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SEO Meets Semantic Web - Saint Patrick's Day 2015-Meetup

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Schema.org didn't just appear out of thin air in 2011. It was built upon a foundation of web standards and technologies that have been in development for decades. In this presentation, Eric Franzon, Managing Partner of SemanticFuse provides an introduction to Semantic Web standards such as RDF and SPARQL. He explores who's using them today and why (hint: it involves money), and takes a look at how Semantic Web, Linked Data, and schema.org are related.

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SEO Meets Semantic Web - Saint Patrick's Day 2015-Meetup

  1. 1. ©2015 Eric Axel Franzon SEO Meets Semantic Web (Meets St. Patrick’s Day) Welcome!
  2. 2. ©2015 Eric Axel Franzon Eric Franzon Managing Partner Semantic Fuse A Roadmap for SEO Today and Tomorrow SemanticWeb:
  3. 3. ©2015 Eric Axel Franzon Semantic Web is like the harmonica
  4. 4. ©2015 Eric Axel Franzon Easy to play
  5. 5. ©2015 Eric Axel Franzon Easy to play; takes work to master.
  6. 6. ©2015 Eric Axel Franzon What we’ll discuss • What is Semantic Web? • Who’s using it? • What makes it work?
  7. 7. ©2015 Eric Axel Franzon What Is Semantic Web? • A Web-scale architecture • A metadata technology • A layer of meaning on the Web • In use TODAY!
  8. 8. ©2015 Eric Axel Franzon What Is it Not? • A software package • Something that will ever be “done” • A replacement for the current Web
  9. 9. ©2015 Eric Axel Franzon What Is it Not? • Limited to the public WWW • A pipe dream • A silver bullet • HAL 9000 or Skynet
  10. 10. ©2015 Eric Axel Franzon
  11. 11. ©2015 Eric Axel Franzon
  12. 12. ©2015 Eric Axel Franzon
  13. 13. ©2015 Eric Axel Franzon
  14. 14. ©2015 Eric Axel Franzon
  15. 15. ©2015 Eric Axel Franzon
  16. 16. ©2015 Eric Axel FranzonIoT Enhancements by Eric Franzon IoT
  17. 17. ©2015 Eric Axel Franzon • Globally • Inexpensively • In Real-Time (public) World Wide Web HTTP HTML Based on W3C Standards
  18. 18. ©2015 Eric Axel Franzon • Globally • Inexpensively • In Real-Time Behind the Firewall (public) World Wide Web HTTP HTML Based on W3C Standards
  19. 19. ©2015 Eric Axel Franzon • Globally • Inexpensively • In Real-Time Semantic Web RDF SPARQL OWL Based on W3C Standards
  20. 20. ©2015 Eric Axel Franzon • Globally • Inexpensively • In Real-Time Behind the Firewall Semantic Web RDF SPARQL OWL Based on W3C Standards
  21. 21. ©2015 Eric Axel Franzon • to connect DATA • to make information interpretable by machines Semantic Web Standards are used…
  22. 22. ©2015 Eric Axel Franzon Machine Interpretation as the Web Evolves…
  23. 23. ©2015 Eric Axel Franzon Web 1.0 – Linking Documents
  24. 24. ©2015 Eric Axel Franzon Web 1.0 “I see: characters + formatting + images” --my Computer
  25. 25. ©2015 Eric Axel Franzon Web 1.0 – Linking Documents Web 2.0 – Linking People
  26. 26. ©2015 Eric Axel Franzon Web 2.0 “I see: characters + formatting + images” --my Computer
  27. 27. ©2015 Eric Axel Franzon It’s hard to interpret meaning when all you see are characters, images, and formatting. Context is critical.
  28. 28. ©2015 Eric Axel Franzon Web 1.0 – Linking Documents Web 2.0 – Linking People Web 3.0 – Linking Data
  29. 29. ©2015 Eric Axel Franzon Web 3.0 – Linking Data Title Price Format Cover Band
  30. 30. ©2015 Eric Axel Franzon Web 3.0 – Linking Data Title Price Format Cover Band “I see: things + relationships. This is about a collection of music.”
  31. 31. ©2015 Eric Axel Franzon Q: What does “Linked Data” have to do with Semantic Web?
