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Retos Investigación Web Semántica

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  • 1. Retos de investigación para la WebSemánticas Asunción Gómez Pérez asun@fi.upm.es ©Asunción Gómez-Pérez -1
  • 2. Idioma(s) de la charla ©Asunción Gómez-Pérez -2
  • 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
  • 4. Web n+1: Roadmap ©Asunción Gómez-Pérez -4
  • 5. The current Web is multilingual ‫ر‬ ‫ا‬ ‫ى‬ ‫:ا‬ ‫ا‬ ‫ـ ز‬ ‫ن‬ :‫ّ ن‬ ‫ا‬ Japonés $74.95 : ّ ‫ا‬ Árabe ‫:ا ب‬ ‫ا‬ ‫ر‬ ‫ى ا‬ ‫< ا‬b>: ‫/<ا‬b><BR> ‫ـ ز‬ ‫ن‬ <b>:‫/<ا ّ ن‬b><BR> $74.95 <b>: ّ ‫/<ا‬b><BR> ‫< 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
  • 6. Information a machine can see… … ©Asunción Gómez-Pérez -6
  • 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
  • 11. Web n+1: Roadmap ©Asunción Gómez-Pérez - 11
  • 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
  • 15. Web n+1: Roadmap ©Asunción Gómez-Pérez - 15
  • 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
  • 21. The Web ©Asunción Gómez-Pérez - 21
  • 22. Semantic Webs ©Asunción Gómez-Pérez - 22
  • 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
  • 24. Corporative Semantics ©Asunción Gómez-Pérez - 24
  • 25. Corporative Semantics ©Asunción Gómez-Pérez - 25
  • 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
  • 33. Linked Data ©Asunción Gómez-Pérez - 33
  • 34. Datos abiertos y enlazados en el sector público ©Asunción Gómez-Pérez - 34
  • 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
  • 41. Anotar las fuentes de datos DMOP ROP Product file ©Asunción Gómez-Pérez - 41
  • 42. Detección del fraude en seguros del coche ©Asunción Gómez-Pérez - 42
  • 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