of Sensor Data and Profile Informa3on
• Privacy in Data Streams
• Sensor Data Expira3on
• Interac3on with Smart En33es
• Integrate Physical and Virtual Presence S3muli
PreSense: User Modelling in the Seman3c Sensor Web

16. Outline
• Introduc3on/Mo3va3on
• Related Work
• Sensors & User Context
• Aims & Challenges
– Scenario of Use
• PreSense Ontology
– Requirements
– Design
– Usage
• Conclusions
PreSense: User Modelling in the Seman3c Sensor Web

17. Imported Ontologies
• Seman3c Sensor Network Incubator Group (SSN‐XG)
– to model sensors
• FOAF
– to model en33es, e.g., Person
• Provenance Vocabulary (PRV)
– provenance‐related metadata for sensors and their owners
• Web of Trust (WOT)
– to verify ownership of a sensor
• Online Presence Ontology (OPO)
– users' online presence proper3es
• Dolce Ultralight Ontology (DUL)
• to model selected proper3es of an en3ty, e.g., context
PreSense: User Modelling in the Seman3c Sensor Web

18. PreSense Core Concepts –
Entity
• func3ons
– describe iden33es of Persons and other en33es to whom sensor data is aVached
– prevent falsifica3on of provenance (through wot:User)
• aVaches sensors to En33es using ps:hasSensor property
PreSense: User Modelling in the Seman3c Sensor Web

19. PreSense Core Concepts –
Sensor
• a physical object that detects, observes and measures a
s3mulus
– ps:attachedTo property used to indicate Entity to which a Sensor
is aVached
PreSense: User Modelling in the Seman3c Sensor Web

20. PreSense Core Concepts –
PhysicalPresence
• aggrega3on of physical proper3es
• derived by sensors observing physical s3muli exhibited by an
Entity, e.g., physical loca3on, blood glucose levels
PreSense: User Modelling in the Seman3c Sensor Web

21. PreSense Core Concepts –
OnlinePresence
• abstrac3on of the aggrega3on of online proper3es exhibited by an
Entity,
– e.g., detec3on of change of status on a social network site
• derived by virtual sensors observing s3muli
PreSense: User Modelling in the Seman3c Sensor Web

22. PreSense Core Concepts –
FeaturePropertyAssociation
• bridge between a sensor's observed s3mulus and the feature
that this s3mulus characterises in a user, e.g.,
– a sensor observes changes in Bob’s BloodGlucose levels ‐ the
feature of interest
– this associa3on enables Alice to monitor Bob’s sugar levels
PreSense: User Modelling in the Seman3c Sensor Web

23. PreSense Ontology
PreSense: User Modelling in the Seman3c Sensor Web
Complete ontology available at: http://purl.org/net/preSense/ns

24. PreSense Ontology
Match of core PreSense ontology components to requirements
PreSense: User Modelling in the Seman3c Sensor Web

25. Outline
• Introduc3on/Mo3va3on
• Related Work
• Sensors & User Context
• Aims & Challenges
– Scenario of Use
• PreSense Ontology
– Requirements
– Design
– Usage
• Conclusions
PreSense: User Modelling in the Seman3c Sensor Web

26. Scenario Reminder
PreSense: User Modelling in the Seman3c Sensor Web

27. PreSense Ontology ‐ Modules
• modelling aspects of the user’s physical proper3es using
PreSense
– e.g., monitoring Bob’s glucose levels
– handles features related to Location and PhysiologicalState
PreSense: User Modelling in the Seman3c Sensor Web

28. PreSense Ontology ‐ Modules
@prefix ps: <http://purl.org/net/preSense/ns#> .
@prefix physioState: <http://purl.org/net/preSense/physioState/ns#> .
@prefix prvTypes: <http://purl.org/net/provenance/types#> .
@prefix prv: <http://purl.org/net/provenance/ns> .
@prefix ps: <http://purl.org/net/preSense/ns#> .
@prefix ssn: <http://purl.oclc.org/NET/ssnx/ssn#> .
<http://my.identity.org/Bob> a ps:Entity, a foaf:Person;
@prefix physioState: <http://purl.org/net/
ps:hasSensor <http://my.identity.org/Bob/sensors/glSen1/>.
ps:declaresPresence _:p1.
preSensephysioState/ns#> .
_:p1 a ps:Presence;
@prefix prvTypes: <http://purl.org/net/provenance/types#> .
ps:hasPresenceComponent _:phyPr.
@prefix prv: <http://purl.org/net/provenance/ns> .
_:phyPr a ps:PhysicalPresence;
@prefix ssn: <http://purl.oclc.org/NET/ssnx/ssn#> .
ps:hasPresenceProperty _:prop1.
_:prop1 a physioState:GlucoseLevel;
ps:hasPresenceProperty _:glucoseLevel.
<http://my.identity.org/Bob> a ps:Entity, a foaf:Person;
ps:isPropertyOf _:bloodGlucose .
ps:hasSensor <http://my.identity.org/Bob/sensors/glSen1/>.
<http://my.identity.org/Bob/sensors/glSen1/>
ps:declaresPresence _:p1.
a ssn:Sensor, prv:Actor, prvTypes:Sensor;
prv:operatedBy <http://my.identity.org/Bob> .
_
prv:observedBy <http://my.identity.org/Bob/sos/observations/glSen1/>.
<http://my.identity.org/Bob/sos/observations/glSen1/> a ssn:Observation;
ssn:observedProperty _:glucoseLevel.
_:glucoseLevel a ssn:Property, ps:PresenceProperty;
ssn:isPropertyOf _:bloodGlucose.
_:bloodGlucose a ps:FeaturePropertyAssociation;
PreSense: User Modelling in the Seman3c Sensor Web

