Using Semantics to Enhance Content Publishing
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Integrating the cloud into content. Web2.0 Expo NY 2009 Workshop

Integrating the cloud into content. Web2.0 Expo NY 2009 Workshop

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  • 1. Integrating the Cloud into Content Using Semantics to Enhance Content Publishing Jamie Taylor http://semprog.com/presentations/web20ny
  • 2. What do y'all mean "Semantics"
  • 3. critique misfortune bad luck occurrence roast KNOCK sound zing knocking zizz vroom bang belt bash bump rap whack blow
  • 4. critique misfortune bad luck occurrence roast LJOMF sound zing knocking zizz vroom bang belt bash bump rap whack blow
  • 5. IBM
  • 6. 1 New Orchard Road Publicaly Listed Armonk, New York Company rs Le 0000051143 arte ga lS NYSE:IBM dqu tru ol Hea ctu 1889 b K ym CI re Dat S e Fou e r nde Ti ck d Thomas Watson Founders Sam Palmisano IBM CEO SIC O pe 3571:Electronic ra IC t Soft es Computers NA diari in g In war co m i e De Subs e 334111:Electronic 17,604,000,000 Computer Manufacturing velo ped USD 2006 Cognos Cross Worlds SANSF, ViaVoice Lotus Notes
  • 7. 1 New Orchard Road Publicaly Listed Armonk, New York Company rs Le 0000051143 arte ga lS NYSE:IBM dqu tru ol Hea ctu 1889 b K ym CI re Dat S e Fou e r nde Ti ck d Thomas Watson Founders Sam Palmisano CEO SIC O pe 3571:Electronic ra IC t Soft es Computers NA diari in g In war co m i e De Subs e 334111:Electronic 17,604,000,000 Computer Manufacturing velo ped USD 2006 Cognos Cross Worlds SANSF, ViaVoice Lotus Notes
  • 8. http://www.flickr.com/photos/pacroon/ http://www.flickr.com/photos/soldiersmediacenter/
  • 9. PageRank tm
  • 10. 1 New Orchard Road Publicaly Listed Armonk, New York Company 0000051143 NYSE:IBM 1889 Thomas Watson Sam Palmisano 3571:Electronic Computers 334111:Electronic 17,604,000,000 Computer Manufacturing USD 2006 Cognos Cross Worlds SANSF, ViaVoice Lotus Notes
  • 11. Earlier this year, the AP slashed prices to try to hold on to subscribers. That's not the answer, says Jeff Jarvis, journalism professor at City University of New York. JEFF JARVIS: The fundamentals of the media economy are changing, from a content economy to a link-based economy. Jarvis says the AP needs to become the broker for those links, like helping the Baltimore Sun link to a story about GM from the Detroit Free Press.
  • 12. Jarvis resorts to the concept of a "gift economy" to explain the link economy http://www.flickr.com/photos/pagedooley/
  • 13. I am a behavioral economist. Gift economics are frequently used as explanations for what we don't understand
  • 14. Worse I am a Behaviorist Only talk about what you can observe
  • 15. Semantics Process of communicating enough meaning to result in an action
  • 16. Link Economy • Enriching links focuses meaning • Improves "findability" (SEO) • Increased usability • Better ad selection
  • 17. Link Economy At the end of this talk - you should be able to say how semantics benefits each of these groups • Semantics Benefit • Site owners • Site users • Developers • You
  • 18. Wish it were real
  • 19. Might be real
  • 20. Is real, but don't believe it
  • 21. Is very useful Build Flexible Applications with Graph Data
  • 22. Not Your Typical Semantic Web Talk
  • 23. The W3C Layer Cake The Cake taken from http://www.w3.org/2007/Talks/0130-sb-W3CTechSemWeb/layerCake-4.png
  • 24. AI Agents http://www.flickr.com/photos/matthewtownsend/
  • 25. Ontologies
