Das Semantische Daten Web für Unternehmen


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  • Popular content types such as pictures, movies, calendars, encyclopedic articles, news recipes etc. are already sufficiently well supported on the Web.However, there is a long tail of special-interest content (profiles of expertise, historic data and events, bio-medical knowledge, intra-corporational knowledge etc.) which has very low or no current support (for filtering, aggregation, searching, querying, collaborative editing) on the Web.
  • Das Semantische Daten Web für Unternehmen

    1. 1. Das SemantischeDaten Web für UnternehmenVision, Technologie, Anwendungen<br />Sören Auer<br />Forschungsgruppe AKSW<br />
    2. 2. Warum Semantic Web?<br />Problem: Try to search for these things on the current Web:<br />Apartments near German-Russian bilingual childcare in Leipzig.<br />ERP service providers with offices in Vienna and London.<br />Researchers working on multimedia topics in Eastern Europe.<br />Informationis available on the Web, but opaque to current Web search.<br />Solution: complement text on Web pages with structured linked open data & intelligently combine/integrate such structured information from different sources:<br />Search engine<br />HTML<br />HTML<br />RDF<br />RDF<br />Web server<br />Web server<br />Web server<br />Web server<br />leipzig.de<br />Has everything about childcare in Potsdam.<br />Immobilienscout.de<br />Knows all about real estate offers in Germany<br />DB<br />DB<br />
    3. 3. Vom Web derDokumentezumSemantic Data Web<br />Semantic Web(Vision 1998, starting ???)<br /><ul><li>Reasoning
    4. 4. Logic, Rules
    5. 5. Trust</li></ul>Data Web (since 2006)<br /><ul><li>URI de-referencability
    6. 6. Web Data integration
    7. 7. RDF serializations</li></ul>Social Web (since 2003)<br /><ul><li>Folksonomies/Tagging
    8. 8. Reputation, sharing
    9. 9. Groups, relationships</li></ul>Web (since 1992)<br /><ul><li>HTTP
    10. 10. HTML/CSS/JavaScript</li></li></ul><li>The Long Tail of Information Domains<br />Pictures<br />The Long Tail by Chris Anderson (Wired, Oct. ´04) adopted to information domains<br />Recipes<br />News<br />Video<br />Calendar<br />Popularity<br />SemWeb supported structured content<br />Requirements-Engineering<br />Talentmanagement<br />Special interest<br />communities<br />Itinerary ofKing George<br />Gene<br />sequences<br />…<br />…<br />…<br />…<br />Currently supportedstructuredcontent types<br />Not or insufficiently supported content types<br />
    11. 11. Die Vision: ein Web VernetzterDaten<br />interlink<br />2009<br />2007<br />SILK<br />DXX Engine<br />fuse<br />create <br />2008<br />poolparty<br />SemMF<br />OntoWiki<br />2008<br />Sigma<br />WiQA<br />2008<br />2008<br />ORE<br />repair<br />classify<br />Virtouso<br />2009<br />DL-Learner<br />MonetDB<br />Sindice<br />enrich<br />
    12. 12. Semantic Web - Standards<br />Standardization Semantic Web<br />1994<br /><ul><li>First public presentation of the Semantic Web idea</li></ul>Semantic Web Architecture<br /><ul><li>Start of standardization of data model (RDF) and a first ontology languages (RDFS) at W3C</li></ul>1998<br /><ul><li>Start of large research projects about ontologies in the US and Europe (DAML & Ontoknowledge)</li></ul>2000<br />Current research<br /><ul><li>Start of standardization of a new ontology language (OWL) based on research results</li></ul>2002<br /><ul><li>Finalization of the standard for data (RDF) and ontology (OWL)</li></ul>2004<br /><ul><li>Standardization of a quer y language(SPARQL, 6. April 2006)
    13. 13. Ongoing work on rule languages(SWRL, DL-safe rules, RIF)
    14. 14. Extension of OWL to OWL 1.1 / 2.0
    15. 15. Ontology language of OMG based on UML (ODM)</li></ul>2006<br />Now standardized<br /><ul><li>RDFa</li></ul>2008<br /><ul><li>OWL2</li></ul>2009<br />6<br />
