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

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

11. http://www.flickr.com/photos/pacroon/
http://www.flickr.com/photos/soldiersmediacenter/

12. PageRank
tm

13. 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

15. 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.

16. Jarvis resorts to the
concept of a "gift
economy" to explain
the link economy
http://www.flickr.com/photos/pagedooley/

17. I am a behavioral
economist.
Gift economics are
frequently used as
explanations for
what we don't
understand

18. Worse I am a
Behaviorist
Only talk about
what you can
observe

19. Semantics
Process of communicating enough
meaning to result in an action

20. Link Economy
• Enriching links focuses meaning
• Improves "findability" (SEO)
• Increased usability
• Better ad selection

21. 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

24. Wish it were real

25. Might be real

26. Is real, but don't believe it

27. Is very useful
Build Flexible
Applications with
Graph Data

28. Not Your Typical
Semantic Web Talk

29. The W3C Layer Cake
The Cake
taken from http://www.w3.org/2007/Talks/0130-sb-W3CTechSemWeb/layerCake-4.png

30. AI Agents
http://www.flickr.com/photos/matthewtownsend/

31. Ontologies

32. 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>.

33. 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

34. Part I
Why

35. Is very useful
Build Flexible
Applications with
Graph Data

36. The Office (US) Leatherheads
TV Program Film
stars in starred in
John Krasinski
Person, Actor
attended
Brown University
College/university
Graph Data Model

37. A socially managed semantic database

38. Freebase has Many Types of Things

41. 9,547,107 Topics

42. 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

43. 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

44. Industry Browser
http://kiwitobes.com/industry_mashup/

45. Barriers between science and
the humanities impede solving
humanities important problems
Web 2.0 + Semantics

46. "Smoov"
Ankolekar et al.2007

47. Topic Blocks
http://www.freebase.com/topicblocks/index?id=/en/pirates_of_the_caribbean_3

48. 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

51. Patrick Sinclair (BBC)

52. About the Content (and visitor?)

53. MIT Simile

54. Simile
http://dev.mqlx.com/~jamie/simile/timeline.html

55. Data Portability
Data Data
Semantics allows data to
be utilized by
Data
unanticipated new
applications
Data

56. Simile

57. MIT Simile: Exhibit

58. User Experience

59. Topic Hubs

60. Open Calais

61. Open Calais

62. http://p.opencalais.com/er/company/ralg-tr1r/9e3f6c34-aa6b-3a3b-b221-a07aa7933633
Open Calais

63. <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

64. <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"/>

65. Epispider
Herman Tolentino et al. http://epispider.net/index.php

66. Chris Thorpe
guardian.co.uk Open Platform

67. Vocabulary
Do you understand the words that are
coming out of my mouth?
-Chris Tucker, Rush Hour

68. 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

69. Epispider
Herman Tolentino et al. http://epispider.net/index.php

70. vocabularies...are
everywhere

71. @
Short URLs
#
The Twitter Vocabulary

72. Pivot on an @ tag

73. Pivot on a # tag

74. http://bit.ly/info/3zyJ8g
Pivot on a Short URL

75. Vocabularies make links
more understandable
...and thus content more
findable

76. microformats
Annotate existing HTML so the
content can be "extracted by
software and indexed, searched for,
saved, cross-referenced or
combined. "

77. microformats

78. 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>

79. microformats.org

80. microformats
• (Relatively) easy to use
• Small, fixed vocabulary
• No standard parsing pattern
• No strong identifiers
• Limits utility

81. RDFa
Annotate HTML with machine readable RDF

82. 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>

83. RDFa
• Unambiguous identifiers
• Extensible vocabulary
• Standard parsing pattern
• Produces RDF
• Hard to use
• Rules about formatting based on RDF

84. 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!

85. <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>

87. And the winner is....

88. HTML5 MicroData
• Annotate HTML with machine
readable data
• Simple Name-Value Pair design

89. 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.

90. HTML5
Simple! 15 pages of 657 page spec

91. 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>

92. MicroData Widgets

93. HTML5 MicroData
• Easy to use
• Strong identifiers
• Extensible vocabulary
• Easy to parse
• In last call for comments stage!
• Usable! Now!