  • 26. RDF Serialization Formats <http://rdf.freebase.com/ns/guid.9202a8c04000641f8000000005b7ab1a> <http://www.w3.org/1999/02/22-rdf-syntax- ns#type> <http://rdf.freebase.com/ns/business.employment_tenure>. <http://rdf.freebase.com/ns/guid.9202a8c04000641f8000000005b7ab1a> <http://rdf.freebase.com/ns/ business.employment_tenure.company> <http://rdf.freebase.com/ns/en.determine_software>. <http://rdf.freebase.com/ns/guid.9202a8c04000641f8000000007e53e16> <http://rdf.freebase.com/ns/ education.education.institution> <http://rdf.freebase.com/ns/en.mounds_view_high_school>.<http://rdf.freebase.com/ns/ guid.9202a8c04000641f8000000007e53e16> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http:// rdf.freebase.com/ns/education.education>. <http://rdf.freebase.com/ns/guid.9202a8c04000641f8000000007e53e16> <http://rdf.freebase.com/ns/ education.education.student> <http://rdf.freebase.com/ns/en.jamie_taylor>. <http://rdf.freebase.com/ns/en.jamie_taylor> <http://rdf.freebase.com/ns/business.company_founder.companies_founded> <http://rdf.freebase.com/ns/en.mobius_net>. <http://rdf.freebase.com/ns/en.jamie_taylor> <http://creativecommons.org/ns#attributionName> "Source: Freebase - The World's database". <http://rdf.freebase.com/ns/en.jamie_taylor> <http://rdf.freebase.com/ns/people.person.nationality> <http:// rdf.freebase.com/ns/en.united_states>. <http://rdf.freebase.com/ns/en.jamie_taylor> <http://rdf.freebase.com/ns/common.topic.image> <http://rdf.freebase.com/ ns/en.jamie_headshot>. <http://rdf.freebase.com/ns/en.jamie_taylor> <http://rdf.freebase.com/ns/type.object.name> "Jamie Taylor"@en. <http://rdf.freebase.com/ns/en.jamie_taylor> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http:// rdf.freebase.com/ns/user.skud.freebase_events.tshirt_recipient>. <http://rdf.freebase.com/ns/en.jamie_taylor> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http:// rdf.freebase.com/ns/user.skud.freebase_events.topic>. <http://rdf.freebase.com/ns/en.jamie_taylor> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http:// rdf.freebase.com/ns/book.author>. <http://rdf.freebase.com/ns/en.jamie_taylor> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http:// rdf.freebase.com/ns/people.person>.
  • 27. Instead.... Part I - so you can explain to other Part II - so you can do what you say • Part I • Why • Uses, Benefits • Part II • How • Representation, Concepts
  • 28. Part I Why
  • 29. Is very useful Build Flexible Applications with Graph Data
  • 30. The Office (US) Leatherheads TV Program Film stars in starred in John Krasinski Person, Actor attended Brown University College/university Graph Data Model
  • 31. A socially managed semantic database
  • 32. Freebase has Many Types of Things
  • 33. 9,547,107 Topics
  • 34. Contributions over $50000 made to members of the US congress in the 2008 election cycle by companies headquartered outside of the United States topic: topic: Barack Obama Switzerland government position held took money from is based in topic: topic: United States UBS AG Senator Freebase
  • 35. Industry Browser Identity Model Industry (USCB) Company Company Donations NAICS Ticker CRP CRP ID CRP CRP ID NAICS/SIC Map SEC Freebase Industry (SEC) Company People Person SIC SEC CIK SEC CIK Freebase Wikipedia Freebase Wikipedia Location Article ZIP Code
  • 36. Industry Browser http://kiwitobes.com/industry_mashup/
  • 37. Barriers between science and the humanities impede solving humanities important problems Web 2.0 + Semantics
  • 38. "Smoov" Ankolekar et al.2007
  • 39. Topic Blocks http://www.freebase.com/topicblocks/index?id=/en/pirates_of_the_caribbean_3
  • 40. http://www.freebase.com/widget/topic? mode=i&pane=image,article_props& id=/en/pirates_of_the_caribbean_3 http://www.freebase.com/widget/topic? mode=i&pane=image,article_props&id=/en/blade_runner
  • 41. Patrick Sinclair (BBC)
  • 42. About the Content (and visitor?)
