Wissenstechnologie I
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  • 1. Wissenstechnologie WS 08/09 Michael Granitzer IWM TU Graz & Know-Center Know Center http://kmi tugraz at http://kmi.tugraz.at http://www.know-center.at http://www know center at This work is licensed under the Creative Commons Attribution 2.0 Austria License. To view a copy of this license, visit http://creativecommons.org/licenses/by/2.0/at/.
  • 2. Today Organization Overview, Motivation and Goals of this lecture 2 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 3. Organization Lecturer • Michael Granitzer(mgranitzer@tugraz.at) Topics p Semantic Web & Top Down Knowledge Modelling Web 2.0 & Bottom Up Knowledge Creation Homepage: http://kmi.tugraz.at/blogs/wissenstechnologie Wordpress Blog News and slides for the lecture Slildes will be in English, lectures as needed 3 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 4. Organization Weekly lectures, no mandatory attendancy (Keine Anwesenheitspflicht) Interrupt me on questions Mandatory attendance (Anwesenheitspflicht) for guest lectures & students presentation (mixed English/German) If you can not participate, write me an e-mail Lectures from 10:15 to around 11:45. Rest is used for practical p exercise News will be on the blog ( use RSS!) Enroll for the course: Deadline is 15.10.08 4 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 5. Organization Feed Reader Free Feed-Reader Google Reader http://www.google.de/reader p // g g / Mozilla Thunderbird http://www.mozilla.com/thunderbird/ Omea Reader http://www.jetbrains.com/omea/reader/ Others http://en.wikipedia.org/wiki/List_of_feed_aggregators 5 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 6. Organization – Practical Excercise Practical/technical or theoretical working out of particular topics in groups of 2-4 f Presentation of your results in December/Januar Topics p Presented next week Announced also on the blog http://kmi.tugraz.at/blogs/wissenstechnologie/ubungsthemen/ ttp // tug a at/b ogs/ sse stec o og e/ubu gst e e / Passwort: wt08 Own proposals are possible as long as they fit the topic of the lecture Details: http://kmi.tugraz.at/blogs/wissenstechnologie/prufungsmodus/ You can cancel your participation in this course during the entire course of this semester (will not result in a negative grade) 6 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 7. Organization – Grading Theoretical Exercise Gather relevant literature for a specific topic using Bibsonomy (bibsonomy.org) and compile an overview on the topic (10 %) – Tag with WT08 UNIQUE_GROUP_TAG – Make your publications accessible via RSS Collaboratively write a paper on the relevant literature using Google Docs (45 %) – Invite me as viewer (mgrani@gmail com) (mgrani@gmail.com) – Paper should be around 8-12 pages depending on the group size – Not only the content will be judged, but also how it was created Presentation of the results (45 %) Make clear who in the group did what 7 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 8. Organization – Grading Technical Exercise Technical documentation using Google Docs (10%) – Invite me as viewer (mgrani@gmail.com) – Requirements definition – System architecture and software design – Documentation Implementation (50%) Short Presentation of the prototype/solution (40%) Make clear who in the group did what 8 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 9. Organization – Scheduling Milestone Theoretical Technical How? Exercise Exercise Next Week Topic presentation In the lecture/ on (8.10.08) the blog 22.10.08 Topic selection and group via E-Mail to me announcement 24.11.08 Gathering of Requirements Bibsonomy/ Google relevant Literature Definition finished Docs finished 11 12 08 & 11.12.08 Oral t ti O l presentation O l presentation Oral t ti 08.01.09 of results & of results & feedback from my feedback from my side side 29.01.09 Delivery of final Delivery of final Via Google Docs results results 9 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 10. Fragen 10 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 11. Today Organisatorisches Overview, Motivation and Goals of this lecture 11 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 12. Agenda The digital world (wide web) today Our problem: the semantic gap S l ti Solution S Semantic W b !? ti Web Solution „Web 2.0“/Social Web!? How to get there… The lectures agenda 12 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 