Semantic Knowledge and Privacy in the Physical Web
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Transcript of Semantic Knowledge and Privacy in the Physical Web
Semantic Knowledge and Privacy in
the Physical WebPRAJIT KUMAR DAS, ABHAY KASHYAP,
GURPREET SINGH, CYNTHIA MATUSZEK, TIM FININ, ANUPAM JOSHI
UMBC ebiquity and IRAL Labs
Motivation
Our goal is to provide contextually aware information, using the IoT, that is privacy preserving and ubiquitously helpful
Image courtesy Batman Wikia
CARLTON
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IoT by Volume
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IoT by Domain
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IoT by Privacy Concerns
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Salient features CARLTON: A context-aware, NL question-
answer BOT Context derived from the Physical Web
(IoT) Under development, prototype system Simple NLP using tools like Stanford
CoreNLP Mobile app and Kiosk for front-end ABAC privacy model, Privacy rules using
SWRL Hierarchical context ontology Optional authentication for UMBC people
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Concretization of IoT
Small, quick seamless
interactions with
physical objects and
locations with your
device
Physical web: What?
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Physical web: What? Everything is a tap
away
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Physical web: What? See what’s useful
around you
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Physical web: What? Any object or place
can broadcast
content
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Physical web: How?Three main techniques
Nearby Connections
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Physical web: How?Three main techniques
Nearby Connections
Nearby Notifications
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Physical web: How?Three main techniques
Nearby Connections
Nearby Notifications
Nearby Messages
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System Overview
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System Overview
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System Overview
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Who is Tim Finin?
System Overview
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“Tim Finin”: Person Entity type
“Who”: WH query type
Text to Semi-Structured Text
Intent
Who is Tim Finin?
System Overview
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“Tim Finin”: Person Entity type
“Who”: WH query type
Text to Semi-Structured Text
Intent
SPARQL query generatorContext
Who is Tim Finin?
System Overview
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“Tim Finin”: Person Entity type
“Who”: WH query type
Text to Semi-Structured Text
Intent
SPARQL query generatorContext
Who is Tim Finin?
Inference EngineOntologyKnowledge base
System Overview
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“Tim Finin”: Person Entity type
“Who”: WH query type
Text to Semi-Structured Text
Intent
SPARQL query generatorContext
Who is Tim Finin?
Inference EngineResponse: JSON{“text”: “He’s a Professor in the
Computer Science department!”}
OntologyKnowledge base
System Overview
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Example query
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Is this room booked from
2PM-3PM?
Example query
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User is a faculty and is in front of Conf. room 1.
Is this room booked from
2PM-3PM?
Example query
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Conf. room 1 calendar has no events during that time.
Is this room booked from
2PM-3PM?
Example query
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Is this room booked from
2PM-3PM? No, would you like me to book it from
2PM – 3PM?
Example query
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Is this room booked from
2PM-3PM? No, would you like me to book it from
2PM – 3PM?Yes, please!
Example query
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Okay, the room has been booked
in your name from 2PM – 3PM
Is this room booked from
2PM-3PM? No, would you like me to book it from
2PM – 3PM?Yes, please!
Example query
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Example query
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Is Dr. Joshi here?
Example query
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Is Dr. Joshi here?
User could mean Dr. A. Joshi or Dr. K. Joshi.
Example query
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Is Dr. Joshi here?
But user is in front of Dr. A. Joshi’s office.
Example query
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Is Dr. Joshi here?
User is an advisee of Dr. A. JoshiExample query
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Is Dr. Joshi here?
Dr. Joshi is in a meeting till
3PM
Example query
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Example query
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Example query
Where is Dr. Finin’s office?
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Example queryUser is in CSEE building
Where is Dr. Finin’s office?
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Example query User is unknown to system
Where is Dr. Finin’s office?
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Example query
Where is Dr. Finin’s office?
Please see CSEE front desk for
required information
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Example1.@prefix crltn:<https://www.ebiquity.org/ontologies/carlton/0.1>.@prefix swrlb:<http://www.w3.org/2003/11/swrlb>.crltn: student(?requester)∧(
crltn: supervises(“Xavier”,?requester)∨(crltn: affiliatedWith(?requester,?labName) crltn: leads(“Xavier”,?labName))∧
)∧crltn: hasCurrentLocation(?requester,?aBldgLocation)∧crltn: room(?aBldgLocation) crltn: sitsIn(“Xavier”,?aBldgLocation)∧ ∧crltn: currentTime(?currTime) swrlb: Exists(?anEvent) crltn: speakingAt(“Xavier”,?anEvent)∧ ∧ ∧(
(crltn: startTime(?anEvent,?eventStartTime) swrlb: greaterThan(?eventStartTime,?∧currTime))∨
(crltn: endTime(?anEvent,?eventEndTime) swrlb: greaterThan(?currTime,?eventEndTime))∧) crltn: hasCurrentLocation(“Xavier”,?aLocation) crltn: Location(?aLocation)∧ ∧ ∧crltn: requestLocation(“Xavier”)⇒shareLocation(?aLocation)
Policy Example
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supervises(“Xavier”,?requester)OR(
affiliatedWith(?requester,?labName)ANDleads(“Xavier”,?labName)
)
Policy Example
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hasCurrentLocation(?requester,?aBldgLocation) ANDroom(?aBldgLocation) AND sitsIn(“Xavier”,?aBldgLocation)=>shareLocation(?aLocation)
Policy Example
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Future work Prototype system constantly adding
conversations Beacons on robots Reason over robots near you How robots respond to instructions?
“Can you take me to Prof. Matuszek now?”
“Show me the way to the ITE 346 conference room”
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Summary We presented CARLTON A context-aware, NL question-answer BOT Context derived from the Physical Web (IoT) Semantic web technologies used to preserve
data privacyThanks to NSF for the travel grant!
and Thanks to Google for the gift of
beacons! Slide 44 of 44