  • 43. MIT Simile
  • 44. Simile http://dev.mqlx.com/~jamie/simile/timeline.html
  • 45. Data Portability Data Data Semantics allows data to be utilized by Data unanticipated new applications Data
  • 46. Simile
  • 47. MIT Simile: Exhibit
  • 48. User Experience
  • 49. Topic Hubs
  • 50. Open Calais
  • 51. Open Calais
  • 52. http://p.opencalais.com/er/company/ralg-tr1r/9e3f6c34-aa6b-3a3b-b221-a07aa7933633 Open Calais
  • 53. <rdf:Description rdf:nodeID="A1"> <att:lastupdated>2009-06-18T21:22:28</att:lastupdated> <att:text>IBM Corporation And Siemens Announce Integrated Solutions To Help Companies</att:text> </rdf:Description> <rdf:Description rdf:nodeID="A2"> <att:code>3577</att:code> <att:description>Computer Periph'L Equipment, Nec</att:description> </rdf:Description> <rdf:Description rdf:nodeID="A3"> <att:code>7371</att:code> <att:description>Computer Programming Services</att:description> </rdf:Description> <rdf:Description rdf:nodeID="A4"> <att:age>46</att:age> <att:lastname>Iwata</att:lastname> <att:officerurl rdf:resource="http://www.reuters.com/finance/stocks/ officerProfile?symbol=IBM.N&amp;officerId=222727"/> <att:firstname>Jon</att:firstname> <att:title>Senior Vice President - Marketing and Communications</att:title> <att:middle>C.</att:middle> </rdf:Description> http://p.opencalais.com/er/company/ralg-tr1r/9e3f6c34-aa6b-3a3b-b221-a07aa7933633 Open Calais
  • 54. <owl:sameAs rdf:resource="http://dbpedia.org/resource/IBM"/> <owl:sameAs rdf:resource="http://cb.semsol.org/company/ibm#self"/> A Graph of Graphs <owl:sameAs rdf:resource="http://p.opencalais.com/er/company/ralg- tr1r/9e3f6c34-aa6b-3a3b-b221-a07aa7933633"/>
  • 55. Epispider Herman Tolentino et al. http://epispider.net/index.php
  • 56. Chris Thorpe guardian.co.uk Open Platform
  • 57. Vocabulary Do you understand the words that are coming out of my mouth? -Chris Tucker, Rush Hour
  • 58. 1 New Orchard Road Publicaly Listed Armonk, New York Company rs Le 0000051143 arte g al NYSE:IBM dqu Str uc ol Hea 1889 b K tur ym CI Dat S e eF e r oun ded Ti ck Thomas Watson Founders Sam Palmisano CEO SIC O pe 3571:Electronic ra IC tin Soft es Computers NA g diari In war com i e De Subs e 334111:Electronic 17,604,000,000 Computer Manufacturing velo ped USD 2006 Cognos Cross Worlds SANSF, ViaVoice Lotus Notes
  • 59. Epispider Herman Tolentino et al. http://epispider.net/index.php
  • 60. vocabularies...are everywhere
  • 61. @ Short URLs # The Twitter Vocabulary
  • 62. Pivot on an @ tag
  • 63. Pivot on a # tag
  • 64. http://bit.ly/info/3zyJ8g Pivot on a Short URL
  • 65. Vocabularies make links more understandable ...and thus content more findable
  • 66. microformats Annotate existing HTML so the content can be "extracted by software and indexed, searched for, saved, cross-referenced or combined. "
  • 67. microformats
  • 68. microformats <div class="vcard"> ..... <div id="view"> <div id="home"> <table> <tr> <td class="f">address</td> <td class="v"> <div class="adr"> <span class="locality">Berkeley</span>, <span class="region">CA</span> <div class="country-name">United States</div> </div> </td> </tr> <tr> <td class="f">aim</td> <td class="v"><a id="aim" class="url im offline" href="aim:goim?screenname=jaredhanson@mac.com">jaredhanson@mac.com</a></td> </tr>
  • 69. microformats.org
  • 70. microformats • (Relatively) easy to use • Small, fixed vocabulary • No standard parsing pattern • No strong identifiers • Limits utility
  • 71. RDFa Annotate HTML with machine readable RDF
  • 72. RDFa <div xmlns:fb=”http://rdf.freebase.com/ns/” about=”http://rdf.freebase.com/ns/en.jamie_taylor” rel=fb:people.person.place_of_birth> <span resource=”http://rdf.freebase.com/ns/en.saint_paul”/> </div>
  • 73. RDFa • Unambiguous identifiers • Extensible vocabulary • Standard parsing pattern • Produces RDF • Hard to use • Rules about formatting based on RDF
  • 74. What “concepts” are covered in content Like existing tagging, but with strong identifiers! <resource> tagged Tag taggingDate "2001-01-01" label means "text" <resource> Strong identifier goes here!