    16. 16. Data Zugriff und Integration auf semantischerEbene<br />Enterprise Information Integration<br />sets of heterogeneous data sources appear as a single, homogeneous data source<br />Research<br />Mediators<br />Ontology-based<br />P2P<br />Web service-based<br />Data Web<br /><ul><li>URIs as entity identifiers
    17. 17. HTTP as data access protocol
    18. 18. Local-As-View (LAV)</li></ul>Data Warehousing<br /><ul><li>Based on extract, transform load (ETL)
    19. 19. Global-As-View (GAV)</li></ul>Data Integration<br />Object-relational mappings (ORM)<br /><ul><li>NeXT’s EOF / WebObjects
    20. 20. ADO.NET Entity Framework
    21. 21. Hibernate</li></ul>Query Languages<br /><ul><li>Datalog, SQL
    22. 22. SPARQL
    23. 23. XPATH/XQuery</li></ul>Linked Data<br /><ul><li>de-referencable URIs
    24. 24. RDF serialization formats</li></ul>Procedural APIs<br /><ul><li>ODBC
    25. 25. JDBC</li></ul>Data Access<br />Triple/Quad Stores<br /><ul><li>RDF data model
    26. 26. Virtuoso, Oracle, Sesame</li></ul>RDBMS<br /><ul><li>Organize data in relations, rows, cells
    27. 27. Oracle, DB2, MS-SQL</li></ul>Others<br /><ul><li>XML, hierachical, tree, graph-oriented DBMS</li></ul>Column-oriented DBMS<br /><ul><li>Collocates column values rather than row values
    28. 28. Vertica, C-Store, MonetDB</li></ul>Data Models<br />Entity-attribute-value (EAV)<br /><ul><li>HELP medical record system, TrialDB</li></li></ul><li>Linked Data Web Technologie<br />1. Nutzt RDF alsDatenmodel<br />6.5.2010<br />takesPlaceAt<br />organizes<br />AKSW<br />LSWT2010<br />Leipzig<br />takesPlaceIn<br />2. Istserialisiert in Triple:<br />AKSW organizes LSWT2010<br />LSWT2010 takesPlaceAt “20100506”^^xsd:date<br />LSWT2010 takesPlaceAt Leipzig<br />3. Nutzt Content-negotiation<br />
    29. 29. RDF Vokabulare:Klassen & Eigenschaften Hierarchien<br />Beer rdf:typerdfs:Class<br />BottomFermentedBeerrdfs:subClassOf Beer<br />Bock rdfs:subClassOfBottomFermentedBeer<br />Lager rdfs:subClassOfBottomFermentedBeer<br />Pilsner rdfs:subClassOfBottomFermentedBeer<br />hasContentrdf:typerdfs:Property<br />hasAlcoholicContentrdfs:subPropertyOfhasContent<br />hasOriginalWortContentrdfs:subPropertyOfhasContent<br />9<br />
    30. 30. RDF-S Instanzen<br />Instanzen sind einer oder mehreren Klassen zugeordnet:<br />Boddingtons rdf:type Ale<br />Grafentrunkrdf:type Bock<br />Hoegaardenrdf:type White<br />Jeverrdf:type Pilsner <br />10<br />
    31. 31. Vokabulare: Friend-of-a-Friend (FOAF)<br />definesclassesandpropertiesforrepresentinginformationaboutpeopleandtheirrelationships<br />Soeren rdf:typefoaf:Person<br />Soeren currentProject http://OntoWiki.net<br />Soeren foaf:homepage http://aksw.org/Soeren<br />Soeren foaf:knows http://sembase.at/Tassilo<br />Soeren foaf:sha1 09ac456515dee<br />11<br />
    32. 32. Integration von RDF und HTML: RDFa<br />12<br /><div typeof="foaf:Person" xmlns:foaf="http://xmlns.com/foaf/0.1/"><br /> <p property="foaf:name"> Alice Birpemswick </p><br /> <p> Email: <a rel="foaf:mbox"href="mailto:alice@exa.com">alice@exa.com</a> </p><br /> <p> Phone: <a rel="foaf:phone"href="tel:+1-617-555-7332">+1 617.555.7332</a> </p><br /></div><br />
    33. 33. Anwendungs- und EinsatzpotentialeimUnternehmen<br />Integration heterogenerInformationsbeständemittelsOntologien und Hintergrundwissen (z.B. DBpedia)<br />Semantische Wikis (z.B. OntoWiki) helfenstrukturierteWissensbasenzuerstellen und managen<br />
    34. 34. Transformation von Wikipedia in eineWissensbasis<br />community effort to extract structured information from Wikipedia and to make this information available on the Web<br />allows to ask sophisticated queries against Wikipedia (e.g. universities in brandenburg, mayors of elevated towns, soccer players), and to link other data sets on the Web to Wikipedia data<br />Represents a community consensus<br />Recently launched DBpedia Live transforms Wikipedia into a structred knowledge base<br />S. Auer; C. Bizer, J. Lehmann, G. Kobilarov, R. Cyganiak, Z. Ives: DBpedia: A Nucleusfor a Web of Open Data. 6th International Semantic Web Conference ISWC 2007.<br />S. Auer, J. Lehmann: Whathave Innsbruck and Leipzig in common? ExtractingSemanticsfrom Wiki Content. 4th European Semantic Web Conference, ESWC 2007.<br />
