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Lecture 1: Semantic Web and RDF Aidan Hogan aidhog@gmail.com THE - PowerPoint PPT Presentation

Lecture 1: Semantic Web and RDF Aidan Hogan aidhog@gmail.com THE WEB The Web is now 26 years old Evolution of the Web The Future of the Web? THE SEMANTIC WEB The Semantic Web what is the Semantic Web? Semantic Web?


  1. Lecture 1: Semantic Web and RDF Aidan Hogan aidhog@gmail.com

  2. THE WEB

  3. The Web is now 26 years old

  4. Evolution of the Web

  5. The Future of the Web?

  6. THE “SEMANTIC WEB”

  7. The “Semantic Web” … what is the “Semantic Web”?

  8. Semantic Web? semantic web

  9. Semantic Web? “ The Semantic Web will bring structure to the meaningful content of Web pages, creating an environment where software agents roaming from page to page can readily carry out sophisticated tasks for users .” ─ Berners- Lee et al. (2001) “The Semantic Web” Sci. American. 284(5):34 – 43.

  10. WHAT’S WRONG WITH THE CURRENT WEB?

  11. The current Web is document-centric

  12. The current Web is document-centric

  13. (Most of it) Makes sense to humans

  14. Not to machines

  15. Not to machines

  16. What machines on the Web can do

  17. What machines on the Web can do

  18. This (with some “tricks”) works really well

  19. Can even get “direct answers” now

  20. THE WEB IS GREAT … … WHAT’S THE PROBLEM …

  21. At its core, Google is still just doing … (… but really really well)

  22. Let’s ask a question … … what might the output be?

  23. A structured question on structured data … … what might the output be?

  24. From a human perspective …

  25. (1) Data, (2) Query, (3) Rules/Ontologies

  26. THE SEMANTIC WEB: NOT JUST PURELY ACADEMIC

  27. Hidden within the Web … let’s have a look

  28. The Linked Data Cloud Oct. 2007 Nov. 2007 Feb. 2008 Sep. 2008 Mar. 2009 July 2009 Sept. 2010 Sept. 2011

  29. Linked Government Data: data.gov 29

  30. Linked Government Data: data.gov.uk 30

  31. Linked Government Data: datos.gob.cl

  32. Life Sciences 32

  33. Life Sciences 33

  34. New York Times Meta-data http://data.nytimes.com/schools/schools.html 34

  35. schema.org (Bing, Google, Yahoo!, Yandex) 35

  36. Facebook Open Graph Protocol

  37. Google’s Knowledge Graph

  38. A MORE IN-DEPTH USE-CASE: WIKIDATA

  39. What is Wikidata?

  40. Problem 1: Different language versions manually edited by users

  41. Problem 2: Complex lists of things manually edited by users

  42. Solution: Wikidata • Collaboratively edit structured data in one place, with multi-lingual labels

  43. Wikidata facts about Abraham Lincoln

  44. STRUCTURING WEB DATA WITH RDF: RESOURCE DESCRIPTION FRAMEWORK

  45. (1) Data, (2) Query, (3) Rules/Ontologies

  46. RDF: Resource Description Framework

  47. Modelling the world with triples

  48. Concatenate to “integrate” new data

  49. RDF often drawn as a (directed, labelled) graph

  50. Set of triples thus called an “RDF Graph”

  51. NAMING THINGS IN RDF: IRIS

  52. Need unambiguous symbols/identifiers • Since we’re on the Web … use Web identifiers • URL: Uniform Resource Location – The location of a resource on the Web – http://ex.org/Dubl%C3%ADn.html • URI: Uniform Resource Identifier (RDF 1.0) – Need not be a location, can also be a name – http://ex.org/Dubl%C3%ADn • IRI: Internationalised Resource Identifier (RDF 1.1) – A URI that allows Unicode characters – http://ex.org/Dublín

  53. We will use IRIs with prefixes • http://ex.org/Dublín ↔ ex:Dublín • “ ex: ” denotes a prefix for http://ex.org/ • “ Dublín ” is the local name

  54. Frequently used prefixes

  55. From strings …

  56. … to IRIs …

  57. NAMING THINGS IN RDF: LITERALS

  58. What about numbers? Should we assign IRIs to numbers, etc.?

  59. RDF allows “literals” in object position • Literals are for datatype values, like strings, numbers, booleans, dates, times • Only allowed in object position

  60. Datatype literals • “lexical - value”^^ ex:datatype – “200”^^ xsd:int – “2014 -12- 13”^^ xsd:date – “true”^^ xsd:boolean – “this is a string”^^ xsd:string • If the datatype is omitted, it’s a string – “this is a string” – “200” is a string, not a number!

