Retos Investigación Web Semántica

Retos de investigaciónpara la WebSemánticas

©Asunción Gómez-Pérez - 1

Asunción Gómez Pérez

[email protected]

Idioma(s) de la charla


Table of Content1. Web n+1: Roadmap

2. The semantic Webs and Corporative Semantics

– Ontologies

– Metadata

3. Example of pure Semantic Web applications

– Semantic Access to DB: FAO

– Linked data

– Semantic Search: SEEMP



4. Example of Web 3.0 applications – Decision support systems: Satellite missions, car insurance– Geobuddies

Web n+1: Roadmap


The current Web is multilingual

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Árabe

Title: Ontological EngineeringSkjøte: Ontological Ingeniørarbeid

Japonés


Title: Ontological Engineering 

Authors: Asunción Gómez-Pérez... 

Price: $74.95 

Product: Book 

Title: Ontological EngineeringAuthors:Asunción Gómez-Pérez...Price: $74.95Product: Book

Inglés

Skjøte: Ontological Ingeniørarbeid 

Forfatter: Overtakelse Gómez-Pérez... 

Pris: 74.95€ 

Produkt: Bok 

Skjøte: Ontological Ingeniørarbeid Forfatter: Overtakelse Gómez-Pérez...Pris: 74.95€Produkt: Bok

Noruego

.- HTML is useful for browsing the information

.- Content is language-dependent

.- High cost for keeping the information up-to-date

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Information a machine can see…


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XML allows the creation of metada with “meaning”

<Title>Ontological Engineering</Title>

<Author>Asunción Gómez-Pérez...</Author>

<Price>$74.95</Price>

Title: Ontological EngineeringAuthors:Asunción Gómez-Pérez...Price: $74.95Product: Book

Inglés

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Árabe


¿What do the tags mean for the machine?

<Price>$74.95</Price>

<Product>Book</Product>

<* 2ّ�<ا�2ّ */>74.95$<ا<ا�;�:ب/>ا�7&�8 <ا�;�:ب>

But What About…?

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�$�� ! ��%� ��$�� ! ��%� ��$�� ! ��%� ��$�� ! ��%� ��</introduction><speaker>�� !�� !�� !�� !��

<bio>�� ! �� % �� ! �� % �� ! �� % �� ! �� % �� </bio></speaker><speaker>�� !�� !�� !�� !��

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Exceso de información


.- Encontrar.- Comprender

Extraer.- Comparar.- Agregar

….

What was the Web intended to be?

“... a goal of the Web was that, if the interaction between person and hypertext could be so intuitive that themachine-readable information space gave an accurate representation of the state of people's thoughts, interactions, and work patterns, then machine analysis


interactions, and work patterns, then machine analysiscould become a very powerful management tool, seeing patterns in our work and facilitating our working togetherthrough the typical problems which beset the management of large organizations.”

[Berners-Lee 1996]

Web n+1: Roadmap



.- Find Information.- Understand

Extract.- Compare.- Agregate

.- Look for consistency.- Publish

.- Contextualize

.- Encontrar.- Comprender

Extraer.- Comparar.- Agregar.- Publicar

.- Contextualizar

But What About…?

<conf>�� </conf><date>�� </date><place>�� </place><introduction>"�#�!�� "�#�!�� "�#�!�� "�#�!�� ( �� ( �� ( �� ( �� )�� $ �� )�� $ �� )�� $ �� )�� $ �� $ �% �� $ �% �� $ �% �� $ �% �� %� ��* ��! $ �!��#��! �� %� ��* ��! $ �!��#��! �� %� ��* ��! $ �!��#��! �� %� ��* ��! $ �!��#��! �� +�� +�� +�� +�$�� ! ��%� ��$�� ! ��%� ��$�� ! ��%� ��$�� ! ��%� ��</introduction>


�$�� ! ��%� ��$�� ! ��%� ��$�� ! ��%� ��$�� ! ��%� ��</introduction><speaker>�� !�� !�� !�� !��

<bio>�� ! �� % �� ! �� % �� ! �� % �� ! �� % �� </bio></speaker><speaker>�� !�� !�� !�� !��

<bio>�� ! �� % �� ! �� % �� ! �� % �� ! �� % �� </bio></speaker><registration>"�#�!�� $� ��$��! ��# % ��"�#�!�� $� ��$��! ��# % ��"�#�!�� $� ��$��! ��# % ��"�#�!�� $� ��$��! ��# % ��!� �� !� �� !� �� !� �� % �� #� �� #�� # ��#� % �� #� �� #�� # ��#� % �� #� �� #�� # ��#� % �� #� �� #�� # ��#� �� &�$�� &�$�� &�$�� &�$�� '�� !� � �� '�� !� � �� '�� !� � �� '�� !� � �� !�#�$� �� !��'� �� !�#�$� �� !��'� �� !�#�$� �� !��'� �� !�#�$� �� !��'� �� #�� !��!� �� #�� !��!� �� #�� !��!� �� #�� !��!� �� '�� '�� '�� '�� <registration>

Y la frase de Tim Berneres-Lee [1996] sigue siendo válida para la Web 2.0

“... the machine-readable information space ...

