Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Contextual Computing - Knowledge Graphs & Web of Entities

2,101 views

Published on

Presentation to the Smart Data 2017 Conference in San Francisco Bay January 31st 2017

Published in: Data & Analytics
  • Could you use an extra $1750 a week? I'm guessing you could right? If you would like to see how you could make this type of money, right from the comfort of your own home, you absolutely need to check out this short free video. ♥♥♥ http://t.cn/AisJWzdm
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • where is the video presentation of this? hard to follow just seeing slides
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • Hello! High Quality And Affordable Essays For You. Starting at $4.99 per page - Check our website! https://vk.cc/82gJD2
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here

Contextual Computing - Knowledge Graphs & Web of Entities

  1. 1. Contextual Computing:
 Knowledge Graphs The Web of Entities Richard Wallis Evangelist and Founder Data Liberate richard.wallis@dataliberate.com @rjw SmartData 2017 San Francisco Bay January 31st 2017
  2. 2. richard.wallis@dataliberate.com — @rjw
  3. 3. Independent Consultant, Evangelist & Founder richard.wallis@dataliberate.com — @rjw
  4. 4. Independent Consultant, Evangelist & Founder richard.wallis@dataliberate.com — @rjw 25+ Years – Library systems technology 10+ Years – Semantic Web & Linked Data
  5. 5. Independent Consultant, Evangelist & Founder W3C Community Groups: • Schema Bib Extend (Chair) • Schema.org for bibliographic data • bib.schema.org • Schema Architypes (Chair) • Financial Industry Business Ontology – fibo.schema.org • Tourism Structured Web Data (Co-Chair) • Schema Course Extension richard.wallis@dataliberate.com — @rjw 25+ Years – Library systems technology 10+ Years – Semantic Web & Linked Data
  6. 6. Independent Consultant, Evangelist & Founder Working With: • Google – Schema.org vocabulary, site, extensions 
 documentation and community W3C Community Groups: • Schema Bib Extend (Chair) • Schema.org for bibliographic data • bib.schema.org • Schema Architypes (Chair) • Financial Industry Business Ontology – fibo.schema.org • Tourism Structured Web Data (Co-Chair) • Schema Course Extension richard.wallis@dataliberate.com — @rjw 25+ Years – Library systems technology 10+ Years – Semantic Web & Linked Data
  7. 7. Independent Consultant, Evangelist & Founder Working With: • Google – Schema.org vocabulary, site, extensions 
 documentation and community • OCLC – Global library cooperative W3C Community Groups: • Schema Bib Extend (Chair) • Schema.org for bibliographic data • bib.schema.org • Schema Architypes (Chair) • Financial Industry Business Ontology – fibo.schema.org • Tourism Structured Web Data (Co-Chair) • Schema Course Extension richard.wallis@dataliberate.com — @rjw 25+ Years – Library systems technology 10+ Years – Semantic Web & Linked Data
  8. 8. Independent Consultant, Evangelist & Founder Working With: • Google – Schema.org vocabulary, site, extensions 
 documentation and community • OCLC – Global library cooperative • FIBO – Financial Industry Business Ontology W3C Community Groups: • Schema Bib Extend (Chair) • Schema.org for bibliographic data • bib.schema.org • Schema Architypes (Chair) • Financial Industry Business Ontology – fibo.schema.org • Tourism Structured Web Data (Co-Chair) • Schema Course Extension richard.wallis@dataliberate.com — @rjw 25+ Years – Library systems technology 10+ Years – Semantic Web & Linked Data