  • 75. <resource> tagged Tag taggingDate label means <div class="rdfa" "text" <resource> xmlns:ctag="http://commontag.org/ns#"> NASA's <a typeof="ctag:Tag" rel="ctag:means" href="http://rdf.freebase.com/ns/en.phoenix_mars_mission" property="ctag:label">Phoenix Mars Lander</a> has deployed its robotic arm. </div>
  • 76. And the winner is....
  • 77. HTML5 MicroData • Annotate HTML with machine readable data • Simple Name-Value Pair design
  • 78. HTML5 MicroData Sometimes, it is desirable to annotate content with specific machine-readable labels, e.g. to allow generic scripts to provide services that are customised to the page, or to enable content from a variety of cooperating authors to be processed by a single script in a consistent manner.
  • 79. HTML5 Simple! 15 pages of 657 page spec
  • 80. HTML5 MicroData <section itemscope itemtype="http://example.org/animals#cat" itemid="http://semprog.com/jamiestuff/hedral"> <h1 itemprop="name">Hedral</h1> <p itemprop="desc">Hedral is a male american domestic shorthair, that is <span itemprop="http://example.com/color">black</span> and <span itemprop="http://example.com/color">white</span>.</p> <img itemprop="img" src="hedral.jpeg" alt="" title="Hedral, age 18 months"> </section>
  • 81. MicroData Widgets
  • 82. HTML5 MicroData • Easy to use • Strong identifiers • Extensible vocabulary • Easy to parse • In last call for comments stage! • Usable! Now!
  • 83. Vocabulary Powered Search Search Applications: - Enhanced results - Info Bar
  • 84. <div class="hReview-aggregate"> <div class="item vcard"> <h1 class="fn org">Taylor&#39;s Automatic Refresher</h1> <div class=rating> <img class="stars_3_half rating average" width="83" height="325" title="3.5 star rating" alt="3.5 star rating" src="http://static1.px.yelp.com/static/2843250757/i/new/ico/stars/stars_map.png"/></div> <em>based on <span class="count">888</span> reviews</em> </div> <div id="bizInfoContent"> <p id="bizCategories">Category: <span id="cat_display"><a href="/c/sf/burgers">Burgers</a> </span> <address class="adr"> Neighborhood: Embarcadero<br/> <span class="street-address">1 Ferry Bldg<br />Marketplace Shop #6</span><br /> <span class="locality">San Francisco</span>, <span class="region">CA</span> <span class="postal-code">94111</span><br /> </address> <span id="bizPhone" class="tel">(866) 328-3663</span>
  • 85. <div class="hReview-aggregate"> <div class="item vcard"> <h1 class="fn org">Taylor&#39;s Automatic Refresher</h1> <div class=rating> <img class="stars_3_half rating average" width="83" height="325" title="3.5 star rating" alt="3.5 star rating" src="http://static1.px.yelp.com/static/2843250757/i/new/ico/stars/stars_map.png"/></div> <em>based on <span class="count">888</span> reviews</em> </div> <div id="bizInfoContent"> <p id="bizCategories">Category: <span id="cat_display"><a href="/c/sf/burgers">Burgers</a> </span> <address class="adr"> Neighborhood: Embarcadero<br/> <span class="street-address">1 Ferry Bldg<br />Marketplace Shop #6</span><br /> <span class="locality">San Francisco</span>, <span class="region">CA</span> <span class="postal-code">94111</span><br /> </address> <span id="bizPhone" class="tel">(866) 328-3663</span>
  • 86. Search Monkey Vocabulary
