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Retos Investigación Web Semántica
- 3. Table of Content
1. 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
©Asunción Gómez-Pérez -3
- 5. The current Web is multilingual
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Japonés
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Árabe
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ر ى ا < اb>: /<اb><BR>
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< اb>:/<ا بb><BR>
Skjøte: Ontological Ingeniørarbeid Title: Ontological Engineering
Forfatter: Overtakelse Gómez-Pérez... Authors: Asunción Gómez-Pérez...
Pris: 74.95€ Price: $74.95
Noruego
Inglés
Produkt: Bok Product: Book
<b>Skjøte:</b> Ontological Ingeniørarbeid<BR> <b>Title:</b> Ontological Engineering <BR>
<b>Forfatter:</b> Overtakelse Gómez-Pérez... <BR> <b>Authors:</b> Asunción Gómez-Pérez... <BR>
<b>Pris:</b> 74.95€<BR> <b>Price:</b> $74.95<BR>
<b>Produkt:</b> Bok<BR> <b>Product:</b> Book<BR>
.- HTML is useful for browsing the information
.- Content is language-dependent
.- High cost for keeping the information up-to-date
©Asunción Gómez-Pérez -5
- 7. XML allows the creation of metada with
“meaning”
ر ا ى :ا ا Title: Ontological Engineering
ـ ز ن :ّ ن ا Authors: Asunción Gómez-Pérez...
$74.95 : ّ ا Price: $74.95
Árabe
Inglés
:ا ب ا Product: Book
< ر >ا ى ا >ا /<ا <Title>Ontological Engineering</Title>
<ـ ز >ا ّ ن ن </>ا ّ ن <Author>Asunción Gómez-Pérez...</Author>
< ّ >ا ّ /<59.47$>ا <Price>$74.95</Price>
<>ا ب >ا ب/<ا <Product>Book</Product>
¿What do the tags mean for the machine?
©Asunción Gómez-Pérez -7
- 8. But What About…?
<conf>
</conf>
<date> </date>
<place>
</place>
<introduction>
</introduction>
<speaker>
<bio>
</bio>
</speaker>
<speaker>
<bio>
</bio>
</speaker>
<registration>
©Asunción Gómez-Pérez <registration> -8
- 9. Exceso de información
.- Encontrar
.- Comprender
Extraer
.- Comparar
.- Agregar
….
©Asunción Gómez-Pérez -9
- 10. 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 the
machine-readable information space gave an accurate
representation of the state of people's thoughts,
interactions, and work patterns, then machine analysis
could become a very powerful management tool, seeing
patterns in our work and facilitating our working together
through the typical problems which beset the management
of large organizations.”
[Berners-Lee 1996]
©Asunción Gómez-Pérez - 10
- 12. .- Find .- Encontrar
Information
.- Understand
.- Comprender
Extract
Extraer
.- Compare
.- Comparar
.- Agregate
.- Agregar
.- Look for consistency
.- Publicar
.- Contextualizar
.- Publish
.- Contextualize
©Asunción Gómez-Pérez - 12
- 13. But What About…?
<conf>
</conf>
<date> </date>
<place>
</place>
<introduction>
</introduction>
<speaker>
<bio>
</bio>
</speaker>
<speaker>
<bio>
</bio>
</speaker>
<registration>
©Asunción Gómez-Pérez <registration> - 13
- 14. 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 ....”
©Asunción Gómez-Pérez - 14
- 16. Table of Content
1. Web n+1: Roadmap
2. The semantic Webs and Corporative Semantics
– Ontologies
– Metadata
3. Example of pure Semantic Web applications
– Corporate Semantic Web: ODESeW
– Semantic Access to DB: FAO
– Semantic Search: SEEMP
4. Example of Web 3.0 applications
– Decision support systems: Satellite missions, car insurance
– Geobuddies
– SemsorGrid4Env
©Asunción Gómez-Pérez - 16
- 17. What is the Semantic Web?
“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
applications.”
