Semantic web

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gcaprio

Semantic Web & Linked Data presentational overview

Technology Education

Semantics Web:
how you can make up your own truth

Semantic Web

Linked Data Semantic Tech

Triple
NLP ML
Stores

Subject Predicate Object

Pam
Spouse

Carmen
Child
Grifﬁn

Subject/Predicate/Object
=
Row/Column/Value

Key-Value BigTable

Document Store Graph

Subject Predicate Object

Pam
Spouse

Carmen Child

Child
Grifﬁn

An ontology is a
speciﬁcation of a
conceptualization.

A Simple Animal Ontology

Body Part Living Thing
eats!
has part!
Plant
Arm
Animal eats!

Leg eats! Grass
Herbivore

Person Tree
Carnivore
Cow

Simple
Knowledge
Organization
System (SKOS)

Semantically
Interlinked Online
Communities
(SIOC)

gcaprio@1530technologies.com
www.twitter.com/gcaprio

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Semantic web

1. Semantics Web: how you can make up your own truth

2. Who Am I?

3. Talk Subject

4. Semantic Web vs. semantic web

7. Semantic Web Linked Data Semantic Tech Triple NLP ML Stores

8. Semantics

9. I Love Pizza = I Pizza

10. Semantic Data

11. RDF

12. Triple

13. Subject Predicate Object Pam Spouse Carmen Child Grifﬁn

14. Subject/Predicate/Object = Row/Column/Value

15. RDF/XML

16. N3

17. NTriples

18. Triplestores

19. NoSQL

20. Key-Value BigTable Document Store Graph

21. Key-Value BigTable Document Store Graph

22. D2R Server

23. Differences vs. RDBMS

24. 1. Subject = URI

25. Anyone Anything Anything

26. 2. Inference

27. Subject Predicate Object Pam Spouse Carmen Child Child Grifﬁn

28. Ontologies

29. An ontology is a speciﬁcation of a conceptualization.

30. Relationships

31. A Simple Animal Ontology Body Part Living Thing eats! has part! Plant Arm Animal eats! Leg eats! Grass Herbivore Person Tree Carnivore Cow

32. RDFS

33. Properties:Label, SubClass, Range

34. OWL

35.

36. Relationships: sameAs, differentFrom

37. 3. Linked Data

38. May 2008

39. March 2009?

40.

41. August 2010?

42.

43. Linked Vocabularies

44. Friend of a Friend (FOAF)

45. Dublin Core (title, date, subject)

46. Simple Knowledge Organization System (SKOS)

47. Semantically Interlinked Online Communities (SIOC)

48. 4. Network Effect

49. Using RDF

50. SPARQL

51. Creation of New Data

52. 5. Embedded Publishing

53. RDFa, eRDF & Microformats

54. LinkedIn:

55.

56.

57. So?

58. Linked Data + Embedded Semantic Data =

59. Schema.org

60. Google, MS, Yahoo

61.

62. Google Rich Snippets

63.

64.

65.

66. Study: Best Buy

67. GoodRelations Ontology

68.

69.

70. How About Publishers?

71. Triplify

72. Publishing Plugin

73. Drupal

74. RDFa

75. By Default

76.

77.

78. And?

79. Facebook

80. OpenGraph

81.

82. Big Data

83. Metadata Discovery

84. Example: Hadoop

85. Kasabi

86. Conclusion

87. Questions?

88. gcaprio@1530technologies.com www.twitter.com/gcaprio

Editor's Notes

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Thing / Property / Value\n
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Thing / Property / Value\n
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Thing / Property / Value\n
Put simply, an ontology is a specification of the characteristics of a domain. In other words, precisely what it mean for something to be in a particular domain.\n \nA taxonomy is simply a hierarchical categorization or classification of entities within a domain.\n
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Network & Links of People\n
Simple vocab ( label, description, etc... ) \n
Classification System ( concept, definition, etc... ) \n
Post, comment, etc...\n
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SPARQL Protocol and RDF Query Language\n
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eRDF = non W3C copy of microformats\nRDFa = W3C copy of microformats.\n
eRDF = non W3C copy of microformats\nRDFa = W3C copy of microformats.\n
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Semantic web

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Editor's Notes