  • 87. Search Monkey Vocabulary
  • 88. DBPedia Place Vocabulary <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs="http://www.w3.org/2000/01/rdf- schema#"> <rdf:Description rdf:about="http://dbpedia.org/ontology/areaTotal"><rdfs:domain rdf:resource="http://dbpedia.org/ ontology/Place"/></rdf:Description> <rdf:Description rdf:nodeID="b29203"><rdf:first rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description> <rdf:Description rdf:about="http://dbpedia.org/ontology/Place/nickname"><rdfs:domain rdf:resource="http:// dbpedia.org/ontology/Place"/></rdf:Description> <rdf:Description rdf:about="http://dbpedia.org/ontology/Place/location"><rdfs:range rdf:resource="http://dbpedia.org/ ontology/Place"/></rdf:Description> <rdf:Description rdf:about="http://dbpedia.org/ontology/maximumDepth"><rdfs:domain rdf:resource="http:// dbpedia.org/ontology/Place"/></rdf:Description> <rdf:Description rdf:about="http://dbpedia.org/ontology/Place/maximumElevation"><rdfs:domain rdf:resource="http:// dbpedia.org/ontology/Place"/></rdf:Description> <rdf:Description rdf:nodeID="b29250"><rdf:first rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description> <rdf:Description rdf:about="http://dbpedia.org/ontology/nearestCity"><rdfs:domain rdf:resource="http://dbpedia.org/ ontology/Place"/></rdf:Description> <rdf:Description rdf:about="http://dbpedia.org/ontology/PopulatedPlace"><rdfs:subClassOf rdf:resource="http:// dbpedia.org/ontology/Place"/></rdf:Description> <rdf:Description rdf:about="http://dbpedia.org/ontology/Place/maximumDepth"><rdfs:domain rdf:resource="http:// dbpedia.org/ontology/Place"/></rdf:Description> <rdf:Description rdf:about="http://dbpedia.org/ontology/Place/location"><rdfs:domain rdf:resource="http:// dbpedia.org/ontology/Place"/></rdf:Description> <rdf:Description rdf:nodeID="b29225"><rdf:first rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description>
  • 89. Rich Snippet Vocabulary • name • affiliation • nickname • price • postal-code • dtReviewed • photo • country-name • locality • reviewer • region • count • address • itemReviewed • title • brand • category • role http://data-vocabulary.org
  • 90. Rich Snippet Vocabulary <rdf:Property rdf:ID="affiliation"> <rdfs:comment>An affiliation can be specified by a string literal or an Organization instance.</rdfs:comment> <rdfs:domain rdf:resource="#Person"/> <rdfs:range> <owl:Class> <owl:unionOf rdf:parseType="Collection"> <owl:Class rdf:about="#Organization"/> <owl:Class rdf:about="xsd:string"/> </owl:unionOf> </owl:Class> </rdfs:range> </rdf:Property> <rdf:Property rdf:ID="brand"> <rdfs:domain rdf:resource="#Product"/> </rdf:Property> <rdf:Property rdf:ID="category"> <rdfs:domain> <owl:Class> <owl:unionOf rdf:parseType="Collection"> <owl:Class rdf:about="#Organization"/> <owl:Class rdf:about="#Product"/> </owl:unionOf> </owl:Class> </rdfs:domain> </rdf:Property>
  • 91. HTML5 Vocabularies
  • 92. Vocab Hub http://microdata.freebaseapps.com/
  • 93. Part II How (or why we wrote the book)
  • 94. The Office (US) Leatherheads TV Program Film stars in starred in John Krasinski Person, Actor attended Brown University College/university Rich Graph Data
  • 95. Connected to other rich sources
  • 96. Where does your data live?