Hendler, J., Berners-Lee, T., and Miller, E.
Integrating Applications on the Semantic Web, 2002,
http://www.w3.org/2002/07/swint.html
©Asunción Gómez-Pérez - 17
- 18. La pila de la Web Semántica
©Asunción Gómez-Pérez - 18
- 19. Ontology
rdfs:Class rdf:ID="Travel">
<rdfs:comment>A journey from place to
place</rdfs:comment>
</rdfs:Class>
<rdf:Property rdf:ID="arrivalDate">
RDFS <rdfs:domain rdf:resource="#Travel"/>
rdfs:Literal rdfs:Class <rdfs:range rdf:resource="&xsd;date"/>
</rdf:Property>
<rdf:Property rdf:ID="departureDate">
<rdfs:domain rdf:resource="#Travel"/>
rdf:Type
<rdfs:range rdf:resource="&xsd;date"/>
rdfs:range </rdf:Property>
Travel rdfs:domain arrivalDate
rdfs:domain rdfs:domai
n
rdfs:domai departureDate
n
Company-name singleFare rdfs:range
rdfs:range
rdfs:range
rdf:Type
units:currencyQuantity xsd:Date
RDF
rdf:Type
rdf:Property
rdf:Type rdf:Type
©Asunción Gómez-Pérez - 19
- 20. Metadata
Iberia
Company-name
IB-4321
arrivalDate
singleFare
departureDate
10/11/2005
<Travel rdf:ID=“IB-4321"> 500 euros
<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>
©Asunción Gómez-Pérez - 20
- 23. Alignments Alignments
Knowledge
Ontologies Metadata
Reasoning
Metadata <RDF <RDF <RDF
triple> The Semantic triple> triple>
<RDF web <RDF <RDF
triple> triple> triple>
<RDF <RDF <RDF
triple> triple> triple>
<RDF <RDF <RDF
triple> triple> triple>
<RDF <RDF <RDF
triple> triple> triple>
The web <RDF <RDF <RDF
triple> triple> Information
triple>
<RDF <RDF <RDF
triple> triple> triple>
©Asunción Gómez-Pérez - 23
- 26. Alignments
Alignments
Ontologies
Knowledge
Alignments Metadata <RDF <RDF <RDF
Onto. - Schema triple> triple> triple> Metadata
Data Sources Reasoning <RDF <RDF <RDF
triple> triple> triple>
<RDF <RDF <RDF
triple> triple> triple>
<RDF <RDF <RDF
triple> triple> triple>
<RDF <RDF <RDF
triple> triple> triple>
Resources <RDF <RDF <RDF
triple> triple> triple>
<RDF <RDF <RDF
triple> triple> triple>
Information
©Asunción Gómez-Pérez - 26
- 27. Table of Content
1. 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
©Asunción Gómez-Pérez - 27
- 28. Acceso semántico a bases de datos
Pregunta: Nombre de
Universidad
los profesores de la
Profesor
universidad UPM
Doctorando
* Un profesor es una persona Ontología
cuyo puesto es “docente”
* Una universidad es una
organización de tipo “3”
? Procesador
Procesado de la consulta de
acuerdo a la descripción
formal de correspondencia
Organización
Personal 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
BDR Modelo estén relacionados con al menos un registro de
Relacional la tabla Organización con el valor “3” en la
columna tipo y “UPM” en la columna nombre.
©Asunción Gómez-Pérez - 28
- 29. Escenario en la FAO
Las ontologías se utilizan en
aplicaciones orientadas a determinar
el stock de los peces en el
Mediterráneo
©Asunción Gómez-Pérez - 29
Slide 29
- 30. Mappings entre Ontologías y BD
Land Fishing Biological Fisheries Vessel types Gear
areas areas entities commodities and size types
R2O R2O R2O R2O R2O R2O
Document Document Document Document Document Document
FAO
FIGIS DB
©Asunción Gómez-Pérez
http://www.fao.org/aims/aos/fi/ - 30
- 31. 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)
©Asunción Gómez-Pérez - 31
31
- 32. 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
©Asunción Gómez-Pérez - 32
- 35. 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/
Medios de comunicación
BBC
New York times
I+D+i
Cordis
Bibliotecas
©Asunción Gómez-Pérez - 35
- 36. IGN se ha incorporado a linked data
IGN
RTMS DB
R2O
ODEMapster
IGN
Virtuoso Server
©Asunción Gómez-Pérez - 36
- 37. The Goal: Helping Job Seekers on their way
Local
o
EURES Matching
p ESES n
(Int) algorithm
ES ES
m Local
Matching
q ES algorithm
Cand. ES Cand.