  32. 32. ©2015 Eric Axel Franzon A Quick word of disambiguation… Semantic Web - A vision for a web of data Semantic Web Standards - A specific set of standards Linked Data - One application area of those standards
  33. 33. ©2015 Eric Axel Franzon Semantic Web Standards Semantic Web Linked Open Data
  34. 34. ©2015 Eric Axel Franzon Semantic Web Standards Semantic Web Linked Open Data Linked Data
  35. 35. ©2015 Eric Axel Franzon Linking Open Data Project May, 2007
  36. 36. ©2015 Eric Axel Franzon July 2009
  37. 37. ©2015 Eric Axel Franzon September 2011
  38. 38. ©2015 Eric Axel Franzon August 2014
  39. 39. ©2015 Eric Axel Franzon Data from these trusted sources is available for you to use in your applications TODAY. Data you can LINK to.
  40. 40. ©2015 Eric Axel Franzon Semantic Data that is machine READABLE. …and machine INTERPRETABLE!
  41. 41. ©2015 Eric Axel Franzon Who’s Using Semantic Web Standards?
  42. 42. ©2015 Eric Axel Franzon • Healthcare / Life Sciences • Financial Services • Manufacturing / Retail • Marketing, Advertising • SEO/SEM • Libraries • Archives • Museums • Governments Who’s Using Sem Web?
  43. 43. ©2015 Eric Axel Franzon Who’s Using Sem Web?
  44. 44. ©2015 Eric Axel Franzon Who’s Using Sem Web?
  45. 45. ©2015 Eric Axel Franzon
  46. 46. ©2015 Eric Axel Franzon What it looks like
  47. 47. ©2015 Eric Axel Franzon
  48. 48. ©2015 Eric Axel Franzon • Activities • Businesses • Groups • Organizations • People • Places • Products and Entertainment • Websites Used to Describe
  49. 49. ©2015 Eric Axel Franzon What it looks like
  50. 50. ©2015 Eric Axel Franzon What it looks like <meta property='og:image' content="http://ia.media- imdb.com/images/M/MV5BMjA0MDYyNzczN15BMl5BanBnXkFtZTYwNjMzNjM z._V1_.jpg" /> <meta property='og:type' content="actor" /> <meta property='fb:app_id' content='115109575169727' /> <meta property='og:title' content="Peter O'Toole" /> <meta property='og:site_name' content='IMDb' /> <meta property="og:description" content="Peter O'Toole, Actor: Lawrence of Arabia. A leading man of prodigious talents, Peter O'Toole was raised in Leeds, England, the son of Constance Jane Eliot (Ferguson), a Scottish nurse, and Patrick Joseph O'Toole, an Irish bookie. As a boy, he decided to become a journalist, beginning as a newspaper copy boy. Although he succeeded in becoming a reporter, he discovered the theater and made his stage debut at 17. He served as a radioman in ..." />
  51. 51. ©2015 Eric Axel Franzon Who’s Using Sem Web?
  52. 52. ©2015 Eric Axel Franzon What is schema.org? “…A collection of schemas, i.e., html tags, that webmasters can use to markup their pages in ways recognized by major search providers.”
  53. 53. ©2015 Eric Axel Franzon e.g. Product Markup
  54. 54. ©2015 Eric Axel Franzon What it looks like
  55. 55. ©2015 Eric Axel Franzon e.g. TV Episode Markup
  56. 56. ©2015 Eric Axel Franzon What it looks like
  57. 57. ©2015 Eric Axel Franzon What it looks like
  58. 58. ©2015 Eric Axel Franzon e.g. Company
  59. 59. ©2015 Eric Axel Franzon What it looks like
  60. 60. ©2015 Eric Axel Franzon What it looks like
  61. 61. ©2015 Eric Axel Franzon Based on a sample of 12 billion web pages: • ~5 million domains (6% of domains) • 15 billion entities • 65 billion triples • 2.5 billion pages (~21% of pages) -Reported in an August 2014 SemTechBiz Keynote by R. V. Guha, Google Fellow Schema.org Adoption
  62. 62. ©2015 Eric Axel Franzon A work in progress
  63. 63. ©2015 Eric Axel Franzon Growing Up • ~ 100 categories at launch in 2011 • ~1200 by Sept. 2014 • Bibliographic Relationships & Periodicals (Sept. 2, 2014) • Music, Video Games, Sports, breadcrumbs, itemList (Dec. 11, 2014) • VisualArtwork, Invoices (Feb. 5, 2015) • Fixes to documentation, examples, & general bugs (ongoing)
  64. 64. ©2015 Eric Axel Franzon Growing Pains • Immature tools for • Publishing • Parsing • Evaluating • Lack of understanding/Misinformation
  65. 65. ©2015 Eric Axel Franzon • Incorrect Signals being sent • Global companies showing as local • Old data • Entities mismatched to concepts Feeling the Pain
  66. 66. ©2015 Eric Axel Franzon When it does work, though…
  67. 67. ©2015 Eric Axel Franzon When it does work, though…
  68. 68. ©2015 Eric Axel Franzon When it does work, though…
  69. 69. ©2015 Eric Axel Franzon What makes SemWeb work?