13. The digital world (wide web) today It s It’s structure The web is a bow tie Nature 405, 113(11 May 2000) 13 doi:10.1038/35012155 doi:10 1038/35012155 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 14. The digital world (wide web) today It’s size Information growth per year (including print, film, optical etc.) Wachstum 1000 999 900 800 700 600 xabytes 500 Ex 400 300 200 160 100 0 1,6 5 1998 2000 2002 2004 2006 2008 2010 2012 Jahr 14 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 15. The digital world (wide web) today It’s size In 2002: 5 Exabytes new information stored All words ever spoken by mankind (http://www2.sims.berkeley.edu/research/projects/how-much-info-2003) In 2006 2010: 161 - 998 Exabytes 2006-2010: http://www.emc.com/about/destination/digital_universe/pdf/Expanding_Digital_Universe_IDC_WhitePaper_022507.pdf 161 exabyte 6 tons of books to read for every human on earth 998 exabytes: book stack from pluto to earth ¼ of the digital universe in 2006 is orignal content ¼ is contributed by images Voice accounts for 20% 15 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 16. The digital world (wide web) today It’s size The internet is a primer mover for the growth of digital information User generated content adds for 75% g 25% of the digital universe has been created in the workplaces of organizations It’s huge! It grows fast! 16 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 17. The digital world (wide web) today ...and so? Our brains/abilities did not change that fast Information/Knowledge Workers spend 14 5 h ki di 14.5 hours a week in reading and answering e-mails d i il 13.3 hours creating documents 9.6 9 6 hours searching 9.5 hours analyzing information 95% of the digital universe is unstructured. in organizations g g its slightly better by having “only” 80% of unstructured information But: unstructured information is hard to process 17 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 18. The Semantic Gap 18 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 19. The Semantic Gap p http://dbpedia.org/page/Paul_McCartney 19 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 20. Semantic Gap Knowledge Ideas thoughts processable Semantic Ontologies Concepts Human p proces Information Documents Metadata ssable Data Binary Data Machine Video Streams 20 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 21. Web 2.0 aka the Social Web 2.0? What Is Web 2 0? Technical: “Web 2.0 … The Machine is Us/ing Us“ htt // t b / t h? 6 P4 k0EOE http://www.youtube.com/watch?v=6gmP4nk0EOE Businesses: „Web 2.0 Remix“ http://www.youtube.com/watch?v=LcIDhJsOl0A Tim O'Reilly on What is Web 2.0? http://www.youtube.com/watch?v=CQibri7gpLM 21 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 22. Web 2.0 What to conclude? Web 2.0 New kind of internet businesses New services and mashup of services New (more concrete?) user generated content Collaboration & communication Prosumer = Consumer + Producer What else? 22 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 23. Web 2.0 Design Patterns The Long Tail Smaller communities are the mass of people (e.g. Amazon.com) Data is the Next Intel Inside Smart applications are needing smart data (GMail, Amazon Reviews und Recommender, vgl. BarnesAndNoble.com) Users Add Value User generated content and usage data (vgl. GoogleMaps, Amazon ASIN, usw.) Network Effects by Default Exploiting community effects for satisfying the community/increasing the community (avalance effect) 23 htt // ill / b/ / ill /ti / /2005/09/30/ h t i b 20 ht l? 5 http://www.oreilly.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.html?page=5 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 24. Web 2.0 Design Patterns Some Rights Reserved Reuse of data, (Creative Commons, Open Source) The Perpetual Beta Continuous development as the community needs it(vgl. Office 10, 11, 12 -> Flickr) Cooperate, Don t Cooperate Don‘t Control Aggregation of content and mashups Software above the Level of the Single Device g Combining different devices into one application (e.g. PC and Smart Phones, PDA, Tablets etc. ) 24 htt // ill / b/ / ill /ti / /2005/09/30/ h t i b 20 ht l? 5 http://www.oreilly.