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Semantic Web, an introduction for bioscientists


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Semantic Web, an introduction for bioscientists

  1. 1. Semantic Web An Introduction <ul><li>Emanuele Della Valle </li></ul><ul><li>[email_address] </li></ul><ul><li> </li></ul>
  2. 2. Share, Remix, Reuse — Legally <ul><li>This work is licensed under the Creative Commons Attribution 3.0 Unported License. </li></ul><ul><li>Your are free: </li></ul><ul><ul><li>to Share — to copy, distribute and transmit the work </li></ul></ul><ul><ul><li>to Remix — to adapt the work </li></ul></ul><ul><li>Under the following conditions </li></ul><ul><ul><li>Attribution — You must attribute the work by inserting </li></ul></ul><ul><ul><ul><li>“ ©” at the end of each reused slide </li></ul></ul></ul><ul><ul><ul><li>a credits slide stating “These slides are partially based on “Semantic Web An Introduction” by Emanuele Della Valle </li></ul></ul></ul><ul><li>To view a copy of this license, visit </li></ul>
  3. 3. Agenda <ul><li>Dal Web delle origini al Semantic Web </li></ul><ul><li>Introduzione al Semantic Web </li></ul><ul><li>Applicazioni del Semantic Web </li></ul><ul><li>Conclusione </li></ul>
  4. 4. Il Web delle origini 1988 (CERN)
  5. 5. Il Web delle origini (1990) [source: ] [source: ]
  6. 6. The Web today Let’s browse together 2009 Map
  7. 7. 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
  8. 8. Introduction What does “understand” mean? <ul><li>What we say to Web agents </li></ul><ul><ul><li>&quot; For more information visit <a href=“”> my company </a> Web site. . .” </li></ul></ul><ul><li>What they “hear” </li></ul><ul><ul><li>&quot; blah blah blah blah blah <a href=“”> blah blah blah </a> blah blah. . .” </li></ul></ul><ul><ul><li>Jet this is enought to train them to achive tasks for us </li></ul></ul>[ source ]
  9. 9. Introduction What does Google “understand”? <ul><li>Understanding that </li></ul><ul><ul><li>[page1] links [page2]  page2 is interesting </li></ul></ul><ul><li>Google is able to rank results! </li></ul><ul><ul><li>“ 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 .” </li></ul></ul><ul><ul><li> </li></ul></ul>
  10. 10. Introduction Two ways for computer to “understand” <ul><li>Smarter machines </li></ul><ul><ul><li>Such as </li></ul></ul><ul><ul><ul><li>Natural Langue processing (NLP) </li></ul></ul></ul><ul><ul><ul><li>Audio Processing </li></ul></ul></ul><ul><ul><ul><li>Image Processing (IP) </li></ul></ul></ul><ul><ul><ul><li>Video Processing </li></ul></ul></ul><ul><ul><ul><li>… many many more </li></ul></ul></ul><ul><ul><li>They all work fine alone, the problem is combining them </li></ul></ul><ul><ul><ul><li>E.g., NLP meets IP </li></ul></ul></ul><ul><ul><ul><ul><li>NLP: What does your eye see? </li></ul></ul></ul></ul><ul><ul><ul><ul><li>IP: I see a sea </li></ul></ul></ul></ul><ul><ul><ul><ul><li>NLP: You see a “c”? </li></ul></ul></ul></ul><ul><ul><ul><ul><li>IP: Yes, what else could it be? </li></ul></ul></ul></ul><ul><ul><li>Not the Semantic Web approach </li></ul></ul><ul><li>Smarter Data </li></ul><ul><ul><li>Make data easier for machines to publish, share, find and understand </li></ul></ul><ul><ul><ul><li>E.g. vs. </li></ul></ul></ul><ul><ul><li>The Semantic Web approach </li></ul></ul>Some NLP Related Entertainment NL/amusement.html
  11. 11. Introduction The Semantic Web 1/4 <ul><li>“ 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.” </li></ul><ul><li>“ The Semantic Web”, Scientific American Magazine, Maggio 2001 </li></ul><ul><li>Key concepts </li></ul><ul><ul><li>an extension of the current Web </li></ul></ul><ul><ul><li>in which information is given well-defined meaning </li></ul></ul><ul><ul><li>better enabling computers and people to work in cooperation. </li></ul></ul><ul><ul><ul><li>Both for computers and people </li></ul></ul></ul>
  12. 12. Introduction The Semantic Web 2/4 <ul><li>“ The Semantic Web is not a separate Web, but an extension of the current one […] ” </li></ul>Web 1.0 The Web Today
  13. 13. Introduction The Semantic Web 3/4 <ul><li>“ The Semantic Web […] , in which information is given well-defined meaning […]” </li></ul>Human understandable but “only” machine-readable Human and machine “ understandable ” ? Web 1.0 Semantic Web
  14. 14. 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
  15. 15. Introduction Bio2RDF project -
  16. 16. Introduction Bio2RDF REST services <ul><li>Describe a resource by a dereferencable URI </li></ul><ul><ul><li> :id </li></ul></ul><ul><li>Global services over federated endpoints </li></ul><ul><ul><li> ns:id </li></ul></ul><ul><ul><li> searchedTerm </li></ul></ul><ul><li>Targeted services to a specific endpoint </li></ul><ul><ul><li> ns2/ns1:id </li></ul></ul><ul><ul><li> searchedTerm </li></ul></ul>