  9. 9. Independent Consultant, Evangelist & Founder Working With: • Google – Schema.org vocabulary, site, extensions 
 documentation and community • OCLC – Global library cooperative • FIBO – Financial Industry Business Ontology • Various Clients – Implementing/understanding Schema.org Europeana – NLB Singapore W3C Community Groups: • Schema Bib Extend (Chair) • Schema.org for bibliographic data • bib.schema.org • Schema Architypes (Chair) • Financial Industry Business Ontology – fibo.schema.org • Tourism Structured Web Data (Co-Chair) • Schema Course Extension richard.wallis@dataliberate.com — @rjw 25+ Years – Library systems technology 10+ Years – Semantic Web & Linked Data
  10. 10. Image: http://enable5.com/
  11. 11. Image: http://enable5.com/
  12. 12. Image: http://enable5.com/
  13. 13. Image: http://enable5.com/
  14. 14. Image: http://enable5.com/
  15. 15. Image: http://enable5.com/
  16. 16. Image: http://enable5.com/
  17. 17. Image: http://enable5.com/
  18. 18. Image: http://enable5.com/
  19. 19. Image: http://enable5.com/ contextual elements such as meaning, syntax, time, location, appropriate domain, regulations, user’s profile, process, task and goal.
  20. 20. Image: http://enable5.com/ contextual elements such as meaning, syntax, time, location, appropriate domain, regulations, user’s profile, process, task and goal. contextual elements such as meaning, syntax, time, location, appropriate domain, regulations, user’s profile, process, task and goal.
  21. 21. Image: http://enable5.com/
  22. 22. Contextual Computing:
 Knowledge Graphs The Web of Entities
  23. 23. Contextual Computing:
 Knowledge Graphs The Web of Entities
  24. 24. Contextual Computing:
 Knowledge Graphs The Web of Entities Context
  25. 25. Contextual Computing:
 Knowledge Graphs The Web of Entities
  26. 26. Context! Context in A Web of Entities
  27. 27. The Web Conceived Tim Berners-Lee
  28. 28. The Web Conceived ● 1989● March Tim Berners-Lee
  29. 29. The Web Conceived ● 1989● March Tim Berners-Lee Vague but exciting …
  30. 30. ● 1999●
  31. 31. ● 1999● Tim Berners-Lee, 1999 “I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘intelligent agents’ people have touted for ages will finally materialize”
  32. 32. ● 1999● Tim Berners-Lee, 1999 “I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘intelligent agents’ people have touted for ages will finally materialize”
  33. 33. ● 1999● Tim Berners-Lee, 1999 “I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘intelligent agents’ people have touted for ages will finally materialize” Intelligent Agents …
  34. 34. Semantic Web Arrives
  35. 35. Semantic Web Arrives ● 2001 ● MAY A vision of the future …
  36. 36. “A Linked Data Web” – Introducing Linked Data
  37. 37. “A Linked Data Web” – Introducing Linked Data ● 2009 Feb Linked Data
  38. 38. The Infamous 
 Open Linked Data Cloud
  39. 39. Linked Open Data The Infamous 
 Open Linked Data Cloud Impressive!
  40. 40. Linked Open Data The Infamous 
 Open Linked Data Cloud Impressive! • Raw RDF • Many Vocabs
  41. 41. Linked Open Data The Infamous 
 Open Linked Data Cloud Impressive! • Raw RDF • Many Vocabs
  42. 42. Linked Open Data The Infamous 
 Open Linked Data Cloud Impressive! • Raw RDF • Many Vocabs • SPARQL
  43. 43. Linked Open Data The Infamous 
 Open Linked Data Cloud Impressive! • Raw RDF • Many Vocabs • SPARQL
  44. 44. Linked Open Data The Infamous 
 Open Linked Data Cloud Impressive! But Useful? • Raw RDF • Many Vocabs • SPARQL
  45. 45. 2 ● 2011 ● June Introducing Schema.org
  46. 46. 2 ● 2011 ● June Introducing Schema.org
  47. 47. 2 ● 2011 ● June Introducing Schema.org
