Semantic Web applications for mobility and social interaction

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Presentation outlook
Ana ROXIN – anamaria.roxin@gmail.com

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Introduction
3Ana ROXIN – anamaria.roxin@gmail.com

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Introduction – The Semantic Web

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Introduction – New issues…
Mobility • Pervasive service provisioning
• Context-aware services
• Pervasive service provisioning
• Context-aware services
Social
Interaction
• Web - Production of community-based knowledge
• Intranets - Better decision-making and greater
profitability
• Web - Production of community-based knowledge
• Intranets - Better decision-making and greater
profitability

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Introduction – Reasons to apply semantics
Improve discovery protocolsMobility
• Overcome expressivity limitations of traditional discovery models
• Enable automated reasoning about interacting entities
Overcome existing boundariesSocial interactions
• Create bridges between isolated communities of users and their data
• Social Semantic Web = network of interlinked and semantically-rich knowledge

|457Ana ROXIN – anamaria.roxin@gmail.com

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Different layers of interoperability
• Concerns bottom layers of ISO/OSI network hierarchy;
• Solved through hardware standards (Ethernet) and protocols (TCP/IP and HTTP).
Physical interoperabilityPhysical interoperability
• Concerns the syntactic form of exchanged messages;
• Realized through XML and syntactic standards (HTML, WSDL, SOAP)
Syntactic interoperabilitySyntactic interoperability
• Concerns the meaning of messages and Web pages;
• Allows automatic machine processing of information (selection, composition,
reasoning).
Semantic interoperabilitySemantic interoperability

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Ontologies as building bricks for the Semantic Web
• An extension of the current Web in which information is given well-defined
meaning, better enabling computers and people to work in cooperation
(T. Berners-Lee, J.A. Hendler, O. Lassila, “The Semantic Web”, Scientific American, vol. 284, no. 5, pp.
34-43, May 2001)
Semantic WebSemantic Web
• Explicit and shared specification of a conceptualization of a given knowledge
domain
(T. R. Gruber. Toward principles for the design of ontologies used for knowledge sharing. Presented at
the Padua workshop on Formal Ontology, March 1993)
OntologyOntology
From taxonomy to ontologyFrom taxonomy to ontology

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Ontology languages

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Flavors of semantic interoperability
• Minimal shared amount of information – the fact expressed in the statement itself
• Enabled by RDF (Resource Description Format)
• Ex: Object “Paris” is related to object “France” by “being its capital”.
Minimal semantic interoperabilityMinimal semantic interoperability
• Minimal set of beliefs on what two agents may infer after having exchanged a sentence
• Enabled by RDF Schema
• Ex: Shared ontology defining that capitals are cities, capitals are unique, etc.
Extended semantic interoperabilityExtended semantic interoperability
• Lower bound + upper bound on what agents may not believe after exchanging a sentence
• Enabled by OWL (Web Ontology Language)
• Ex: OWL shared ontology forbidding the belief of Grenoble is also a French capital.
Full semantic interoperabilityFull semantic interoperability

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Building bricks of the Semantic Web architecture

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RDF Ressource Description Framework
An RDF document is structured as an ensemble of triplets
An RDF triplet is an association {subject, predicate, object}
An RDF document is a labeled and oriented graph.
Object – Author ROX639
Subject – Document no42305
http://www.gsem.fr/documents#D42305

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OWL Web Ontology Language
Extension of RDF/RDFS languages
Adds new concepts
Specialization of RDF constructs

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SPARQL – Simple Protocol And RDF Query Language
• SELECT – retrieve information based on a particular
pattern
• CONSTRUCT – create an RDF graph based on RDF
input
• ASK – identify if a particular query pattern can be
matched on the queried RDF graph
• DESCRIBE – identify all triples related to the
particular object that must be described.
Query formsQuery forms
• SPARQL 1.1 Query – adds support for aggregates, sub-
queries, projected expressions, and negation
• SPARQL 1.1 Update – provides operations to update,
create and remove RDF graphs in a Graph Store
• SPARQL 1.1 Federation Extensions – defines the syntax
and semantics of a SPARQL 1.1 Query extension for
executing distributed queries over different endpoints
Latest add-onsLatest add-ons