  70. 70. ©2015 Eric Axel Franzon The Technologies of SemWeb • Data • Schemas • Query Language
  71. 71. ©2015 Eric Axel Franzon The Data Language Resource Description Framework
  72. 72. ©2015 Eric Axel Franzon “RDF is good for distributing data across the Web and pretending it’s in one place.” -Dean Allemang, Author, Semantic Web for the Working Ontologist
  73. 73. ©2015 Eric Axel Franzon • to connect DATA • to make it interpretable by machines RDF is used… RDF is made up of triples!
  74. 74. ©2015 Eric Axel Franzon 1. By uniquely identifying THINGS 2. By uniquely identifying RELATIONSHIPS 3. By using TRIPLES Machine Interpretable - How?
  75. 75. ©2015 Eric Axel Franzon So, what’s a THING? 1. By uniquely identifying THINGS
  76. 76. ©2015 Eric Axel Franzon A THING is anything that can be uniquely identified by a URI or a literal (string) Me My postal code The White House L.A. County’s sales tax rate http://ericaxel.com/eric.rdf#me http://www.city-data.com/zips/59801.html Lat: 38.89859 Long: -77.035971 9.750 % http://ericfranzon.com/harpcase.jpg
  77. 77. ©2015 Eric Axel Franzon This is a collection of THINGS: t_people Name City State Post code Bill Carlsbad CA 92008 Eric Missoula MT 59801
  78. 78. ©2015 Eric Axel Franzon Who’s your daddy? 1. By uniquely identifying THINGS 2. By uniquely identifying RELATIONSHIPS
  79. 79. ©2015 Eric Axel Franzon Is Father of
  80. 80. ©2015 Eric Axel Franzon Is Father ofhttp://ericaxel.com/eric.rdf#me
  81. 81. ©2015 Eric Axel Franzon <owl:ObjectProperty rdf:ID="isFather"> <rdfs:domain rdf:resource="#Person"/> <rdfs:range rdf:resource="#Person"/> </owl:ObjectProperty> http://ericaxel.com/eric.rdf#me ns:isFather
  82. 82. ©2015 Eric Axel Franzon Is Father of <owl:ObjectProperty rdf:ID="isFather"> <rdfs:domain rdf:resource="#Person"/> <rdfs:range rdf:resource="#Person"/> </owl:ObjectProperty> http://ericaxel.com/eric.rdf#me ns:isFather
  83. 83. ©2015 Eric Axel Franzon <owl:ObjectProperty rdf:ID="isFather"> <rdfs:domain rdf:resource="#Person"/> <rdfs:range rdf:resource="#Person"/> </owl:ObjectProperty> http://ericaxel.com/eric.rdf#me ns:isFather
  84. 84. ©2015 Eric Axel Franzon <owl:ObjectProperty rdf:ID="isFather"> <rdfs:domain rdf:resource="#Person"/> <rdfs:range rdf:resource="#Person"/> </owl:ObjectProperty> ns:isFather
  85. 85. ©2015 Eric Axel Franzon 1. By uniquely identifying THINGS 2. By uniquely identifying RELATIONSHIPS 3. By using TRIPLES What’s a triple?
  86. 86. ©2015 Eric Axel Franzon The Building block of RDF The Triple
  87. 87. ©2015 Eric Axel Franzon Triples? It’s Elementary! (School) song has title.
  88. 88. ©2015 Eric Axel Franzon Triples? It’s Elementary! (School) song has title. Relationship
  89. 89. ©2015 Eric Axel Franzon Predicate Triples? It’s Elementary! (School) song has title.
  90. 90. ©2015 Eric Axel Franzon Triples? It’s Elementary! (School) song has title. That is a Triple!
  91. 91. ©2015 Eric Axel Franzon “This band recorded a song.” “This recording is part of a collection.” “This item has a barcode.” “I like blues.” “I like B.L.U.E.S.” “This image can be used non-commercially.” “My email address is eric.franzon@gmail.com.” Triples? It’s Elementary!