  • 97. Traditional data-modeling
  • 98. Tabular data Restaurant Address Cuisine Price Open Deli Lllama Peachtree Rd Deli $ Mon, Tue, Wed, Thu, Fri Peking Inn Lake St Chinese $$$ Thur, Fri, Sat Thai Tanic Branch Dr Thai $$ Tue, Wed, Thu, Fri, Sat, Sun Lord of the Fries Flower Ave Fast food $$ Tue, Wed, Thu, Fri, Sat, Sun Marquis de Salade Main St French $$$ Thur, Fri, Sat Wok this way Second St Chinese $ Mon, Tue, Wed, Thu, Fri, Sat, Sun Luna Sea Autumn Dr Seafood $$$ Tue, Thu, Fri, Sat Pita Pan Thunder Rd Middle Eastern $$ Mon, Tue, Wed, Thu, Fri, Sat, Sun Award Weiners Dorfold Mews Fast food $ Mon, Tue, Wed, Thu, Fri, Sat Lettuce Eat Rustic Parkway Deli $$ Mon, Tue, Wed, Thu, Fri The beloved spreadsheet
  • 99. Tabular Data Restaurant Address Cuisine Price Open Deli Lllama Peachtree Rd Deli $ Mon (11a-4p), Tue (11-4), Wed (11-4), Thu (11-7), Fri (11-8) Peking Inn Lake St Chinese $$$ Thur (5p-10p), Fri (5p-1a), Sat (5p-1a) etc… Too much information, not enough cells
  • 100. A simple schema Restaurant Hours id restaurant_id name day address open cuisine_id close Cuisine id name Allows for simple queries
  • 101. A simple schema id name address price restaurant_id day open close 1 Deli Lllama Peachtree $ 1 Mon 11 16 Rd 1 Tue 11 16 2 Peking Inn Lake St $$$ 1 Thu 11 19 ... 2 Fri 5 23 ... Filled with data
  • 102. Some new data Bar Address DJ Best Drink The Bitter End 14th Ave No Beer Peking Inn Lake St No Scorpion Bowl Hammer Time Wildcat Dr Yes Hennessey Marquis de Salade Main St Yes Martini This doesn’t fit into our schema...
  • 103. Half-empty columns Restaurant Address Price DJ Best Drink Deli Lllama Peachtree Rd $ Peking Inn Lake St $$$ No Scorpion Bowl Thai Tanic Branch Dr $$ Lord of the Fries Flower Ave $$ Marquis de Salade Main St $$$ Yes Martini Wok this way Second St $ Luna Sea Autumn Dr $$$ Pita Pan Thunder Rd $$ Award Weiners Dorfold Mews $ Lettuce Eat Rustic Parkway $$ Hammer Time Wildcat Dr Yes Hennessey The Bitter End 14th St No Beer Maybe ok now, but can’t this keep happening?
  • 104. Link the tables Restaurant RB_Link id restaurant_id Bar name bar_id id address name cuisine_id dj best_drink But now the information is duplicated :(
  • 105. Split place / purpose Bar id venue_id dj Hours Venue best_drink venue_id id day name open address Restaurant close id venue_id cuisine_id Better, but now we have to “migrate”
  • 106. Large schemas A small section of a limited product
  • 107. A flexible schema Venue Properties id venue_id name field_id address value field id name Does this look familiar?
  • 108. Add some data id name address venue_id field_id value 1 Deli Lllama Peachtree Rd 1 1 Deli 2 Peking Inn Lake St 1 2 $ ... 2 1 Chinese 2 2 $$$ 2 3 Scorpion Bowl 2 4 No id name 1 Cuisine 2 Price 3 Specialty Cocktail 4 DJ? simple enough...
  • 109. Add live music info id name address venue_id field_id value 1 Deli Lllama Peachtree Rd 1 1 Deli 1 2 $ 2 Peking Inn Lake St 2 1 Chinese 3 Thai Tanic Branch Dr 2 2 $$$ 2 3 Scorpion Bowl 2 4 No 3 5 Yes 3 6 Jazz id name 1 Cuisine 2 Price 3 Specialty Cocktail 4 DJ? 5 Live Music 6 Music Genre No schema change required
  • 110. Explicit semantics
  • 111. The basic data unit subject predicate object Remember this from grammar class?