… machine analysis could become a very


powerful management tool, …

… facilitating our working together ....”

Web n+1: Roadmap




– Ontologies

– Metadata


– Corporate Semantic Web: ODESeW





4. Example of Web 3.0 applications – Decision support systems: Satellite missions, car insurance– Geobuddies– SemsorGrid4Env

“The Semantic Web is an extension of the current Web in which

information is given well-defined meaning, better enabling computers

and people to work in cooperation. It is based on the idea of having data

on the Web defined and linked such that it can be used for more effective

discovery, automation, integration, and reuse across various

What is the Semantic Web?


discovery, automation, integration, and reuse across various

applications.”

Hendler, J., Berners-Lee, T., and Miller, E.

Integrating Applications on the Semantic Web, 2002,

http://www.w3.org/2002/07/swint.html

La pila de la Web Semántica


rdfs:Literal rdfs:Class

rdfs:range

rdf:Type

RDFS

Ontologyrdfs:Class rdf:ID="Travel">

<rdfs:comment>A journey from place to

place</rdfs:comment>

</rdfs:Class>

<rdf:Property rdf:ID="arrivalDate">

<rdfs:domain rdf:resource="#Travel"/>

<rdfs:range rdf:resource="&xsd;date"/>

</rdf:Property>

<rdf:Property rdf:ID="departureDate">

<rdfs:domain rdf:resource="#Travel"/>

<rdfs:range rdf:resource="&xsd;date"/>

</rdf:Property>


Travel

Company-name singleFare

units:currencyQuantity

rdfs:range

rdfs:domain

rdfs:domain

departureDate

rdfs:domain

xsd:Date

rdfs:range

arrivalDate

rdfs:range

rdfs:domain

rdf:Propertyrdf:Typerdf:Type

rdf:Type

rdf:Type

RDF

IB-4321

Iberia

Company-name

singleFaredepartureDate

arrivalDate

Metadata


500 euros

departureDate

10/11/2005<Travel rdf:ID=“IB-4321">

<Company-name>Iberia</Company-name>

<singleFare>500 Euros</singleFare>

<departureDate rdf:datatype="&xsd;date">

2005-11-10

</departureDate>

<arrivalDate rdf:datatype="&xsd;date">

2005-11-10

</arrivalDate>

<arrivalPlace rdf:resource="#Paris"/>

</Travel>

The Web


Semantic Webs


Metadata <RDF triple><RDF triple>

<RDF triple><RDF triple>


AlignmentsAlignments AlignmentsAlignments

Ontologies

KnowledgeMetadataReasoning

The Semanticweb


The web

triple><RDF triple><RDF triple><RDF triple><RDF triple><RDF triple>



Information

Corporative Semantics


AlignmentsAlignments

AlignmentsAlignments

Metadata

<RDF triple><RDF triple><RDF



AlignmentsAlignmentsOnto. Onto. -- SchemaSchemaData SourcesData Sources

Ontologies

KnowledgeMetadataReasoning


Resources

<RDF triple><RDF triple><RDF triple><RDF triple><RDF triple>



Information



– Ontologies

– Metadata



– Linked data





Acceso semántico a bases de datos

Pregunta: Nombre de

los profesores de la

universidad UPM

* Un profesor es una personacuyo puesto es “docente”

* Una universidad es una organización de tipo “3”

?

Ontología

Profesor

Doctorando

Universidad

Procesador


BDR ModeloRelacional

Personal

Organización

Consulta: valores de la columna nombre de los

registros de la tabla Personal para los que el

valor de la columna puesto is “docente” que

estén relacionados con al menos un registro de

la tabla Organización con el valor “3” en la

columna tipo y “UPM” en la columna nombre.

? Procesado de la consulta de acuerdo a la descripción formal de correspondencia

Procesador

Escenario en la FAOEscenario en la FAO


Las ontologías se utilizan en aplicaciones orientadas a determinar el stock de los peces en el Mediterráneo

Slide 29

Mappings entre Ontologías y BD

Land

areas

Fishing

areas

Biological

entities

Fisheries

commodities

Vessel types

and size

Gear

types

R O R O R O R O R O R O


R2O

Document

R2O

Document

R2O

Document

R2O

Document

R2O

Document

R2O

Document

FAOFIGIS DB

http://www.fao.org/aims/aos/fi/

Mapping Design

• 3 Mapping Creation Steps– Load Ontology

– Load Database(s)