Cand.
Vacan. l
Catalonia
r Vacan.
Vacan.
Cand.
Cand. ESES
(Es)
ES
Cand.
Cand.
European Vacan.
Vacan.
i
Lombard Employment ES
ES (It) Mediators
Vacan.
Vacan.
Marketplace Cand.
Cand.
a h
ES ES
LEGENDA Cand.
Cand.
Vacan.
Vacan.
Vacan.
Vacan. Local
Matching
Requester ES b Private algorithm
g
ES ES ES
(Int)
Responding ES Local
Matching
ES not involved c f
algorithm
Cand.
Cand. ES ES
d e
Wallonia
Job Seeker’s Candidacy ESES
(Be)
ES
Vacan.
Vacan.
Employer Job Vacancy
©Asunción Gómez-Pérez - 37
- 38. Centralized network of ontologies Federated network of ontologies
Ms Ms
Ms Ms
Ms Ms
Ms
Ms Ms
Ms
Ms
Ms
Ms
Ms
Ms
1. Build a reference ontology for the domain
1. Build a reference ontology
2. Build local ontologies
2. Build mappings between the 3. Build mappings between the core and local ontologies
reference ontology and the data sources 4. Build mappings between the local ontologies and the data
sources
©Asunción Gómez-Pérez - 38
- 39. Table of Content
1. 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
©Asunción Gómez-Pérez - 39
- 40. Procesamiento de información de satélites
• 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:
• 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 Analysis needs to be carried out
– Each product file corresponds with a planning activity on the existence, contents and
©Asunción Gómez-Pérez - 40 correlation of these files
- 43. Geobuddies
Semantic & Collaborative annotation using mobile devices in
the “Camino de Santiago”
– Ontologies
– Web 3.0
• Semantic Web
• Web 2.0
– Mobile devices
– Data Grid
– Geographic information
©Asunción Gómez-Pérez - 43
- 44. 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
• People want to
– Find interesting locations
– Find community services
– Provide information
©Asunción Gómez-Pérez - 44
- 45. Las anotaciones
se guardan y los
objetos se consolidan
Servidor de
con bases de datos geográficas anotaciones
y anotaciones existentes
El usuario ve un punto de walk sun
interés y envía una foto tired
con sus correspondientes
anotaciones cathedral
huge
peaceful
BBDD geográficas
Motor de recomendaciones
(sólo geográfico)
El usuario quiere saber
qué puntos de interés le
pueden interesar en la zona
en la que se encuentra Servidor de
anotaciones
Motor de recomendaciones (todos los usuarios)
(geográfico + tags + ontologías)
mezcla
Servidor de
ontologías
Camino Personalizado
©Asunción Gómez-Pérez - 45
- 46. Transferencia de la
comunidad generada
Generated social communities are transferred into social community sites (facebook, Google social API)
Reuse of other off-the-shelf services
Sustainability of people links found during the walk
Ease of implementation
©Asunción Gómez-Pérez - 46
- 47. 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 …
data integration at large scale is one of the main challenge
and …
everything combined with
1. Social communities
2. Mobile devices
3. Ubiquitous computing
©Asunción Gómez-Pérez - 47
- 48. Tendencias en el Desarrollo de
Aplicaciones Semánticas
Asunción Gómez Pérez
asun@fi.upm.es
©Asunción Gómez-Pérez - 48
