The Next Web of Linked Data -- University of St Thomas SEIS 708

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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.

Tecnología Educación

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”

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

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

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 .

“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

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 Search
Yahoo! Related Entities

Practical Applications in Search
Yandex Islands

Practical Applications in Search
Google Knowledge Graph
Additional content driven
by schema.org derived
data

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

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The Next Web of Linked Data -- University of St Thomas SEIS 708

1. The Next Web of Linked Data @jaymyers SEIS 708

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. Original Web • Collections of documents • Users “surfed” • Created mostly for human consumption

4. Web of Today • Trillions of web pages • 5 billion web pages change every day • 1000x more web pages on the “deep web”

5. Machine-driven Web

6. Every day we create 2.5 quintillion bytes of data (equivalent to 3.4 billion HD movies)

7. Linked Data “A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities” - TBL

8. 2009

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 .

12. dbpedia Machine readable data

13. “Show me music artists whose hometown is Minneapolis”

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

15. 2010

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)

20. Practical Applications in Search Yahoo! Related Entities

21. Practical Applications in Search Yandex Islands

22. Practical Applications in Search Google Knowledge Graph Additional content driven by schema.org derived data

23. Other Applications Pinterest Rich Pins

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

The Next Web of Linked Data -- University of St Thomas SEIS 708

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