Presented in March 2012 at the OECD Statistical Information System Collaboration Community (SIS-CC) Workshop in Paris. Video available at http://youtu.be/ZldhNV3Qt6c The digitization of information exchange processes has led in many industries to define standards to be used in the B2B side of the value chain for the conversations between key partners. The agencies involved in statistical production are not an exception and need to agree on standards that can be used in the exchange of data and metadata between them. However, before these standards have been fully adopted, new needs have arisen that have stressed the importance of machine readable formats for the reuse of the public sector information. Open data initiatives have usually found a strategic ally in the statistical offices because timeliness, punctuality and accessibility are part of the code of practice in official statistics. This has increased the necessity of standards not only for data exchange between organizations specializing in statistical production but also for dissemination to third parties. The presentation will try to address the requirements that the dissemination standards should meet in this new context.

1. Standards for statistical data dissemination
a wish list
Xavier Badosa (@badosa)
Statistical Institute of Catalonia
OECD Statistical Information System
Collaboration Community (SIS-CC)
Workshop 2012. Paris, 12-14 March

2. For humans

3. For humans (naked)

4. For humans (naked)
(accessed and read by humans)

5. For humans (naked)
(accessed and read humans)

6. For humans with machines
(accessed by humans,
but read by machines)
For humans (naked)
(accessed and read humans)

7. For machines

8. For machines built by humans

9. For machines built by humans
(accessed and read by machines)

10. API D A T A

12. General-purpose
“Apps”
Third-party
“Apps”
that solve specific needs
Statistics as platform “O.S.”

13. How I stopped worrying about my
website and learned to love the whole
Internet
Matt McAlister
Director of Digital Strategy
Guardian Media Group

14. We don’t operate in the
eyeball market maximum data
exposure & reach
We operate in the
accuracy preservation
reference
market brand recognition

19. E A B
C
H
A Big orgs
N
G Stats-savvy
E
B2B

20. E A B
C
H
A Big orgs
N
G Stats-savvy
E
B2B
Shared environment

21. D
I
S
S
E
M
I
N
A
T
I
O
N

22. ?

23. like the ?
WWW

25. For machines built by humans

26. don’t make me think
KISS principle
respect the conventions
develop also
for the weakest link

27. is a platform
An example

28. is widely used
An example

29. 2006
is widely used
2009 50,000 applications

30. is widely used
# mashups

32. is widely used
had more than
1 provider

37. is widely used
= is a standard

38. “these APIs are simple enough for weekend
hackers to build interesting projects on, and
(…) easy to implement even on mobile devices
and in almost any programming language.”
Anil Dash
Expert Labs
http://dashes.com/anil/2009/12/the-twitter-api-is-finished.html

39. KISS principle
“these APIs are simple enough for weekend
hackers to build interesting projects on, and
(…) easy to implement even on mobile devices
and in almost any programming language.”
Anil Dash
Expert Labs
http://dashes.com/anil/2009/12/the-twitter-api-is-finished.html

40. develop for the weakest link
“these APIs are simple enough for weekend
hackers to build interesting projects on, and
(…) easy to implement even on mobile devices
and in almost any programming language.”
Anil Dash
Expert Labs
http://dashes.com/anil/2009/12/the-twitter-api-is-finished.html

41. provide a useful service
“these APIs are simple enough for weekend
hackers to build interesting projects on, and
(…) easy to implement even on mobile devices
and in almost any programming language.”
Anil Dash
Expert Labs
http://dashes.com/anil/2009/12/the-twitter-api-is-finished.html

42. get close to the end users
“these APIs are simple enough for weekend
hackers to build interesting projects on, and
(…) easy to implement even on mobile devices
and in almost any programming language.”
Anil Dash
Expert Labs
http://dashes.com/anil/2009/12/the-twitter-api-is-finished.html

43. langs / APIs ~ browsers / websites
“these APIs are simple enough for weekend
hackers to build interesting projects on, and
(…) easy to implement even on mobile devices
and in almost any programming language.”
Anil Dash
Expert Labs
http://dashes.com/anil/2009/12/the-twitter-api-is-finished.html

44. “these APIs are simple enough for weekend
hackers to build interesting projects on, and
(…) easy to implement even on mobile devices
and in almost any programming language.”