  61. Many datatypes borrowed from XML Schema

  62. Boolean datatype

  63. Numeric datatypes

  64. Temporal datatypes

  65. Text/string datatypes

  66. Language-Tagged Strings • Specify that a string is in a given language • “string”@ lang-tag • No datatype!

  67. (NOT) NAMING THINGS IN RDF: BLANK NODES

  68. Having to name everything is hard work

  69. For this reason, RDF gives blank nodes • Syntax: _:blankNode • Represents existence of something – Often used to avoid giving an IRI (e.g., shortcuts) • Can only appear in subject or object position • (More later)

  70. RDF TERMS: SUMMARY

  71. A Summary of RDF Terms 1. IRIs (Internationalised Resource Identifiers) – Used to name generic things 2. Literals – Used to refer to datatype values – Strings may have a language tag 3. Blank Nodes – Used to avoid naming things – A little mysterious right now

  72. MODELLING DATA IN RDF

  73. Let’s model something in RDF … Model the following in RDF: “ Sharknado is the first movie of the Sharknado series. It first aired on July 11, 2013. The movie stars Tara Reid and Ian Ziering . The movie was followed by ‘Sharknado 2: The Second One ’.

  74. RDF Properties • RDF Terms used as predicate • rdf:type , ex:firstMovie , ex:stars , …

  75. RDF Classes • Used to conceptually group resources • The predicate rdf:type is used to relate resources to their classes

  76. Modelling in RDF not always so simple Model the following in RDF: “ Sharknado stars Tara Reid in the role of ‘April Wexler’.

  77. Modelling in RDF not always so simple Model the following in RDF: “The first movie in the Sharknado series is ‘Sharknado’. The second movie is ‘Sharknado 2: The Second One’. The third movie is ‘Sharknado 3: Oh Hell No!’.

  78. RDF Collections: Model Ordered Lists • Standard way to model linked lists in RDF • Use rdf:rest to link to rest of list • Use rdf:first to link to current member • Use rdf:nil to end the list

  79. RDF Collections: Generic Modelling • Not just for Sharknado series

  80. RDF SYNTAXES: WRITING RDF DOWN

  81. N-Triples • Line delimited format • No shortcuts

  82. RDF/XML • Legacy format • Not intuitive

  83. RDFa • Embed RDF into HTML • Not so intuitive

  84. JSON-LD • Embed RDF into JSON • Not completely aligned with RDF

  85. Turtle • Readable format

  86. Turtle: Collections Shortcut

  87. BLANK NODES ADD COMPLEXITY

  88. Blank nodes names aren’t important … (Isomorphic)

  89. Blank nodes are local identifiers How should we combine these two RDF graphs?

  90. Need to perform an RDF merge How should we combine these two RDF graphs?

  91. Are two RDF graphs the “same”? (Isomorphic)

  92. Are two RDF graphs the “same”?

  93. RECAP

  94. (1) Data, (2) Query, (3) Rules/Ontologies

  95. RDF: Resource Description Framework

  96. RDF = Resource Description Framework • Structure data on the Web! • RDF based on triples: – subject, predicate, object – A set of triples is called an RDF graph • Three types of RDF terms: – IRIs (any position) – Literals (object only; can have datatype or language) – Blank nodes (subject or object)

  97. RDF = Resource Description Framework • Modelling in RDF: – Describing resources – Classes and properties form core of model – Try to break up higher-arity relations – Collections: standard way to model order/lists • Syntaxes: – N-Triples: simple, line-delimited format – RDF/XML: legacy format, horrible – RDFa: embed RDF into HTML pages – JSON-LD: embed RDF into JSON – Turtle: designed to be human friendly

  98. RDF = Resource Description Framework • Two operations on RDF graphs: – Merging: keep blank nodes in source graphs apart – Are they the “same” modulo blank node labels: isomorphism check!

  99. Questions?

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