29. PreSense Ontology ‐ Modules
@prefix ps: <http://purl.org/net/preSense/ns#> .
@prefix physioState: <http://purl.org/net/preSense/physioState/ns#> .
@prefix prvTypes: <http://purl.org/net/provenance/types#> .
@prefix prv: <http://purl.org/net/provenance/ns> .
@prefix ssn: <http://purl.oclc.org/NET/ssnx/ssn#> .
<http://my.identity.org/Bob> a ps:Entity, a foaf:Person;
ps:hasSensor <http://my.identity.org/Bob/sensors/glSen1/>.
ps:declaresPresence _:p1.
_:p1 a ps:Presence;
_:p1 a ps:Presence;
ps:hasPresenceComponent _:phyPr.
ps:hasPresenceComponent _:phyPr.
_:phyPr a ps:PhysicalPresence;
_:phyPr a ps:PhysicalPresence;
ps:hasPresenceProperty _:prop1.
ps:hasPresenceProperty _:prop1.
_:prop1 a physioState:GlucoseLevel;
ps:hasPresenceProperty _:glucoseLevel.
_:bloodGlucose .
_:prop1 a physioState:GlucoseLevel;
<http://my.identity.org/Bob/sensors/glSen1/>
ps:hasPresenceProperty _:glucoseLevel.
a ssn:Sensor, prv:Actor, prvTypes:Sensor;
prv:operatedBy <http://my.identity.org/Bob> .
ps:isPropertyOf _:bloodGlucose .
prv:observedBy <http://my.identity.org/Bob/sos/observations/glSen1/>.
<http://my.identity.org/Bob/sos/observations/glSen1/> a ssn:Observation;
ssn:observedProperty _:glucoseLevel.
_:glucoseLevel a ssn:Property, ps:PresenceProperty;
ssn:isPropertyOf _:bloodGlucose.
_:bloodGlucose a ps:FeaturePropertyAssociation;
PreSense: User Modelling in the Seman3c Sensor Web

30. PreSense Ontology ‐ Modules
@prefix ps: <http://purl.org/net/preSense/ns#> .
@prefix physioState: <http://purl.org/net/preSense/physioState/ns#> .
@prefix prvTypes: <http://purl.org/net/provenance/types#> .
@prefix prv: <http://purl.org/net/provenance/ns> .
@prefix ssn: <http://purl.oclc.org/NET/ssnx/ssn#> .
<http://my.identity.org/Bob> a ps:Entity, a foaf:Person;
<http://my.identity.org/Bob/sensors/glSen1/>
ps:hasSensor <http://my.identity.org/Bob/sensors/glSen1/>.
ps:declaresPresence _:p1.
a ssn:Sensor, prv:Actor, prvTypes:Sensor;
_:p1 a ps:Presence;
prv:operatedBy <http://my.identity.org/Bob> .
ps:hasPresenceComponent _:phyPr.
prv:observedBy <http://my.identity.org/Bob/sos/
_:phyPr a ps:PhysicalPresence;
observations/glSen1/>.
ps:hasPresenceProperty _:prop1.
<http://my.identity.org/Bob/sos/observations/glSen1/>
_:prop1 a physioState:GlucoseLevel;
ps:hasPresenceProperty _:glucoseLevel.
a ssn:Observation;
ps:isPropertyOf _:bloodGlucose .
ssn:observedProperty _:glucoseLevel.
<http://my.identity.org/Bob/sensors/glSen1/>
_:glucoseLevelprv:Actor, prvTypes:Sensor;
.
ps:PresenceProperty;
a ssn:Sensor,
a ssn:Property,
prv:operatedBy <http://my.identity.org/Bob>
ssn:isPropertyOf _:bloodGlucose.
a ssn:Observation;
prv:observedBy <http://my.identity.org/Bob/sos/observations/glSen1/>.
<http://my.identity.org/Bob/sos/observations/glSen1/>
_:bloodGlucose a ps:FeaturePropertyAssociation;
ssn:observedProperty _:glucoseLevel.
_:glucoseLevel a ssn:Property, ps:PresenceProperty;
ssn:isPropertyOf _:bloodGlucose.
_:bloodGlucose a ps:FeaturePropertyAssociation;
PreSense: User Modelling in the Seman3c Sensor Web