  92. 92. ©2015 Eric Axel Franzon Song Has Title “Title” Eric Created Webpage Image Has License CC Non- Commercial Make Assertions Subjects Objects Predicates
  93. 93. ©2015 Eric Axel Franzon Song Author Title PublisherLyrics A Simple Graph
  94. 94. ©2015 Eric Axel Franzon The Trouble with Triples
  95. 95. ©2015 Eric Axel Franzon Visualization of graph from Pharma space - Cytoscape.org
  96. 96. ©2015 Eric Axel Franzon Where does one store triples? In a “triple store”
  97. 97. ©2015 Eric Axel Franzon Where does one store triples? • Native Semantic Web stores • RDBMS databases • As native files (.rdf) • Woven into documents (RDFa) • Generated on the fly
  98. 98. ©2015 Eric Axel Franzon Just so you know… There are many ways of representing RDF: • RDF/XML • N3 • JSON-LD • N-Triples • Turtle • RDFa • Microdata • Microformats Each has pros and cons, but they all connect THINGS and RELATIONSHIPS into TRIPLES
  99. 99. ©2015 Eric Axel Franzon The Technologies of SemWeb • Data • Schemas • Query Language
  100. 100. ©2015 Eric Axel Franzon The Schemata Linked Data schemas consist of: Your RDF relationships (predicates) + Relationship descriptions
  101. 101. ©2015 Eric Axel Franzon SemWeb Schemata id First Name Last Name 1 Barbara Starr Schema Data Initial Schema hasID hasFirstName hasLastName Barbara Starr1 owl:sameAs hasSurname Relationship description
  102. 102. ©2015 Eric Axel Franzon Choosing Relationships • Reuse popular vocabularies –FOAF (Friend-of-a-friend) –Dublin Core (library/publisher metadata) –SIOC (Semantically-Interlinked Online Communities) –Schema.org • ...or make up your own!
  103. 103. ©2015 Eric Axel Franzon 1. Resource Description Framework Schema (RDFS): Simple, hierarchical classes 2. Simple Knowledge Organization System (SKOS): Port taxonomies to the Semantic Web 3. Web Ontology Language (OWL): Complex logical relationships Relationship Descriptions
  104. 104. ©2015 Eric Axel Franzon Worldcat.org • A project of the OCLC
  105. 105. ©2015 Eric Axel Franzon Vocabulary Combination “in the wild”
  106. 106. ©2015 Eric Axel Franzon Vocabulary Combination “in the wild”
  107. 107. ©2015 Eric Axel Franzon The Technologies of SemWeb • Data • Schemas • Query Language
  108. 108. ©2015 Eric Axel Franzon The query language SPARQL Protocol And RDF Query Language SPARQL
  109. 109. ©2015 Eric Axel Franzon SPARQL allows us to: • Pull values from structured & semi-structured data • Explore data by querying unknown relationships • Perform complex joins of disparate databases in a single, simple query • Transform RDF data from one vocabulary to another --Lee Feigenbaum, Cambridge Semantics
  110. 110. ©2015 Eric Axel Franzon Eric
  111. 111. ©2015 Eric Axel Franzon <hasDepiction> Eric
  112. 112. ©2015 Eric Axel Franzon <hasLicense> <hasDepiction> Eric
  113. 113. ©2015 Eric Axel Franzon <hasLicense> <hasDepiction> <likes> Eric
  114. 114. ©2015 Eric Axel Franzon <hasLicense> <hasDepiction> <likes> <likes>
  115. 115. ©2015 Eric Axel Franzon <hasLicense> <hasDepiction> <likes> <likes> <likes> Eric
  116. 116. ©2015 Eric Axel Franzon Chicago, Illinois On the shores of Lake Michigan, Chicago is one of the major… <hasLicense> <wrote> <hasDepiction> <likes> <likes> <likes> Eric Bob
  117. 117. ©2015 Eric Axel Franzon Chicago, Illinois On the shores of Lake Michigan, Chicago is one of the major… <hasLicense> <wrote> <isAbout> <hasDepiction> <likes> <likes> <likes> Eric Bob
  118. 118. ©2015 Eric Axel Franzon Chicago, Illinois On the shores of Lake Michigan, Chicago is one of the major… <hasLicense> <wrote> <isAbout> <livedIn> <hasDepiction> <likes> <likes> <likes> Eric Bob
  119. 119. ©2015 Eric Axel Franzon Chicago, Illinois On the shores of Lake Michigan, Chicago is one of the major… <hasLicense> <hasLicense> <wrote> <isAbout> <livedIn> <hasDepiction> <likes> <likes> <likes> Eric Bob
  120. 120. ©2015 Eric Axel Franzon What can we ask of a system like this?
