Semantic Web, an introduction
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  • 07/04/10 © 2005 - Della Valle - CEFRIEL

Semantic Web, an introduction Semantic Web, an introduction Presentation Transcript

  • Semantic Web An Introduction
    • Emanuele Della Valle
    • [email_address]
    • http://emanueledellavalle.org
  • Share, Remix, Reuse — Legally
    • This work is licensed under the Creative Commons Attribution 3.0 Unported License.
    • Your are free:
      • to Share — to copy, distribute and transmit the work
      • to Remix — to adapt the work
    • Under the following conditions
      • Attribution — You must attribute the work by inserting
        • “ © applied-semantic-web.org” at the end of each reused slide
        • a credits slide stating “These slides are partially based on “Semantic Web An Introduction” by Emanuele Della Valle http://applied-semantic-web.org/slides/2010/03/01_intro.ppt
    • To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/
  • Agenda
    • Un modello per studiare l’innovazione
    • Dal Web delle origini al Semantic Web
    • Introduzione al Semantic Web
    • Applicazioni del Semantic Web
    • Conclusione
  • Innovazione
  • Innovazione oggi idea micro fenomeno macro fenomeno problemi innovare analizzare creare complessità = 6.000.000.000 persone
  • Innovazione: non tutto è controllabile idea micro fenomeno macro fenomeno problemi innovare analizzare creare complessità = magia
  • Innovazione: ruolo di scienza e ingegneria idea micro fenomeno macro fenomeno problemi innovare analizzare creare complessità = magia scienza ingegneria
  • Innovare … idea micro fenomeno innovare creare complessità
  • … non è mai solo una questione di tecnologia idea micro fenomeno innovare soluzione tecnica soluzione sociale creare complessità
  • Un modello per studiare l’innovazione oggi idea micro fenomeno macro fenomeno problemi analizzare creare complessità soluzione tecnica soluzione sociale innovare
  • Il Web delle origini 1988 (CERN)
  • Analizziamo il Web delle origini (1988-1998) idea micro fenomeno macro fenomeno problemi analizzare creare complessità soluzione tecnica soluzione sociale innovare Non riesco ad accedere all’informazione Ipertesti + Internet WWW URI HTTP HTML Condividere info e link a cose interessanti
  • Il Web delle origini (1990) [source: http://www.w3.org/DesignIssues/diagrams/history/proposal-fig1.gif ] [source: http://www.w3.org/DesignIssues/diagrams/history/Architecture_crop.png ]
  • Analizziamo il Web delle origini (1988-1998) idea micro fenomeno macro fenomeno problemi analizzare creare complessità soluzione tecnica soluzione sociale innovare Non riesco ad accedere all’informazione Ipertesti + Internet WWW URI HTTP HTML Esplosione del fenomeno Web Condividere info e link a cose interessanti
  • The Web today Let’s browse together 2009 Map http://www.zoomorama.com/01-2477f0e8b447bb6570493cdac464c41f
  • Analizziamo il Web delle origini (1988-1998) idea micro fenomeno macro fenomeno problemi analizzare creare complessità soluzione tecnica soluzione sociale innovare Non riesco ad accedere all’informazione Ipertesti + Internet WWW URI HTTP HTML Esplosione del fenomeno Web Come trovo le pagine? Come posso scrivere? Condividere info e link a cose interessanti
  • Come posso scrivere? … Web 2.0! (1998-2006) idea micro fenomeno macro fenomeno problemi analizzare creare complessità soluzione tecnica soluzione sociale innovare Come posso scrivere? wiki-wiki e Web-Log Web 2.0 wiki blog I fenomeni Wikipedia, blogosphere, … Come gestire tutta questa info? Condividere info e link a cose interessanti
  • Come trovo le pagine? … Google! (1998-oggi) idea micro fenomeno macro fenomeno problemi analizzare creare complessità soluzione tecnica soluzione sociale innovare Come trovo le pagine? Indici + eigenspace Google PageRank Il fenomeno Google Basta cercare, vogliamo trovare! Condividere info e link a cose interessanti
  • Introduction Computer should understand more Large number of integrations - ad hoc - pair-wise Too much information to browse, need for searching and mashing up automatically Each site is “understandable” for us Computers don’t “understand” much ? Millions of Applications Search & Mash-up Engine 010 0 1 1 0 0 1101 10100 10 0010 01 101 101 01 110 1 10 1 10 0 1 1 0 1 0 1 0 0 1 1 0 1 1 1 10 0 1 101 0 1
  • Introduction What does “understand” mean?