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Mobile Semantic Web tools
XML ParsersXML Parsers
kXMLkXML
NanoXML
for J2ME
NanoXML
for J2ME
RDF
Frameworks
RDF
Frameworks
Mobile RDFMobile RDF
µJenaµJena
AndrojenaAndrojena
SMADSMAD
Query and
persistence
frameworks
Query and
persistence
frameworks
RDF On
the Go
RDF On
the Go
SWIPSWIP

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Examples of applications
2008
• Context-aware semantic web service
discovery
2008
• Context-aware semantic web service
discovery
2009
DBpedia Mobile
• Location-aware Linked Data browser
2009
DBpedia Mobile
• Location-aware Linked Data browser
2011
Siri / Iris
• Contextual, semantic, personalized search
engine
2011
Siri / Iris
• Contextual, semantic, personalized search
engine

Prototype application for Android-based mobile phones
Evaluate the feasibility of semantic discovery for mobile phones
Context-aware semantic web service discovery19

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Example – Extending OWL-S for context-aware
semantic Web service discovery – 1
20
ServiceService
Service
Profile
Service
Profile
Service
Model
Service
Model
Service
Grounding
Service
Grounding
Service
Context
Service
Context
ECommerce
Service
xsd:float
Information
Service
…
Emergency
Service
xsd:boolean
hasValue*

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1
2
3 4
1
2 3
4
5

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1
2
3
4
5

| 4523

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0 500 1000 1500 2000
1
1
3
5
10
67
68
201
335
788
199
174
483
834
1648
Time of execution (in ms)
Numberofservices
Premier test Deuxième test

Exploring the Geospatial Semantic Web with a Location-Enabled Linked Data
Browser
DBpedia Mobile25

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The Linking Open Data Project

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Application example – DBpedia Mobile
27
Main features Illustration

Personal assistants28

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Siri – A Virtual Personal Assistant
1966
• SRI recruited by
DoD
1966
• SRI recruited by
DoD
2003-2007
• CALO program
(DARPA funded)
2003-2007
• CALO program
(DARPA funded)
2007
• Foundation of
Siri
2007
• Foundation of
Siri
June 2009
• Tom Gruber
presentation of
Siri
June 2009
• Tom Gruber
presentation of
Siri
05/02/2010
• Siri launched on
iTunes Store
05/02/2010
• Siri launched on
iTunes Store
29/04/2010
• Apple buys Siri
29/04/2010
• Apple buys Siri
04/10/2011
• Siri part of iOS
5
04/10/2011
• Siri part of iOS
5
Does things for the user…Functionalities
•Multi-criteria vertical search and browse
•Various sources of information with integrated transactions and social communication:
•Web services and APIs – set of service providers
•Domain and task semantic models – grammar analyzer
•Guided dialog – speech-to-text analyzer
… but not anythingLimitations
•Can only perform a limited set of key tasks
•Can only understand words and sentences that pertain to key tasks
•Uses a simple semantic task model to map language to actions
•No deep parsing - the model does simple keyword matching and slot filling

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Android voice assistants
Uses
inference
EviEvi
Pulls
information
from True
Knowledge
IrisIris
Publishes
directly into
Google
calendar or
Evernote
SpeakToItSpeakToIt
Can be set
to listen at
launch +
email/text
reader
VlingoVlingo
Mostly for
directions
and
reminders
SkyviSkyvi
Google
voice
recognition
EdwinEdwin

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Social networks limitations
• User is required to re-enter profile and redefine social connections when registering for
each new social site.
Repeated registrationsRepeated registrations
• Obtain a complete set of content items that a person has created on all the sites that they
are registered on ?
• Find all the content created by a group of like-minded users in a distributed set of sites ?
Published contentPublished content
• The same information is repeated on different sites
• Relevant parts of information are distributed across several sites
Information duplication and distributionInformation duplication and distribution
• View such conversations across several community sites ?
Distributed discussionsDistributed discussions

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Semantic vocabularies for interlinking online
communities
FOAF – 2000FOAF – 2000
Vocabulary for
describing:
• Characteristics of people
and social groups,
• The things they create and
do.
SIOC – 2004SIOC – 2004
Integration of online
community
information
• Semantic Web ontology for
representing rich data from
the Social Web in RDF
SKOS – 2004SKOS – 2004
Common data model
for knowledge
organization systems
(thesauri, classification
schemes, subject
heading systems and
taxonomies)
• Explores the problem of
describing topics,
categories, "folksonomies"
and subject hierarchies.
RDFa – 2008RDFa – 2008
Set of XHTML
attributes to augment
visual data with
machine-readable
hints
OpenGraph – 2008OpenGraph – 2008
Uses <meta> tag
markup to deliver a
comprehensive view
of a web entity within
a user’s social graph.
• Based on RDFa
• May include geographic
information and contact
details.