  17. 17. Introduction Example of questions Bio2RDF can answer <ul><li>What is known about human BRCA genes? </li></ul><ul><ul><li> </li></ul></ul><ul><li>What is known about human BRCA genes in Entrez Gene databank (i.e., the Bio2RDF data source whose namespace is geneid)? </li></ul><ul><ul><li> </li></ul></ul><ul><li>What can you tell me which fact are known about the human tumor suppressor gene BRCA1 (Gene ID: 672 )? </li></ul><ul><ul><li> </li></ul></ul><ul><li>What information is linked to geneid:672? </li></ul><ul><ul><li> </li></ul></ul><ul><li>Which is the FASTA sequence of the human 5-hydroxytryptamine receptor 2A (whose accession number is AB037513 ) in NCBI GeneBank databank (i.e., the Bio2RDF data source whose namespace is genbank). </li></ul><ul><ul><li> </li></ul></ul><ul><li>And the image? </li></ul><ul><ul><li> </li></ul></ul>
  18. 18. Introduction Complex Example: Linking Open Data Project <ul><li>Goal: extend the Web with data commons by publishing open data sets using Semantic Web techs </li></ul>Visit ! <ul><li>Project Chartres </li></ul><ul><li>RDFizers and ConverterToRdf </li></ul><ul><li>Publishing Tools </li></ul><ul><li>Semantic Web Browsers and Client Libraries </li></ul><ul><li>Semantic Web Search Engines </li></ul><ul><li>Applications </li></ul><ul><li>[…] </li></ul>Bio2RDF
  19. 19. Introduction Light Example: Publishing Semantic Mark-up <ul><li>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” </li></ul><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>
  20. 20. Introduction Example: BBC’s Artist as Linked Data <ul><li><?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot;?> </li></ul><ul><li><rdf:RDF </li></ul><ul><li>xmlns:rdf = &quot;; </li></ul><ul><li>xmlns:rdfs = &quot;; </li></ul><ul><li>xmlns:owl = &quot;; </li></ul><ul><li>xmlns:dc = &quot;; </li></ul><ul><li>xmlns:foaf = &quot;; </li></ul><ul><li>xmlns:rel = &quot;; </li></ul><ul><li>xmlns:mo = &quot;; </li></ul><ul><li>xmlns:rev = &quot;; > </li></ul><ul><li><rdf:Description rdf:about=&quot;/music/artists/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432.rdf&quot;> </li></ul><ul><li><rdfs:label>Description of the artist U2</rdfs:label> </li></ul><ul><li><foaf:primaryTopic rdf:resource=&quot;/music/artists/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432#artist&quot;/> </li></ul><ul><li></rdf:Description> </li></ul><ul><li><mo:MusicGroup rdf:about=&quot;/music/artists/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432#artist&quot;> </li></ul><ul><li><foaf:name>U2</foaf:name> </li></ul><ul><li><owl:sameAs rdf:resource=&quot;; /> </li></ul><ul><li><foaf:page rdf:resource=&quot;/music/artists/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432.html&quot; /> </li></ul><ul><li><mo:musicbrainz rdf:resource=&quot;; /> </li></ul><ul><li><mo:homepage rdf:resource=&quot;; /> </li></ul><ul><li><mo:fanpage rdf:resource=&quot;; /> </li></ul><ul><li><mo:wikipedia rdf:resource=&quot;; /> </li></ul><ul><li><mo:imdb rdf:resource=&quot;; /> </li></ul><ul><li><mo:myspace rdf:resource=&quot;; /> </li></ul><ul><li><mo:member rdf:resource=&quot;/music/artists/7f347782-eb14-40c3-98e2-17b6e1bfe56c#artist&quot; /> </li></ul><ul><li><mo:member rdf:resource=&quot;/music/artists/1f52af22-0207-40ac-9a15-e5052bb670c2#artist&quot; /> </li></ul>HTML: RDF :
  21. 21. Introduction New York Times Thesaurus <ul><li>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 […]. </li></ul><ul><li>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 . </li></ul><ul><li>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. […] </li></ul><ul><li>So now you can visit and see that our “Colbert, Stephen” is equivalent to DBPedia’s and Freebase’s . Even more importantly, your computer can visit and get all of this information in a computer-readable (RDF) document. </li></ul><ul><li>October 29, 2009, 4:07 pm First 5,000 Tags Released to the Linked Data Cloud By EVAN SANDHAUS AND ROB LARSON </li></ul>
  22. 22. Introduction Browsing the LOD with Try it!
  23. 23. Introduction The new era of Semantic Apps <ul><li>One of the highlights of October's Web 2.0 Summit in San Francisco was the emergence of 'Semantic Apps' as a force. </li></ul><ul><li>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. </li></ul><ul><li>Read out more at </li></ul>
  24. 24. Introduction Semantic Web “layer cake” Standardized Under Investigation Already Possible [ source ]
  25. 25. Introduction Architectural view of the lower layers [source ]
  26. 26. Credits <ul><li>Introduction and RDF slides are partially based on “Fundamentals of the Semantic Web” by David Booth </li></ul>