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INTRODUCTION TO Elena Simperl, University of Southampton, UK THE - PowerPoint PPT Presentation

INTRODUCTION TO Elena Simperl, University of Southampton, UK THE SEMANTIC WEB e.simp mperl@sot soton.ac.uk @esimperl rl THE BEGINNINGS The Semantic Web is no not a a sep separate We Web but an extens nsion n of the he c current


  1. INTRODUCTION TO Elena Simperl, University of Southampton, UK THE SEMANTIC WEB e.simp mperl@sot soton.ac.uk @esimperl rl

  2. THE BEGINNINGS “The Semantic Web is no not a a sep separate We Web but an extens nsion n of the he c current on one, in which information is given we well-de defined m meaning ng, better enabl bling ng com ompu puters a and nd p peopl ple to to wo work rk i in cooperat ation on” [Berners-Lee, Hendler & Lassila, 2001]

  3. NOT A SEPARATE WEB Dece centr tralized ed i informati tion s space ce (for people) Consisting of documents and other Web resources  Uniquely identified  Connected to each other via hyperlinks  Accessed via the Internet http://info.cern.ch/hypertext/WWW/TheProject.ht  Created and used by different parties ml Technologies  URIs  HTML  HTTP

  4. BUT AN EXTENSION OF THE CURRENT ONE A decentralized information space (for computers an and pe d people) A Web of A Web of data ta Consisting of information and non-information resources  Uniquely identified  Connected to each other via hyperlinks  Accessed via the Internet  Created and used by different parties

  5. INFORMATION WITH WELL- DEFINED MEANING Machines can process Web information ‘intelligently One can encode this additional information in a machine- This article is about a person processable way This article is about a writer People and writers have  Using formal knowledge charac acterist stic pr properties es e.g., representation languages and they are born somewhere • reasoning they publish books • books have topics, chapters, • a price etc.

  6. COMPUTERS AND PEOPLE WORK IN COOPERATION Artificial intelligence: “th the scienc ence a and eng engine neering ng of making ng i intel ellige gent machines” [John Mc Carthy, http://www-formal.stanford.edu/jmc/whatisai/whatisai.html] Areas of AI Knowledge representation  Inference  Logics  Search  Planning and scheduling  Pattern recognition  Learning  Natural language processing  Computer vision  Robotics  .... 

  7. MEANING ON THE WEB  Add metadat adata to Web resources  Dif ifferent t types o of lin links ks  Encode additional information about metadata entities and links in onto ntologies  No global bal information schemas  Incomple lete and inconsistent [Examples from Wikipedia]

  8. YOU DON’T HAVE TO BUILD YOUR OWN ONTOLOGY

  9. LINKED DATA MAKES DATA INTEGRATION EASY Concepts, entities, and properties are accessible on the Web just as traditional Web documents Linked Data: Linked Data: Set of technologies and principles to publish and access data on the Web http://lod-cloud.net/ http://www.ted.com/talks/tim_berners_lee _on_the_next_web.html

  10. SEMANTIC WEB STACK Standardized family of languages  Compatible with the Web architecture  With a formal semantics Linked data is part of the stack Tools  Editors  Data stores  Reasoners  Machine learning  NLP  Data interlinking  …

  11. FROM THE SEMANTIC WEB TO SEMANTIC TECHNOLOGIES “The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries” [W3C]

  12. EXAMPLE: KNOWLEDGE GRAPH MAKING SEARCH MORE INTELLIGENT http://googleblog.blogspot.gr/2012/05/introducing-knowledge-graph-things-not.html

  13. EXAMPLE: BBC & MEDIA CONTENT PUBLISHING AND INTEGRATION

  14. EXAMPLE: OPEN GRAPH INTEROPERABLE CONTENT REPRESENTATION http://ogp.me/ Represent Web content in a social graph in an interoperable way Used by Facebook (‘stories’), Google (snippets), IMDb etc. Facebook: actors, apps, objects with metadata to create stories  Example: Elena has finished reading ‘The Economist’, an object of type Newspaper  Types with attributes, extensions allowed  Pre-defined and custom actions on objects Image from https://developers.facebook.com/docs/opengraph/cre ating-custom-stories 10/5/2015 14

  15. EXAMPLE: PROJECT HALO Ima mages f from http:/ ://w /www.projecthalo.com and d http:/ ://w /www.inquireproject.com/ m/ 05.10.2015

  16. EXAMPLE: DATA.GOV USING LINKED DATA TO PUBLISH GOVERNMENT OPEN DATA

  17. SEMANTIC WEB TODAY Semantic Web technologies, standardized by the W3C, are mature  RDF recommendation in 1999, update in 2004  RDFa (RDF in HTML) note in 2008  RDFS recommendation in 2004  SPARQL recommendation in 2008  OWL recommendation in 2004, update in 2009 Schema.org markup (RDFa, microformats, microdata)  http://www.webdatacommons.org/structureddata/ Linked Open Data  http://linkeddatacatalog.dws.informatik.uni- mannheim.de/state/ Ontologies  http://lov.okfn.org/dataset/lov/

  18. JOIN THE SEMANTIC WEB COMMUNITY Mailing lists Mailing lists Workshops Workshops  public_lod  Knowledge Discovery and Data Mining Meets  semanticweb Linked Open Data @ESWC  Diverse others for special topics (Dbpedia,  Consuming Linked Data @ISWC schema.org etc.)  Detection, Representation, and Exploitation of Facebook, LinkedIn, Quora Facebook, LinkedIn, Events in the Semantic Web @ESWC  Services and Applications over Linked APIs Conferences Conferences and Data @ESWC  Academic: ESWC, ISWC, WWW, AAAI etc.  Ontology Alignment Evaluation Initiative  Applied/industry: Semantics, SmartData etc. @ISWC  Semantic Statistics @ISWC  Ontology Design Patterns @ISWC  NLP & Dbpedia @ISWC  Linked Data for Information Extraction @ISWC  …

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