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Relations between SIOC, FOAF and SKOS ontologies

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Interlinking online communities with RDFa
Ana ROXIN – ana.roxin@univ-fcomte.fr
One Person, Many User AccountsOne Person, Many User Accounts
Unified CommunitiesUnified Communities
Virtual ForumsVirtual Forums
http://www.facebook.com/anaroxin http://rdfs.org/sioc/ns#UserAccount
rdf:type
http://www.facebook.com/anaroxin#me
sioc:account_of
http://xmlns.com/foaf/0.1/Person
rdf:type
http://example.org/forums/metal http://rdfs.org/sioc/ns#Forum
rdf:type
#post
sioc:container_of
http://rdfs.org/sioc/ns#Post
rdf:type
_:resource1 http://rdfs.org/sioc/ns#Community
rdf:type
_:resource2
dcterms:hasPart
http://rdfs.org/sioc/ns#Site
rdf:type
sioc:space_of

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Using SIOC for data portability

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RDFa in Drupal 7

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Example: Twitris 2.0 Semantic Social Web application
http://twitris.knoesis.org/events/ows
Home page
Sentiment
analysis
Browse by
location
Network
analysis
Real-timeSearch

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Example: Factoetum
http://www.factoetum.com/Home

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Social websites interconnection

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Social Web + Semantic Web = Giant Global Graph
Social Web
• Authoring
• Architecture of participation
• Collaboration
• Browsing interfaces
• Mash-ups
Semantic Web
• Unified representations (RDF)
• Metadata and vocabularies (SIOC, FOAF)
• Ontology languages (OWL)
• Unified queries (SPARQL)

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Benefits of adding semantics to existing data
Web
of
data
Connect data in a
more meaningful way
Perform more specific
queries
Linked data
Related data

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Emergence of the « Metaweb »

Contact information:
anamaria.roxin@gmail.com | 0033.6.68.79.51.54

| 4546
Example – DBpedia Relation Finder
http://www.visualdataweb.org/relfinder/relfinder.php

| 45
Semantic Learning Content Management System (SLCMS)
Noyau Sémantique
Règles
Logique
Requête
Raisonneur
Modules Sémantiques
Productivité
Collaboration
Présentation course
Contrôle des connaissances
Communication
Administration
Noyau
Sémantique
Ressources LOM-RDF
LDAP Sémantique
Agenda
Sémantique
Marque-page
Sémantique
Forum Sémantique
Wiki Sémantique
Blog Sémantique
Concepts
Réponse
RDF
RDF
RDFS RDF
des concepts _
Logiques Règles

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Les ontologies Quiz et LMD
Formation Semester Year
Mention
Learning Path Domain
Group
SectionUnit
Question
StudentCourse
Specialisation
Variant
Quiz Author
Pending Quiz
Configuration Competence
hasSemester
hasFormation
hasSemester
hasFormation
hasMention
hasMention
hasDomainhasSpecialisation
hasSpecialisation
hasUnit
hasGroup
hasCourse
hasQuiz
hasCourse
hasQuiz
hasPendingQuiz
hasQuiz
hasQuestion
hasVariant hasConfiguration hasCompetence

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L’architecture d’application Quiz sémantique
l‘Enseignant Administrateur Étudiant
Couche données
Couche logique
Couche présentation
Adobe Flex
Affichage
Gestionnaire d'événement Flex
QuestionQuestion ……
CourseCourseQuizQuiz
Flex Data Services
QuestionQuestion ……
CourseCourseQuizQuizGestionnaire d'événement Java
Constructeur RDFConstructeur RDF Constructeur SPARQLConstructeur SPARQL J2EE
Stockage de donnéesMySQL
Numériques
Ressources
Numériques
Protocole RTMP
Connecteurs de données

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Interface application Quiz sémantique

Semantic Web applications for mobility and social interaction

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