  121. 121. ©2015 Eric Axel Franzon Chicago, Illinois On the shores of Lake Michigan, Chicago is one of the major… <hasLicense> <hasLicense> <wrote> <isAbout> <livedIn> <hasDepiction> <likes> <likes> <likes> Bob Eric
  122. 122. ©2015 Eric Axel Franzon Chicago, Illinois On the shores of Lake Michigan, Chicago is one of the major… <hasLicense> <hasLicense> <wrote> <isAbout> <livedIn> <hasDepiction> <likes> <likes> <likes> What does Eric Like? Bob Eric
  123. 123. ©2015 Eric Axel Franzon Chicago, Illinois On the shores of Lake Michigan, Chicago is one of the major… <hasLicense> <hasLicense> <wrote> <isAbout> <livedIn> <hasDepiction> <likes> <likes> <likes> What has a Creative Commons License? Bob Eric
  124. 124. ©2015 Eric Axel Franzon Chicago, Illinois On the shores of Lake Michigan, Chicago is one of the major… <hasLicense> <hasLicense> <wrote> <isAbout> <livedIn> <hasDepiction> <likes> <likes> <likes> What license does THIS document have? Bob Eric
  125. 125. ©2015 Eric Axel Franzon Chicago, Illinois On the shores of Lake Michigan, Chicago is one of the major… <hasLicense> <hasLicense> <wrote> <isAbout> <livedIn> <hasDepiction> <likes> <likes> <likes> What is liked by anyone who has lived somewhere that is the subject of a document Bob has written? Bob Eric
  126. 126. ©2015 Eric Axel Franzon SPARQL Queries
  127. 127. ©2015 Eric Axel Franzon SPARQL Example #1 (specific endpoint – dbPedia) Artists/Albums produced by Pharrell PREFIX d: <http://dbpedia.org/ontology/> SELECT ?artistName ?albumName WHERE { ?album d:producer :Pharrell_Williams . ?album d:musicalArtist ?artist . ?album rdfs:label ?albumName . ?artist rdfs:label ?artistName . FILTER ( lang(?artistName) = "en" ) FILTER (lang(?albumName) = "en" ) }
  128. 128. ©2015 Eric Axel Franzon SPARQL Example #1
  129. 129. ©2015 Eric Axel Franzon SPARQL Example #1
  130. 130. ©2015 Eric Axel Franzon
  131. 131. ©2015 Eric Axel Franzon SPARQL Example #2 (specific endpoint – dbPedia) Musical artists who were born in or have a hometown in Ireland and the acts they performed with.
  132. 132. ©2015 Eric Axel Franzon SPARQL Example #2 (specific endpoint – dbPedia) PREFIX dbo: <http://dbpedia.org/ontology/> SELECT DISTINCT ?name ?person ?artist WHERE { ?person foaf:name ?name . ?person rdf:type <http://dbpedia.org/ontology/MusicalArtist> . ?person <http://dbpedia.org/ontology/associatedMusicalArtist> ?artist . { ?person dbo:hometown <http://dbpedia.org/resource/Republic_of_Ireland> . } UNION { ?person dbo:birthPlace <http://dbpedia.org/resource/Republic_of_Ireland> . } } ORDER BY ?name
  133. 133. ©2015 Eric Axel Franzon SPARQL Example #2
  134. 134. ©2015 Eric Axel Franzon SPARQL Example #2 A major retailer ran this query… associated it with the catalog of albums it sells… and delivered a set of recommended purchases for St. Patrick’s Day!