    • What we say to Web agents
      • &quot; For more information visit <a href=“http://www.ex.org”> my company </a> Web site. . .”
    • What they “hear”
      • &quot; blah blah blah blah blah <a href=“http://www.ex.org”> blah blah blah </a> blah blah. . .”
      • Jet this is enought to train them to achive tasks for us
    [ source http://www.thefarside.com/ ]
  • Introduction What does Google “understand”?
    • Understanding that
      • [page1] links [page2]  page2 is interesting
    • Google is able to rank results!
      • “ The heart of our software is PageRank™, a system for ranking web pages […] (that) relies on the uniquely democratic nature of the web by using its vast link structure as an indicator of an individual page's value .”
      • http://www.google.com/technology/
  • Introduction Two ways for computer to “understand”
    • Smarter machines
      • Such as
        • Natural Langue processing (NLP)
        • Audio Processing
        • Image Processing (IP)
        • Video Processing
        • … many many more
      • They all work fine alone, the problem is combining them
        • E.g., NLP meets IP
          • NLP: What does your eye see?
          • IP: I see a sea
          • NLP: You see a “c”?
          • IP: Yes, what else could it be?
      • Not the Semantic Web approach
    • Smarter Data
      • Make data easier for machines to publish, share, find and understand
        • E.g. http://wordnet.rkbexplorer.com/description/word-sea vs. http://wordnet.rkbexplorer.com/description/word-c
      • The Semantic Web approach
    Some NLP Related Entertainment http://www.cl.cam.ac.uk/Research/ NL/amusement.html
  • Introduction The Semantic Web 1/4
    • “ The Semantic Web is not a separate Web, but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation.”
    • “ The Semantic Web”, Scientific American Magazine, Maggio 2001 http://www.sciam.com/article.cfm?articleID=00048144-10D2-1C70-84A9809EC588EF21
    • Key concepts
      • an extension of the current Web
      • in which information is given well-defined meaning
      • better enabling computers and people to work in cooperation.
        • Both for computers and people
  • Introduction The Semantic Web 2/4
    • “ The Semantic Web is not a separate Web, but an extension of the current one […] ”
    Web 1.0 The Web Today
  • Introduction The Semantic Web 3/4
    • “ The Semantic Web […] , in which information is given well-defined meaning […]”
    Human understandable but “only” machine-readable Human and machine “ understandable ” ? Web 1.0 Semantic Web
  • Introduction The Semantic Web 4/4 Semantic Web Fewer Integration - standard - multi-lateral […] better enabling computers and people to work in cooperation. Even More Applications Easier to understand for people More “understandable” for computers Semantic Mash-ups & Search
  • Introduction Semantic Web “layer cake” Standardized Under Investigation Already Possible [ source http://www.w3.org/2007/03/layerCake.png ]
  • Introduction The “lower” layers are already useful Standardized Under Investigation Already Possible [ source http://www.w3.org/2007/03/layerCake.png ]
  • Introduction Architectural view of the lower layers [source http://www.w3.org/DesignIssues/diagrams/sw-double-bus.png ]
  • Introduction What’s an ontology? Standardized Under Investigation Already Possible [ source http://www.w3.org/2007/03/layerCake.png ]
  • Introduction Ontology definition Formal, explicit specification of a shared conceptualization [Studer(98)] Machine readable Several people agrees that such conceptual model is adequate to describe such aspects of the reality A conceptual model of some aspects of the reality It makes domain assumption explicit