  48. 48. 2 ● 2011 ● June Introducing Schema.org
  49. 49. Knowledge Graph
  50. 50. Knowledge Graph 16 ● 2012 ● May Google Knowledge Graph
  51. 51. Knowledge Graph 16 ● 2012 ● May Google Knowledge Graph
  52. 52. Knowledge Graph 16 ● 2012 ● May Google Knowledge Graph
  53. 53. Google Knowledge Graph
  54. 54. Google Knowledge Graph
  55. 55. Google Knowledge Graph
  56. 56. Google Knowledge Graph
  57. 57. Knowledge Graph Related Entities in a Graph
  58. 58. Knowledge Graph Bart Simpson Related Entities in a Graph
  59. 59. Knowledge Graph Bart Simpson Nancy Cartwright Played By Related Entities in a Graph
  60. 60. Knowledge Graph Bart Simpson Nancy Cartwright Dayton Ohio Played By Born In Related Entities in a Graph
  61. 61. Knowledge Graph Bart Simpson Nancy Cartwright Dayton Ohio Dayton Aviation
 Heritage National Park Played By Born In Place of Interest Related Entities in a Graph
  62. 62. Knowledge Graph
  63. 63. Knowledge Graph Sources for the Graph
  64. 64. Knowledge Graph Sources for the Graph
  65. 65. Knowledge Graph Sources for the Graph
  66. 66. Knowledge Graph Sources for the Graph
  67. 67. Knowledge Graph Sources for the Graph
  68. 68. Knowledge Graph Sources for the Graph
  69. 69. Knowledge Graph Powered by the Graph
  70. 70. Knowledge Graph Powered by the Graph Knowledge Panel
  71. 71. Knowledge Graph Powered by the Graph Knowledge Panel Info Box
  72. 72. Knowledge Graph Powered by the Graph Knowledge Panel Info Box Answer Box
  73. 73. Knowledge Graph Powered by the Graph Knowledge Panel Info Box Answer Box Rich Snippets
  74. 74. Knowledge Graph Powered by the Graph Knowledge Panel Info Box Answer Box Rich Snippets
  75. 75. Using Schema.org
  76. 76. Using Schema.org •Data embedded in website html -Microdata / RDFa / JSON-LD
  77. 77. Using Schema.org •Data embedded in website html -Microdata / RDFa / JSON-LD •Harvested during normal web crawls
  78. 78. Using Schema.org •Data embedded in website html -Microdata / RDFa / JSON-LD •Harvested during normal web crawls •Under control of the [site] publisher
  79. 79. Schema.org today
  80. 80. •In use on over 12 million domains •Broad core vocabulary: Schema.org today
  81. 81. •In use on over 12 million domains •Broad core vocabulary: -Types: 571 Properties: 832 Values: 114 •Extensions published: Schema.org today
  82. 82. •In use on over 12 million domains •Broad core vocabulary: -Types: 571 Properties: 832 Values: 114 •Extensions published: - auto.schema.org - bib.schema.org - health-lifesci.schema.org Schema.org today
  83. 83. Schema.org
  84. 84. Schema.org 12+ Million Web Sites
  85. 85. Schema.org 12+ Million Web Sites Found On30% Pages* * In a 10 billion page sample - 2015
  86. 86. Schema.org A de facto vocabulary for structured data on the web12+ Million Web Sites Found On30% Pages* * In a 10 billion page sample - 2015
  87. 87. Schema.org A de facto vocabulary for structured data on the web So, what does it look like …. 12+ Million Web Sites Found On30% Pages* * In a 10 billion page sample - 2015
  88. 88. A Bibliographic Example WorldCat.org
  89. 89. A Bibliographic Example WorldCat.org
  90. 90. A Banking Example Banc of California
  91. 91. A Banking Example Banc of California
  92. 92. A Banking Example Banc of California
  93. 93. Who is doing it?
  94. 94. Who is doing it? Common Crawl - Structured Data
  95. 95. Who is doing it? Common Crawl - Structured Data
  96. 96. Who is doing it?Who is doing it? Common Crawl - Structured Data
  97. 97. Who is doing it?Who is doing it? About ⅓ of Web (about ⅙ domains) Common Crawl - Structured Data
  98. 98. Why?

