The document discusses the evolution of the web from human-centric to machine-driven. It describes how linked open data and semantic technologies like RDF, schema.org, and JSON-LD are creating a web of data that is meaningful to computers. This machine-driven web unleashes new possibilities by enabling inferences across datasets that allow machines to discover and explore new knowledge. Many large companies and governments have adopted these technologies to publish structured data and power new applications like knowledge graphs and rich search results.
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
9. 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
10. 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”
11. 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 .
14. 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
16. 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
17. 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
18. Value Prop
“Give us your data in a machine-
readable format and we’ll make
your stuff more attractive in search
results”
19. 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)
24. 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…
25. 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