An approach to modeling short messages in spatio- temporal - - PowerPoint PPT Presentation

An approach to modeling short messages in spatio- temporal networks

Amosse EDOUARD, PhD student Nhan LE-THAN, Supervisor

Outline

• 1. Concept & Objective
• 2. The Radio Social Platform
• 3. Realisation
• 4. Contribution
• 5. Perspectives
• 6. Current Works

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Short messages

— People prefere to communicate with short

messages — Time constraints — Easy to produce & to share

— Technicals limitations/restrictions of mobile

sensors

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Motivation

« This traffic jam bothers me! »

« I am on Route des Lucioles at 6:00 P .M and there is a traffic jam which bothers me »

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Objective

— Semantic enrichment

— Spatial properties & thematic

— Platform for creating, managing and sharing spatio-

temporal information.

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Radio Social

Radio social

Thematic Reporter Redaction Broadcas ting Listener

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Use case

Moderate Traffic Moderate traffic Moderate traffic on Route des Colles Moderate traffic on Route des Colles

e-reporters e-listeners

Traffic Event

e-redaction e-diffusion

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Message structures

— Defined by the thematic — Qualificative : tags, symbols — Descriptive

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BRIEF

Message modeling & context enrichment

— Message — RS metadata

— Thematic — Reporter — Space — Time

M R T T S

Spatio-temporal context Semantic context

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Context infering

— Top down approach à Non trivial problem — Bottom up approach à The approach we use

è We aim to enrich the information context regard to user context

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Spatial Representation

— Geographical space — Set of dynamic and static objects

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Spatial modeling

— Dynamic spatial entities are modelized regard to

static entities

— Semantic and GIS infrastructures

— Google Maps & Places services — Geonames ontology

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Exemple

Geonames & Google Places

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43.6161871, 7.0677087

{

"long_name" : "Route des Lucioles", "short_name" : "Route des Lucioles", "types" : [ "route" ] }, :geo a :Feature shortName : "Route des Lucioles"; name : "Route des Lucioles"; wgs84_pos:lat "43.6161871"; wgs84_pos:long "7.0677087";

Spatial layers overlapping

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Time modelling

— We used the OWL Time — Instant for messages

:messageTi me a :Instant; :inXSDTime : 2014-03-20T10:30:00-5:00 ;

— Interval for event

:eventTime a :Interval; :hasBeginning: :eventStart ; :eventStart a :Instant; :inXSDTime 2014-03-20T10:30:00-5:00 ;

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The Ontology

— 9 classes — 13 ObjectProperty — 6 DatatypeProperty — Using existing ontologies

— OWL Time — GeoNames & WGS84 — FOAF

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Radio Sociale Ontology

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Technical architecture

JENA Model REST Services / SPARQL Endpoint EJB Container Entity Manager Data Model SPARQL Virtuoso JENA BEAN

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SPARQL Jax-B

Other use case

— Epidemic symptom report — The frequency : RASE — Annotation structure

— Disease : Flu — Symptom : cough, rheum — Metakeys : reliability, certitude

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RASE : Use case

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cough Flux Fiever

Valbonne 12/12/13 Flu

Flu symptom at Biot Emergence of a flu epidemic in Nice

Antibes 12/12/13 Fiever, cough

Contributions

— Short messages modeling — Spatial mobile Gentities modeling — The radio sociale ontology — Generic platform radio social platform

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Research keys and limitations

— Modeling thematic using existing ontologies

(DBPedia)

— Ontology-based user interfaces — Spatial reasoning

— What could be the incidence of an event on a region

to others

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Current works

— Qualitative spatial representation — Spatial reasonning

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Thank you !

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