  99. 99. Why?
 Our world is Changing!
  100. 100. Why?
 Our world is Changing!
  101. 101. Why?
 Our world is Changing!
  102. 102. Why?
 Our world is Changing!
  103. 103. Why?
 Our world is Changing!
  104. 104. Why?
 Our world is Changing!
  105. 105. Why?
 Our world is Changing!
  106. 106. How To Participate https://www.genua.de Implementing Schema.org
  107. 107. How To Participate https://www.genua.de A strategy for sharing data Implementing Schema.org
  108. 108. How To Participate https://www.genua.de A strategy for sharing data • Identify your data entities • Map to Schema.org • Look for external links • Add markup to pages • Markup your organisation • Help the crawlers • Monitor effects • Continuously improve Implementing Schema.org
  109. 109. How To Participate https://www.genua.de A strategy for sharing data • Identify your data entities • Map to Schema.org • Look for external links • Add markup to pages • Markup your organisation • Help the crawlers • Monitor effects • Continuously improve Make the Search Engines Aware of Your Entities Implementing Schema.org
  110. 110. A Structured Web
 Data Revolution Structured Data Powering Discovery
  111. 111. A Structured Web
 Data Revolution Our Data Enriching Knowledge Graphs Structured Data Powering Discovery
  112. 112. A Structured Web
 Data Revolution Our Data Enriching Knowledge Graphs Rich
 Snippets Knowledge
 Panels Semantic
 Search Answer
 BoxesInfo
 Boxes Conversational
 Search Rich
 Cards Semantic
 SEO Enhanced
 AnalyticsRankBrain Structured Data Powering Discovery Knowledge Graphs Enriching our Online World
  113. 113. A Structured Web
 Data Revolution Our Data Enriching Knowledge Graphs Rich
 Snippets Knowledge
 Panels Semantic
 Search Answer
 BoxesInfo
 Boxes Conversational
 Search Rich
 Cards Semantic
 SEO Enhanced
 AnalyticsRankBrain Structured Data Powering Discovery Knowledge Graphs Enriching our Online World
  114. 114. Structured Data - Global Context Structured Data Web
  115. 115. Structured Data - Global Context Structured Data Web A Global Graph of Related Entities
  116. 116. Structured Data - Global Context Structured Data Web A Global Graph of Related Entities Providing Context on a Global Scale
  117. 117. Structured Data - Global Context Structured Data Web A Global Graph of Related Entities Providing Context on a Global Scale contextual elements such as meaning, syntax, time, location, appropriate domain, regulations, user’s profile, process, task and goal. Cognitive/ Contextual Computing
 needs
  118. 118. Cognitive/Contextual Computing
  119. 119. Cognitive/Contextual Computing Is evolving from a world constrained by
  120. 120. Cognitive/Contextual Computing Is evolving from a world constrained by Local Context Cognitive Computing - Local Context
  121. 121. Cognitive/Contextual Computing Is evolving from a world constrained by Local Context •Domain •Local Familiarity •Developer experiences •Local data models •Industry focussed
 vocabularies Cognitive Computing - Local Context
  122. 122. Cognitive/Contextual Computing
  123. 123. Is emerging into a world enabled by Global Context Cognitive Computing - Global Context Cognitive/Contextual Computing
  124. 124. Is emerging into a world enabled by Global Context •Cross Domain •Broad Familiarity •Many Developers •Flexible data model •De facto vocabulary •Knowledge Graphs •Millions* of Entities Cognitive Computing - Global Context Cognitive/Contextual Computing *12+ Million Sites
  125. 125. For Cognitive/Contextual Computing Image: http://enable5.com/
  126. 126. For Cognitive/Contextual Computing Global and y Image: http://enable5.com/
  127. 127. For Cognitive/Contextual Computing Global and y Image: http://enable5.com/ Delivering on one revolution …
  128. 128. For Cognitive/Contextual Computing Global and y Image: http://enable5.com/ Delivering on one revolution … Laying foundations for another
  129. 129. For Cognitive/Contextual Computing Global and y Image: http://enable5.com/ Delivering on one revolution … Laying foundations for another Building a Contextual Web of Entities Schema.org - Building Global Context
  130. 130. Contextual Computing: Richard Wallis Evangelist and Founder Data Liberate richard.wallis@dataliberate.com @rjw Knowledge Graphs
 The Web of Entities SmartData 2017 San Francisco Bay January 31st 2017
  131. 131. Contextual Computing: Richard Wallis Evangelist and Founder Data Liberate richard.wallis@dataliberate.com @rjw Cognitive / Knowledge Graphs
 The Web of Entities SmartData 2017 San Francisco Bay January 31st 2017
  132. 132. Contextual Computing: Richard Wallis Evangelist and Founder Data Liberate richard.wallis@dataliberate.com @rjw The Global Web of Entities Helped by Knowledge Graphs Cognitive / Enabled by SmartData 2017 San Francisco Bay January 31st 2017
  133. 133. Contextual Computing: Richard Wallis Evangelist and Founder Data Liberate richard.wallis@dataliberate.com @rjw The Global Web of Entities Helped by Knowledge Graphs Cognitive / Enabled by *Assisted by * SmartData 2017 San Francisco Bay January 31st 2017

×