  135. 135. ©2015 Eric Axel Franzon
  136. 136. ©2015 Eric Axel Franzon
  137. 137. ©2015 Eric Axel Franzon
  138. 138. ©2015 Eric Axel Franzon SPARQL Query #3 • Show me all landlocked countries • With populations > 50,000 • Display the country names in English • Eliminate duplicates
  139. 139. ©2015 Eric Axel Franzon SPARQL Query #3 • Show me all landlocked countries • With populations > 50,000 • Display the country names in English • Eliminate duplicates PREFIX type: <http://dbpedia.org/class/yago/> PREFIX prop: <http://dbpedia.org/property/> SELECT ?country_name ?population WHERE { ?country a type:LandlockedCountries ; rdfs:label ?country_name ; prop:populationEstimate ?population . FILTER (?population > 15000000 && langMatches(lang(?country_name), "EN")) . } ORDER BY DESC(?population)
  140. 140. ©2015 Eric Axel Franzon SPARQL Query #3 Results
  141. 141. ©2015 Eric Axel Franzon SPARQL Query #3 • Show me all landlocked countries • With populations > 50,000 • Display the country names in English • Eliminate duplicates PREFIX type: <http://dbpedia.org/class/yago/> PREFIX prop: <http://dbpedia.org/property/> SELECT ?country_name ?population WHERE { ?country a type:LandlockedCountries ; rdfs:label ?country_name ; prop:populationEstimate ?population . FILTER (?population > 15000000 && langMatches(lang(?country_name), "RU")) . } ORDER BY DESC(?population)
  142. 142. ©2015 Eric Axel Franzon SPARQL Query #3 Results
  143. 143. ©2015 Eric Axel Franzon • 8 KB text file with the .rdf extension • Hosted on my website • Information on me, my interests, and people I know My FOAF Profile
  144. 144. ©2015 Eric Axel Franzon SPARQL Example #4 (generic endpoint) FOAF (some people that Eric Franzon knows) PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?name FROM <http://ericaxel.com/eric.rdf> WHERE { ?knower foaf:knows ?known . ?known foaf:name ?name . }
  145. 145. ©2015 Eric Axel Franzon SPARQL Example #4
  146. 146. ©2015 Eric Axel Franzon Example #4 - Results
  147. 147. ©2015 Eric Axel Franzon 2 Disparate Data Sources: 2 FOAF Profiles
  148. 148. ©2015 Eric Axel Franzon SPARQL Example #5 Querying two FOAF Profiles PREFIX foaf: <http://xmlns.com/foaf/0.1/> PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> SELECT ?name FROM <http://ericaxel.com/eric.rdf> FROM <http://bosatsu.net/foaf/brian.rdf> WHERE { ?x rdf:type foaf:Person . ?x foaf:name ?name . }
  149. 149. ©2015 Eric Axel Franzon Where’s the Data? What’s The Question?
  150. 150. ©2015 Eric Axel Franzon Example #5 - Results
  151. 151. ©2015 Eric Axel Franzon Another Benefit of querying Linked Data… Data link to other data! SPARQL Example #6
  152. 152. ©2015 Eric Axel Franzon 1. Find these pieces of information: • Episode number • Airdate • Guest star • Chalkboard gag • Couch gag 2. Order them by Episode number SPARQL Example #6
  153. 153. ©2015 Eric Axel Franzon SPARQL Example #6 Bart Simpson's Linked Data (DBPedia) SELECT ?epnum ?airdate ?guest_star ?chalkboard_gag ?couch_gag WHERE { ?s dbpedia2:airdate ?airdate . ?s dbpedia2:blackboard ?chalkboard_gag . ?s dbpedia2:guestStar ?guest_star . ?s dbpedia2:episodeNo ?epnum . ?s dbpedia2:couchGag ?couch_gag . } order by ?epnum
  154. 154. ©2015 Eric Axel Franzon SPARQL Example #6
  155. 155. ©2015 Eric Axel Franzon Example #6 - Results
  156. 156. ©2015 Eric Axel Franzon Following the Trail…
  157. 157. ©2015 Eric Axel Franzon
  158. 158. ©2015 Eric Axel Franzon One More Thing…
  159. 159. ©2015 Eric Axel Franzon A little bit can be powerful!
  160. 160. ©2015 Eric Axel Franzon Questions? Operators are standing by. THANK YOU! eric@semanticfuse.com @EricAxel http://linkedin.com/in/ericfranzon https://plus.google.com/+EricFranzon
  161. 161. ©2015 Eric Axel Franzon • Semantic Markup Infusion • Semantic Data Fusion • Semantic SEO • Semantic Roadmap/Audit • Semantic Streamlining of Product Feeds/Catalogs • Semantic Consulting/Training • Semantic Interest Graph Generation
  162. 162. ©2015 Eric Axel Franzon Resources https://flic.kr/p/6krdsM https://flic.kr/p/p9jiDK https://flic.kr/p/3q8afL https://flic.kr/p/brJs4G https://flic.kr/p/78rsTc https://flic.kr/p/bpSeR2 http://www.flickr.com/photos/dawnmanser/3532853278/ http://www.flickr.com/photos/artolog/3983764041/ http://www.flickr.com/photos/97964364@N00/59780745/ http://www.flickr.com/photos/starwarsblog/ http://aldobucchi.com http://www.addletters.com/pictures/bart-simpson-generator/3024046.htm http://richard.cyganiak.de/2007/10/lod/

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