31. PreSense Ontology ‐ Modules
• Modeling aspects of the user’s online (virtual) presence using
PreSense
– e.g., monitoring Bob’s tweet stream
– handles features related to OnlineStatusStream
PreSense: User Modelling in the Seman3c Sensor Web

32. PreSense Ontology ‐ Modules
<http://my.identity.org/Bob> a ps:Entity, a foaf:Person;
ps:hasSensor <http://my.identity.org/Bob/sensors/stSen1/>.
<http://my.identity.org/Bob> a ps:Entity, a foaf:Person; ps:hasSensor <http://my.identity.org/Bob/
sensors/stSen1/>.
ps:declaresPresence _:p1.
ps:declaresPresence _:p1.
_:p1a a ps:Presence;
_:p1 ps:Presence;
ps:hasPresenceComponent _:onlPr.
ps:hasPresenceComponent _:onlPr.
_:onlPr a ps:OnlinePresence;
_:onlPr a ps:OnlinePresence;
ps:hasPresenceProperty _:prop2.
ps:hasPresenceProperty _:prop2.
_:prop2 a ps:OnlineStatusStream; ps:hasPresenceProperty :personalStatusStream.
ps:isPropertyOf :twitterStatusStream .
_:prop2 a ps:OnlineStatusStream;
ps:hasPresenceProperty :personalStatusStream.
<http://my.identity.org/Bob/ /stSen1/> a ssn:Sensor, prv:Actor, prvTypes:Sensor;
ps:isPropertyOf :twitterStatusStream <http://my.identity.org/Bob/sos/
prv:operatedBy <http://my.identity.org/Bob> . prv:observedBy .
observations/stSen1/>.<http://my.identity.org/Bob/sos/observations/stSen1/> a ssn:Observation;
ssn:observedProperty :personalStatusStream
.:personalStatusStreama ssn:Property, ps:PresenceProperty;
ssn:isPropertyOf :twitterStatusStream.:twitterStatusStreama ps:FeaturePropertyAssociation
PreSense: User Modelling in the Seman3c Sensor Web

33. PreSense Ontology ‐ Modules
<http://my.identity.org/Bob/sensors/stSen1/> a ssn:Sensor;
<http://my.identity.org/Bob> a ps:Entity, a foaf:Person; ps:hasSensor <http://my.identity.org/Bob/
prv:operatedBy <http://my.identity.org/Bob> .
sensors/stSen1/>.
prv:observedBy <http://my.identity.org/Bob/sos/observations/
ps:declaresPresence _:p1.
stSen1/>.
_:p1 a ps:Presence;
<http://my.identity.org/Bob/sos/observations/stSen1/> a
ps:hasPresenceComponent _:onlPr.
ssn:Observation;
ssn:observedProperty _:personalStatusStream.
_:onlPr a ps:OnlinePresence;
ps:hasPresenceProperty _:prop2.
_:personalStatusStream a ssn:Property, ps:PresenceProperty;
ssn:isPropertyOf _:twitterStatusStream.
_:prop2 a ps:OnlineStatusStream; ps:hasPresenceProperty :personalStatusStream.
_:twitterStatusStream a ps:FeaturePropertyAssociation
ps:isPropertyOf :twitterStatusStream .
<http://my.identity.org/Bob/ /stSen1/> a ssn:Sensor, prv:Actor, prvTypes:Sensor;
prv:operatedBy <http://my.identity.org/Bob> . prv:observedBy <http://my.identity.org/Bob/sos/
observations/stSen1/>.<http://my.identity.org/Bob/sos/observations/stSen1/> a ssn:Observation;
ssn:observedProperty :personalStatusStream
.:personalStatusStreama ssn:Property, ps:PresenceProperty;
ssn:isPropertyOf :twitterStatusStream.:twitterStatusStreama ps:FeaturePropertyAssociation
PreSense: User Modelling in the Seman3c Sensor Web

34. Outline
• Introduc3on/Mo3va3on
• Related Work
• Sensors & User Context
• Aims & Challenges
– Scenario of Use
• PreSense Ontology
– Requirements
– Design
– Usage
• Conclusions
PreSense: User Modelling in the Seman3c Sensor Web

35. Conclusions
The PreSense Ontology, compared to exis3ng, standard models –
fulfilment of requirements
PreSense: User Modelling in the Seman3c Sensor Web

36. Next Steps
• further development of PreSense modules
– to address interac3on with smart en33es and environments, e.g.,
• mapping user loca3ons to NearByPOIs and NearByFriends
• tes3ng applica3on of PreSense in real world scenarios
– by exploring new environments and ongoing events
– plans to evaluate PreSense during Sheffield 2011 Tramlines Fes3val
• link users’ ps:PhysicalPresence (via mobile GPS) to
ps:OnlinePresence (via twiVer and public Facebook feeds)
• collect and broadcast informa3on, e.g.,
– par3cipants’ interests in music and fes3vals (Events)
– preferences when exploring new loca3ons (NearByPOIs)
– informa3on on NearByFriends
PreSense: User Modelling in the Seman3c Sensor Web

37. Find this online at...
PreSense: User Modelling in the Seman3c Sensor Web