The Next Web of Linked Data
@jaymyers
SEIS 708
• 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
Original Web
• Collections of documents• Users “surfed”• Created mostly for human consumption
Web of Today
• Trillions of web pages• 5 billion web pages change every day• 1000x more web pages on the “deep web”
Machine-driven Web
Every day we create 2.5 quintillion bytes of data(equivalent to 3.4 billion HD movies)
Linked Data
“A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities” - TBL
2009
Five Star Open Data
Make your stuff available on the webMake it available as structured dataUse non-proprietary formatsUse URIs to denote things, so people can link to your dataLink your data to other data
RDF Ontology: FOAF
<jaymyers> <foaf:knows> <arun>
<arun> <foaf:knows> <billybob>
A machine could infer that Jay might like to know Billy Bob
<billybob> <foaf:interest> “Arduino”
<jaymyers> <foaf:interest> “Arduino”
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 .
dbpedia
Machine readable
data
“Show me music artists whose hometown is Minneapolis”
Hydra and 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
2010
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
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
Value Prop
“Give us your data in a machine-readable format and we’ll make
your stuff more attractive in search results”
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)
Practical Applications in SearchYahoo! Related Entities
Practical Applications in SearchYandex Islands
Practical Applications in SearchGoogle Knowledge Graph
Additional content driven by schema.org derived data
Other ApplicationsPinterest Rich Pins
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…
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