  • Introduction Esempio di Ontologia
    • Concetti e relazioni primitivi
      • essere umano
      • maschio
      • femmina
      • ha figlio
    • Concetti e relazioni derivate
      • un uomo è un essere umano ed è un maschio
      • una donna è un essere umano ed è una femmina
      • una madre è una donna che ha almeno un figlio
      • una padre è un uomo che ha almeno un figlio
      • un genitore è o un padre o una madre
      • un nonno è un uomo che ha almeno un figlio che è un genitore
      • “ essere figlio di ” è la relazione inversa a “avere un figlio”
    • Fatti asseriti
      • Antonio , Lorenzo e Carlo sono uomini
      • Rosanna è una donna
      • Antonio ha figlio Lorenzo
      • Rosanna ha figlio Carlo
      • Carlo è figlio di Lorenzo
      • Una macchina in grado di “capire” un linguaggio ontologico “sa inferire”
      • Concetti: un nonno è un genitore
      • Fatti: Antonio è un nonno, Lorenzo è un padre, Rosanna è una madre
  • Introduction How explicit shall the specification be ? “ A little semantics , goes a long way” [James Hendler, 2001] “ A Little Semantic Web Goes a Long Way in Biology” [ Wolstencroft et al., 2005]
  • Introduction Light Example: Publishing Semantic Mark-up
    • A firefox plug-in such as Operator can extract those semantic mark-up from the page and offers actions such as “add the event to your calendar” https://addons.mozilla.org/en-US/firefox/addon/4106
    <div id=&quot;event-info-where&quot; class=&quot;info-wh-info vcard &quot;> <h2><a rel=&quot;bookmark&quot; class=&quot;fn org location&quot; href=&quot;/venues/V0-001-000693919-2&quot;> Circus Krone Munich </a></h2> <div class=&quot;adr&quot; > <span class=&quot;street-address&quot; > 1 </span><br> <span class=&quot;locality&quot; > Munich </span>, <span class=&quot;region&quot; > Bayern </span> <br> <span class=&quot;country-name&quot; > Germany </span>
  • Introduction Example: Automatic Semantic mark-up Normal page Page Augmented with Gnosis Firefox Extension Download Gnosis at https://addons.mozilla.org/de/firefox/addon/3999
  • Introduction Example: BBC’s Artist as Linked Data
    • <?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot;?>
    • <rdf:RDF
    • xmlns:rdf = &quot;http://www.w3.org/1999/02/22-rdf-syntax-ns#&quot;
    • xmlns:rdfs = &quot;http://www.w3.org/2000/01/rdf-schema#&quot;
    • xmlns:owl = &quot;http://www.w3.org/2002/07/owl#&quot;
    • xmlns:dc = &quot;http://purl.org/dc/elements/1.1/&quot;
    • xmlns:foaf = &quot;http://xmlns.com/foaf/0.1/&quot;
    • xmlns:rel = &quot;http://www.perceive.net/schemas/relationship/&quot;
    • xmlns:mo = &quot;http://purl.org/ontology/mo/&quot;
    • xmlns:rev = &quot;http://purl.org/stuff/rev#&quot; >
    • <rdf:Description rdf:about=&quot;/music/artists/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432.rdf&quot;>
    • <rdfs:label>Description of the artist U2</rdfs:label>
    • <foaf:primaryTopic rdf:resource=&quot;/music/artists/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432#artist&quot;/>
    • </rdf:Description>
    • <mo:MusicGroup rdf:about=&quot;/music/artists/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432#artist&quot;>
    • <foaf:name>U2</foaf:name>
    • <owl:sameAs rdf:resource=&quot;http://dbpedia.org/resource/U2&quot; />
    • <foaf:page rdf:resource=&quot;/music/artists/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432.html&quot; />
    • <mo:musicbrainz rdf:resource=&quot;http://musicbrainz.org/artist/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432.html&quot; />