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.html?page=5 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 25. Web 2.0 How does it help? Pros: Social Bookmarking & Tagging: Adding Metadata to existing Information Collaborative Creation of Information: Wikipedia Social Search: Connecting people Context based search & recommender systems Specialised services and mashup of services Cons: Increase in information growth Again information is unstructured 25 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 26. Semantic Web Video Berners Lee Tim Berners-Lee on the Semantic Web http://www.technologyreview.com/video/semantic 26 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 27. Semantic Web Web of data Decentral Intelligent A I t lli t Agent t Increase in information quality Let the machine do the hard work… 27 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 28. Search in the WWW An example Image search for „Apache“ 28 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 29. The Problem of Meaning Searching for character sequences, not for concepts Syntactic search does not recognice Synonyms: different syntax, equal semantic (e.g. „money“,“cash“, „dollars“) Homonyme: equal syntax, diff l different semantic ( i (e.g. „Apache “) (e.g. Meaning in a particular context (e g linux and windows as operating systems) 29 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 30. The Problem of Relationships No Meaning of Realtionships Who tried to shoot Mr. Burns in „Who shot Mr. Burns? Part 1“ ( (6. Season)) 30 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 31. Definition „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 cooperations. [Berners-Lee et al. 2001] http://www.sciam.com/print_version.cfm?articleID=00048144- 10D2 1C70 84A9809EC588EF21 10D2-1C70-84A9809EC588EF21 31 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 32. The Vision as Application Scenario Plan a trip via the internet using your personal agent Agent searches automatically for Suitable flight Suitable hotels Alternative routes Also, the software agent tells you why it made this decision! 32 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 33. Intelligent Web = Semantic Web + Social Web Web 3 0 = Semantic Web + Web 2 0 ;) 3.0 2.0 • Semantic Wave Report. (http://www.readwriteweb.com/archives/semantic_wave_2008_free_report.php) (http://www readwriteweb com/archives/semantic wave 2008 free report php) 33 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 34. Semantic Web Agenda Inferenz & Reasoning Semantic W b Services S ti Web S i Semantic Search … Semantic Technologies Semantic Web Stack W b 2.0 Web 2 0 XML, RDFS, OWL, Ontology Modelling, Alignment OWL-DL & Matching Ontologies REST, AJAX, Syndication , , y Tagging, Folksonomies Representation of Knowledge Open Linked Data Ontology L O t l Learning i Text Mining Information Retrieval Unstructured People Information 34 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 35. Preliminary Agenda Date D t Topic T i 8.10. Semantic Web Stack: From URI‘s to RDF 16.10. Semantic Web Stack (cont‘d): RDF-S, OWL (cont d): RDF S, and Description Logic 23.10. Ontology Modelling, Ontology Alignment & Mapping 30.10. RDF Triple Stores, Query Languages, 6.11. Information Retrieval vs. Semantic Search 13.11. Guest Lectures: Semantic Web Services & Open Linked Data 20.11. Web 2.0 Part I: Basic Concepts and Ideas, Folksonomies, Tagging, Microformats etc. 27.11. Web 2.0 Part II: Social Semantic Systems 35 4.12. 4 12 O t l from T t Learning f Ontology L i Text http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 36. Preliminary Agenda Date D t Topic T i 11.12. Student presentation & feedback 08.01. Student presentation & feedback 15.01. Guest Lectures: Blog Analysis, Relationship Detection 22.01. Guest Lectures: Context Detection 29.01. Wrap Up: A summary of the semester 36 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 37. Points you should take away from this lecture What is the Semantic Web? What is/is not Web 2.0? What are the differences between the Semantic Web and Web 2.0? What is the need for Web 2.0 and the Semantic Web? 37 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 38. That‘s it for today… Thanks for your attention Questions/comments? mgranitzer@tugraz.at i @ 38 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at
  • 39. License This work is licensed under the Creative Commons Attribution 2.0 Austria License. To view a copy of this license, visit http://creativecommons org/licenses/by/2 0/at/ http://creativecommons.org/licenses/by/2.0/at/. Contributors: Mathias Lux Peter Scheir Klaus Tochtermann Michael Granitzer 39 http://kmi.tugraz.at WS 08/09 Wissenstechnologie @ kmi.tugraz.at