– Create mapping


� 2 Usage Modes– Online mode (run

time query execution)

– Offline mode (materialized RDF dump)

ODEMapster

• The ODEMapster processor generates RDF from relational instances based on the

mapping description expressed in the R2O document

– Batch process: DB records migrated to the ontology

– On demand: Querying the DB in terms of ontological terms


Linked Data


Datos abiertos y enlazados en el sector público


Iniciativas Datos Abiertos y Enlazados

Administraciones Públicas

Gobierno británico: http://data.gov.uk

Proyecto Aporta

Iniciativa Abre datos

Geográfica

Geolinked data: http://geo.linkeddata.es/


Geolinked data: http://geo.linkeddata.es/

Medios de comunicación

BBC

New York times

I+D+i

Cordis

Bibliotecas

IGN se ha incorporado a linked data

IGNRTMS DB

R2OODEMapster

IGN


Virtuoso Server

IGN

Lombard

qES

rES

pES

iES

nES

lES

oES

mES

The Goal: Helping Job Seekers on their way

EuropeanEuropean

EmploymentEmployment

LocalMatching algorithm

EURESES (Int)

LocalMatching algorithm

CataloniaES (Es)

CandCand..CandCand..




VacanVacan..VacanVacan..




gES

LombardES (It)

aES

cES

ES

eES

hES

fES

dES

bES

Requester ES

Responding ES

ES not involved

Job Seeker’s Candidacy

Employer Job Vacancy

LEGENDA

EmploymentEmployment

MediatorsMediators

MarketplaceMarketplace

LocalMatching algorithmPrivate

ES (Int)Local

Matching algorithm

WalloniaES (Be)






VacanVacan..VacanVacan..VacanVacan..VacanVacan..

Ms Ms

Ms

MsMs

Ms

Centralized network of ontologies Federated network of ontologies

Ms

Ms

Ms


Ms

Ms

MsMs

Ms

Ms

1. Build a reference ontology 1. Build a reference ontology for the domain

2. Build local ontologies

3. Build mappings between the core and local ontologies

4. Build mappings between the local ontologies and the datasources

MsMs

2. Build mappings between the reference ontology and the data sources



– Ontologies

– Metadata



– Linked data





• Geographically distributed organizations

• Organizations send plans to the Envisat

• Envisat has Instruments on board that take “pictures”

• Envisat sends back information to the Earth

USE CASE DIMENSION:

Procesamiento de información de satélites


• 1 planning file (DMOP) is generated per planning day– Parameters for instrument operation (taking

pictures)

– Parameters for the satellite general configuration.

– MacroCommands (MCMD’s): translation from planning

• For each DMOP file:– Hundreds of planning activities per instrument and

instrument mode

– Hundreds of Product files are generated per instrument and instrument mode

– Each product file corresponds with a planning activity

Analysis needs to be carried out on the existence, contents and

correlation of these files

Anotar las fuentes de datos

ROP

DMOP


Product file

Detección del fraude en seguros del coche


Geobuddies

Semantic & Collaborative annotation using mobile devices in

the “Camino de Santiago”– Ontologies

– Web 3.0

• Semantic Web


• Semantic Web

• Web 2.0

– Mobile devices

– Data Grid

– Geographic information

A pilgrim in St. James’ Way (Camino de Santiago)

• Diverse routes for pilgrims

• Self-emergent community of pilgrims– People that talk about their experiences during the way

– People that join together in the joy of walking

– Mobile users


– Mobile users

• People want to– Find interesting locations

– Find community services

– Provide information

Servidor de anotaciones

El usuario ve un punto de interés y envía una foto con sus correspondientes anotaciones

walk sun tired

cathedralhugepeaceful

Las anotacionesse guardan y losobjetos se consolidancon bases de datos geográficasy anotaciones existentes

BBDD geográficas

El usuario quiere saber

Motor de recomendaciones(sólo geográfico)


Motor de recomendaciones(geográfico + tags + ontologías)

Servidor de anotaciones

(todos los usuarios)

Servidor de ontologías

mezcla

El usuario quiere saberqué puntos de interés lepueden interesar en la zonaen la que se encuentra

Camino Personalizado

Transferencia de la comunidad generada


Generated social communities are transferred into social community sites (facebook, Google social API)Reuse of other off-the-shelf servicesSustainability of people links found during the walkEase of implementation

Conclusions

We are moving into a new generation of semantic applications• Open to web resources

• Open to semantic resources

• Open to web services

• Open to web data

• Open to the physical world and having an impact on it.

where …


where …

data integration at large scale is one of the main challenge

and …

everything combined with 1. Social communities

2. Mobile devices

3. Ubiquitous computing

Tendencias en el Desarrollo de Aplicaciones Semánticas


Asunción Gómez Pérez

[email protected]

Retos Investigación Web Semántica

Education

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