    • <mo:homepage rdf:resource=&quot;http://www.u2.com/&quot; />
    • <mo:fanpage rdf:resource=&quot;http://www.atu2.com/&quot; />
    • <mo:wikipedia rdf:resource=&quot;http://en.wikipedia.org/wiki/U2&quot; />
    • <mo:imdb rdf:resource=&quot;http://www.imdb.com/name/nm1277752/&quot; />
    • <mo:myspace rdf:resource=&quot;http://www.myspace.com/u2&quot; />
    • <mo:member rdf:resource=&quot;/music/artists/7f347782-eb14-40c3-98e2-17b6e1bfe56c#artist&quot; />
    • <mo:member rdf:resource=&quot;/music/artists/1f52af22-0207-40ac-9a15-e5052bb670c2#artist&quot; />
    HTML: http://www.bbc.co.uk/music/artists/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432 RDF : http://www.bbc.co.uk/music/artists/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432.rdf
  • Introduction Complex Example: Linking Open Data Project
    • Goal: extend the Web with data commons by publishing open data sets using Semantic Web techs
    Visit http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData !
    • Project Chartres
    • RDFizers and ConverterToRdf
    • Publishing Tools
    • Semantic Web Browsers and Client Libraries
    • Semantic Web Search Engines
    • Applications
    • […]
  • Introduction New York Times Thesaurus
    • For more than 150 years, The New York Times has meticulously indexed its archives. Through this process, we have developed an enormous collection of subject headings […].
    • Unfortunately, our list of subject headings is an island. For example, even though we can show you every article written about “Colbert, Stephen,” our databases can’t tell you that he was born on May 13, 1964, or that he lost the 2008 Grammy for best spoken word album to Al Gore . To do this we would need to map our subject headings onto other Web databases such as Freebase and DBPedia .
    • So that’s exactly what we did. Over the last several months we have manually mapped more than 5,000 person name subject headings onto Freebase and DBPedia. […]
    • So now you can visit http://data.nytimes.com/N66220017142656459133 and see that our “Colbert, Stephen” is equivalent to DBPedia’s http://dbpedia.org/resource/Stephen_Colbert and Freebase’s http://rdf.freebase.com/rdf/en.stephen_colbert . Even more importantly, your computer can visit http://data.nytimes.com/N66220017142656459133.rdf and get all of this information in a computer-readable (RDF) document.
    • October 29, 2009, 4:07 pm First 5,000 Tags Released to the Linked Data Cloud By EVAN SANDHAUS AND ROB LARSON
  • Introduction Browsing the LOD with http://sig.ma/ Try it! http://sig.ma/search?q=Propranolol
  • Introduction The new era of Semantic Apps
    • One of the highlights of October's Web 2.0 Summit in San Francisco was the emergence of 'Semantic Apps' as a force.
    • The purpose of this post is to highlight 10 Semantic Apps. […] It reflects the nascent status of this sector, even though people like Hillis and Spivack have been working on their apps for years now.
    • Read out more at http://www.readwriteweb.com/archives/10_semantic_apps_to_watch.php
  • Analizziamo il Semantic Web idea micro fenomeno macro fenomeno problemi analizzare creare complessità soluzione tecnica soluzione sociale innovare Come gestire i dati sul Web? KR + Web Semantic Web RDF SPARQL SKOS OWL RIF LOD ? Condividere info e link a cose interessanti
  • Credits
    • Introduction and RDF slides are partially based on “Fundamentals of the Semantic Web” by David Booth http://www.w3.org/2002/Talks/0813-semweb-dbooth/
  • Semantic Web An Introduction
    • Emanuele Della Valle
    • [email_address]
    • http://emanueledellavalle.org