    35. 35. Structure in Wikipedia<br />Title<br />Abstract<br />Infoboxes<br />Geo-coordinates<br />Categories<br />Images<br />Links<br />other language versions<br />other Wikipedia pages<br />To the Web<br />Redirects<br />Disambiguations<br />
    36. 36. Infobox templates<br />Wikitext-Syntax<br />{{Infobox Korean settlement<br />| title = Busan Metropolitan City<br />| img = Busan.jpg<br />| imgcaption = A view of the [[Geumjeong]] district in Busan<br />| hangul = 부산 광역시<br />...<br />| area_km2 = 763.46<br />| pop = 3635389<br />| popyear = 2006<br />| mayor = Hur Nam-sik<br />| divs = 15 wards (Gu), 1 county (Gun)<br />| region = [[Yeongnam]]<br />| dialect = [[Gyeongsang]]<br />}}<br />http://dbpedia.org/resource/Busan<br />dbp:Busan dbpp:title ″Busan Metropolitan City″<br />dbp:Busan dbpp:hangul ″부산 광역시″@Hang<br />dbp:Busan dbpp:area_km2 ″763.46“^xsd:float<br />dbp:Busan dbpp:pop ″3635389“^xsd:int<br />dbp:Busan dbpp:region dbp:Yeongnam<br />dbp:Busan dbpp:dialect dbp:Gyeongsang<br />...<br />RDF representation<br />
    37. 37. Einegroße multi-linguale, multi-domänenWissensbasis<br />DBpediaExtraktionresultiertin:<br />Beschreibungen von ca. 3.4 MillionenDingen(1.5 million classified in a consistent ontology, including 312,000 persons, 413,000 places, 94,000 music albums, 49,000 films, 15,000 video games, 140,000 organizations, 146,000 species, 4,600 diseases<br />Labels und Zusammenfassungen in 92 verschiedenenSprachen; 1,460,000 links to images and 5,543,000 links to external web pages; 4,887,000 external links into other RDF datasets, 565,000 Wikipedia categories, and 75,000 YAGO categories<br />Zusammenmehrals1 MilliardeFakten(d.h. RDF triple): 257M from English edition, 766M from other language editions<br />DBpediahinterläßt sichtbareSpurenin Wissenschaft, Technologieand Gesellschaft<br />DBpedia became the central interlinking hub on the Data Web<br />Scientific publications attracted more than 500 citations<br />More than 15.000 monthly visits on DBpedia.org,numerous press articles, blog posts …<br />Ecosystem of commercial and community applications:ThomsonReuters, BBC, Neofonie, Openlink, Faviki…<br />
    38. 38. Das Semantische Daten Wiki<br />Agiles, verteiltes Knowledge Engineering<br />KeinWiki mitsemantischerErweiterung(Semantic MediaWiki, IkeWiki), sondern Ontology Editor der Wiki Konzeptenutzt:<br />Make it easy tocorrect mistakes(ant intelligence)<br />Activity can bewatched andreviewed<br />Everything canbe undone<br />AKSW Vorstellung<br />
    39. 39. OntoWiki: CatalogusProfessorum<br />
    40. 40.
    41. 41.
    42. 42. SoftWiki<br />Problem: Requirements Engineering mitgroßen, geografischverteilten Stakeholder-Gruppen<br />Lösung:umfassendeOntologie für RE Wissen+ adaptierteOntoWikiAnwendung<br />Anwendung von Textmining<br />Algorithmen für DuplicateDetection<br />
    43. 43. OntoWiki: Vakantieland<br />
    44. 44. Take Home Messages<br />Semantic Web<br />Unterstützt die Integration von Datenim Web (einheitliches Triple-Datenmodel)<br />Standardisierte (W3C) Linked Data Technologiebasis<br />Ontologien und Hintergrundwissen (z.B. DBpedia) hilftbeider Integration heterogenerInformationsbestände<br />Semantische Wikis helfen RDF Wissensbasenzuerstellen und managen<br />
    45. 45. Vielen Dank!<br />Sören Auer<br />auer@informatik.uni-leipzig.de<br />Agile Knowledge Engineering & Semantic Web (AKSW)http://aksw.org<br />BerufsbegleitenderMasterstudiengang“Content- & Media Engineering”<br />M1: Medienproduktion (GMP)<br />M2: Web-Technologien (WT)<br />M3: Content- und Wissensmanagement-Systeme (CWM)<br />M4: Crossmediale Produktion (CP)<br />M5: Medienwirtschaft und Medienmanagement (MW)<br />M6: Projektarbeit (PA)<br />M7: E-Business (EB)<br />http://www.leipzigschoolofmedia.de/<br />Mediencampus “Villa Ida”<br />