  • 112. Restaurants as triples subject predicate object S1 cuisine “Deli” S1 price “$” S1 name “Deli Llama” S2 cuisine “Chinese” S2 price “$” S2 name “Peking Inn” S2 best drink “Scorpion Bowl” S2 address “Lake St” S2 DJ? “No” S4 name “Fendalton” S4 contained-by S5 S5 name “Christchurch” S1 location S4 S6 name “Downtown” S6 contained-by S7 S7 name “Wellington, NZ” S2 location S6 Machine readable and almost human readable
  • 113. ...or as a graph Deli Liiama Name Cuisine S1 Deli Price $
  • 114. Restaurant Graph Peking Inn Deli Liiama Name Cuisine Name S1 Deli Price S2 $ Location Cuisine Location Chinese Contained-by Christchurch S4 Name Fendalton
  • 115. Extending The Restaurant Model Deli Liiama Urban Chic Name Decor Cuisine S1 Deli Music Price $ Location Live DJ Contained-by Christchurch S4 Name Fendalton
  • 116. Integrating Graph Data Models Deli Liiama Name Deli Liiama Name A2 Cuisine S1 Deli Price OnTap $ Z6 Brand Leinenkugel Brand Pabst BR
  • 117. What Went Wrong? Scripting Languages facilitate change ....where is the data model that does the same? Things change Requirements change User expectations change Data structures change Our data models aren’t keeping up
  • 118. Semantic Representation Relationships are represented explicitly Schema can be represented as a graph Data integration is the union of two graphs This makes creating, extending, and combining data much easier than before
  • 119. Just enough RDF
  • 120. Just Enough RDF RDF is a Data Model A very simple model!
  • 121. Cosmos was written by Carl Sagan
  • 122. Subject Predicate Object (Cosmos) (was written by) (Carl Sagan) author Carl Cosmos Sagan
  • 123. Subject Which Cosmos? (Cosmos)
  • 124. Subject Which Cosmos? (Cosmos)
  • 125. Identifiers are Everywhere #w2e
  • 126. The humble URI •URI’s provide strong references •Much like pointing in the physical world “this is red” “this is a pen” •a URIref is an unambiguous pointer to something of meaning
  • 127. Subject Which Cosmos? (Cosmos) http://rdf.freebase.com/ns/authority.openlibrary.book.OL3568862M
  • 128. What do you mean, author? http://rdf.freebase.com/ns/book.written_work.author author Carl Cosmos Sagan vocabulary
  • 129. There are billions of Carl Sagans... http://rdf.freebase.com/ns/en.carl_sagan Cosmos author
  • 130. 0 ” 9 8 d “1 h e b lis p u author Carl Cosmos Sagan
  • 131. RDF Data Model Nodes (“Subjects”) connect via Links (“Predicates”) to Objects • either Nodes or Literals
  • 132. Expressions of RDF RDF has many (inconvenient) serializations •RDF-XML •N3 •Turtle •NTriples •RDFa
  • 133. URIs provide identity http://rdf.freebase.com/ns/en.robert_cook Stability Simplicity Manageability
  • 134. Not all URL’s are good identifiers
  • 135. Plugable Data Data Semantics allows an Data application to utilize unanticipated new Data Data data sources
  • 136. Plugable Data
  • 137. Data Portability Data Data Semantics allows data to be utilized by Data unanticipated new applications Data
  • 138. Data Portability http://dev.mqlx.com/~jamie/simile/timeline.html
  • 139. Data Portability
  • 140. Why Does This Work? Semantics facilitate shared meaning through • Subject Identity • Strong and Consistent Semantics • Open APIS + Open Data These principles make it much easier to extend, combine, and integrate data
  • 141. RDF Graphs Carrie Starred In Star Wars Fisher Starred In Harrison Blade Starred In Ford Runner Starred In Daryl Hannah
  • 142. Triple Stores (aka Graph Stores)
  • 143. Allegro Graph
  • 144. + + Keep your data as flexible as the source
  • 145. Strong Identifiers Strong Semantics (strong vocabularies) Open Data
  • 146. Can describe?! At the end of this talk - you should be able to say how semantics benefits each of these groups • Semantics Benefit • Site owners • Site users • Developers • You