94. Vocabulary Powered Search
Search Applications:
- Enhanced results
- Info Bar

95. <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>

97. <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>

98. Search Monkey Vocabulary

99. Search Monkey Vocabulary

100. 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>

101. 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

102. 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>

103. HTML5 Vocabularies

104. Vocab Hub
http://microdata.freebaseapps.com/

105. Part II
How
(or why we wrote the book)

107. The Office (US) Leatherheads
TV Program Film
stars in starred in
John Krasinski
Person, Actor
attended
Brown University
College/university
Rich Graph Data

108. Connected to other rich sources

109. Where does your data live?

110. Traditional data-modeling

111. 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

112. 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

113. A simple schema
Restaurant Hours
id restaurant_id
name day
address open
cuisine_id close
Cuisine
id
name
Allows for simple queries

114. 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

115. 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...

116. 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?

117. 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 :(

118. 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”

119. Large schemas
A small section of a limited product

120. A flexible schema
Venue Properties
id venue_id
name field_id
address value
field
id
name
Does this look familiar?

121. 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...

122. 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

123. Explicit semantics

124. The basic data unit
subject predicate object
Remember this from grammar class?

125. 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

126. ...or as a graph
Deli Liiama
Name
Cuisine
S1 Deli
Price
$

127. Restaurant Graph
Peking Inn Deli Liiama
Name
Cuisine
Name S1 Deli
Price
S2
$
Location
Cuisine Location
Chinese Contained-by
Christchurch
S4
Name Fendalton

128. Extending The Restaurant Model
Deli Liiama
Urban Chic Name
Decor
Cuisine
S1 Deli
Music Price
$
Location
Live DJ
Contained-by
Christchurch
S4
Name Fendalton

129. Integrating Graph Data Models
Deli Liiama
Name
Deli Liiama
Name
A2
Cuisine
S1 Deli
Price
OnTap
$
Z6 Brand
Leinenkugel
Brand
Pabst BR

130. 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

131. 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

132. Just enough RDF

133. Just Enough RDF
RDF is a Data Model
A very simple model!

134. Cosmos was written by Carl Sagan

135. Subject Predicate Object
(Cosmos) (was written by) (Carl Sagan)
author Carl
Cosmos
Sagan

136. Subject Which Cosmos?
(Cosmos)

137. Subject Which Cosmos?
(Cosmos)

138. Identifiers are Everywhere
#w2e

139. 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

140. Subject Which Cosmos?
(Cosmos)
http://rdf.freebase.com/ns/authority.openlibrary.book.OL3568862M

141. What do you mean, author?
http://rdf.freebase.com/ns/book.written_work.author
author Carl
Cosmos
Sagan
vocabulary

142. There are billions of Carl Sagans...
http://rdf.freebase.com/ns/en.carl_sagan
Cosmos author

143. 0 ”
9 8
d “1
h e
b lis
p u
author Carl
Cosmos
Sagan

144. RDF Data Model
Nodes (“Subjects”)
connect via Links (“Predicates”)
to Objects
• either Nodes or Literals

145. Expressions of RDF
RDF has many (inconvenient) serializations
•RDF-XML
•N3
•Turtle
•NTriples
•RDFa

146. URIs provide identity
http://rdf.freebase.com/ns/en.robert_cook
Stability
Simplicity
Manageability

147. Not all URL’s are good identifiers

148. Plugable Data
Data
Semantics allows an
Data
application to utilize
unanticipated new
Data
Data
data sources

149. Plugable Data

150. Data Portability
Data Data
Semantics allows data to
be utilized by
Data
unanticipated new
applications
Data

151. Data Portability
http://dev.mqlx.com/~jamie/simile/timeline.html

152. Data Portability

153. 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

154. RDF Graphs
Carrie
Starred In Star Wars
Fisher
Starred In
Harrison Blade
Starred In
Ford Runner
Starred In
Daryl
Hannah

155. Triple Stores
(aka Graph Stores)

156. Allegro Graph

157. +
+
Keep your data as flexible as the source

158. Strong Identifiers
Strong Semantics
(strong vocabularies)
Open Data

159. 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