Minnebar9 -- The Next Web of Linked Data


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Next Web of Linked Data at Minnebar9. I chat about open data, "raw data now", JSON-LD and Hydra, and schema.org. A basic high-level overview of what is going on in the open data and semantic web world.

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Minnebar9 -- The Next Web of Linked Data

  1. 1. The Next Web of Linked Data @jaymyers MinneBar 9
  2. 2. • Early adopter • Semantic Web, Linked & Open data enthusiast • Speaker • BBY’er * * thoughts in this presentation are my own and may not be shared Best Buy
  3. 3. Original Web • Collections of documents • Users “surfed” • Created mostly for human consumption
  4. 4. Web of Today • Trillions of web pages • 5 billion web pages change every day • 1000x more web pages on the “deep web” • Over 60% of website visitors are machines
  5. 5. Every day we create 2.5 quintillion bytes of data (equivalent to 3.4 billion HD movies)
  6. 6. Linked Data “A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities” - TBL
  7. 7. 2009
  8. 8. Five Star Open Data Make your stuff available on the web Make it available as structured data Use non-proprietary formats Use URIs to denote things, so people can link to your data Link your data to other data
  9. 9. RDF Ontology: FOAF <jaymyers> <foaf:knows> <kristenwomack> <kristenwomack> <foaf:knows> <billybob> A machine can infer that Jay might like to know Billy Bob
  10. 10. RDF Ontology: GoodRelations <wafflemaker> a gr:ProductOrService ; <wafflemaker> <gr:category> ‘Waffle_Makers’ “Show me the names of all ‘lightweight’ waffle makers” <wafflemaker> <gr:name> ‘Euro Cuisine 8" Heart-Shape Waffle Maker’ <wafflemaker> <gr:weight> ”2.0"^^xsd:float .
  11. 11. dbpedia Machine readable data
  12. 12. “Show me music artists whose hometown is Minneapolis”
  13. 13. Hydra & JSON-LD • Machine-readable vocabulary that can be used to describe web APIs • Puts the information back in APIs by defining small contract that sets JSON structures and URLs • Creates new breed of web APIs (powered by Linked Data) using decentralized, reusable contracts
  14. 14. 2010
  15. 15. schema.org • Common vocabularies that search engines can understand • Lower the bar for webmasters to publish linked data on the web in their HTML • Improve user experience through data
  16. 16. Goals • Create a web for both humans and machines • Entice webmasters to make metadata available through web standards and structured HTML • Gain access to the meaning of web sites • Establish relationships between data that allow for exploration and discovery
  17. 17. Value Prop “Give us your data in a machine- readable format and we’ll make your stuff more attractive in search results”
  18. 18. Looks Like We’ve Got Something Here! • 15% of all sites contain schema.org markup • Many major sites • Adoption by content systems like Drupal and Wordpress • Around 1200 object types and growing (people, places, products, etc)
  19. 19. Practical Applications in Search Yahoo! Related Entities
  20. 20. Practical Applications in Search Yandex Islands
  21. 21. Practical Applications in Search Google Knowledge Graph Additional content driven by schema.org derived data
  22. 22. Other Applications Pinterest Rich Pins
  23. 23. Time To Get On Board! • US, UK gov’t • BBC • Flickr • Google • Yahoo! • Bing • Last.fm • Facebook • New York Times • Sears • IBM • O’reilly • Volkswagen • IMDB • Elsevier • Fujitsu • Alchemy API • Many more…
  24. 24. Thank You! Guha, Ramanathan V. “Light at the End of the Tunnel.” 12th International Semantic Web Conference (ISWC), Sydney, NSW, Australia. 23 October 2013. Keynote Address. Hepp, Martin H., Dr. "Semantic SEO." GoodRelations: The Professional Web Vocabulary for E-Commerce. Dr. Martin Hepp. Web. 17 Mar. 2014. Berners-Lee, Tim. Tim Berners-Lee: The next web. Feb 2009. Video File. http://www.ted.com. Web. 17 Mar 2014. <http://www.ted.com/talks/tim_berners_lee_on_the_next_web >. Condliffe, Jamie ”Over 60 Percent of Internet Traffic Driven by Bots” Gizmodo. Web. 13 Dec. 2013. Credits and Resources