45. 2 APIs
REST API 100 x 1.5 = 150 pp.
Streaming API 6 x 3 = 18 pp.
< 200 pp.

46. 208 pp.
< 200 pp.
books.google.com

47. The Fifteen Minute Rule
A person of reasonable
ability should be able to
get from zero to ‘Hello World’
in fifteen minutes.
Michael E. Driscoll
Dataspore, Metamarkets

48. http://lcsd05.cs.tamu.edu/slides/keynote.pdf

51. 18 pp.
1 PDF
18 pp.

52. 18 pp.
1 PDF
143 pp.

53. 161 pp.
1 PDF
143 pp.

54. 161 pp.
ZIP 8 MSW

55. 1,109 pp.
ZIP 8 MSW
46 pp.
341 pp.
269 pp.
68 pp.
176 pp.
34 pp.
4 pp.
10 pp.

56. 1,109 pp.
Samples

57. 1,278 pp.
ZIP 1 PDF
169 pp.

58. 1,327 pp.
PDF
49 pp.

59. 1,377 pp.
PDF
50 pp.

60. 1,408 pp.
PDF
31 pp.

61. 1,408 pp.
1,344 pp.
books.google.com

62. high barrier to entry
API
developers

63. E
C
H
A
N SDMX
G
E
Shared environment

64. E
C
H
A
N SDMX
G amazingly flexible
E
Shared environment

65. E
C
H
A
N SDMX
G amazingly complex
E
Shared environment

66. E
C
H
A
N SDMX
G amazingly complex
E
SDMX-ML is a meta-language

67. D
I
S TypePad WordPress
S
E
M
I
N
A
T
I
existing Twitter clients
O
N

68. The Metcalfe-Bray Law
D The value of a
I markup language
is proportional
S TypePad WordPress
approximately
S to the square
E of the
M number of
I different
N software
implementations
A that can process
T it.
I Tim Bray
existing Twitter clients
O Google
N

69. The Metcalfe-Bray Law
D The value of a
I markup language
is proportional
S Stats provider Stats provider
approximately
S to the square
E of the
M number of
I different
N software
implementations
A that can process
T it.
I Tim Bray
existing clients
O Google
N

70. D
I Are we
S Stats provider Stats provider
so special
S that
E we
M can’t
I benefit
N from
A existing
T libraries
I and clients?
existing clients
O
N

71. Are we
so special
that
we
Special things can’t
benefit
from
existing
libraries
and clients?
Common things

72. Population Search API

73. Population Search API
Atom

74. Population Search API
Atom OpenSearch

75. Population Search API
Atom OpenSearch SDMX

76. Population Search API

77. Population Search API

78. Rectifications API

79. Rectifications API
Atom OpenSearch

80. Rectifications API
Atom OpenSearch

81. Rectifications API
Atom OpenSearch

82. Rectifications API
Atom OpenSearch

83. Rectifications API
Atom OpenSearch

84. Rectifications API
Atom OpenSearch

87. Atom
OpenSearch
http://www.opensearch.org
Open Data Protocol
http://www.odata.org
Google Data Protocol
http://code.google.com/apis/gdata/
Open Publication Distribution System
http://opds-spec.org

88. Are we
so special
that
we
Special things can’t
benefit
from
existing
libraries
and clients?
Common things

89. Are we
so special
SDMX? that
we
Special things can’t
benefit
from
existing
libraries
and clients?
Common things

90. Are we
so special
SDMX? that
we
Special things can’t
benefit
from
Simplified SDMX? existing
libraries
and clients?
Common things

91. A Complex System That Works Is Invariably
Found To Have Evolved From A Simple System
That Worked.
“Gall’s Law”
Systemantics
How Systems Work and Especially How They Fail
John Gall

92. The parallel proposition also appears to be true:
A Complex System Designed From Scratch
Never Works And Cannot Be Made To Work.
You Have To Start Over, Beginning With A
Working Simple System.
“Gall’s Law”
Systemantics
How Systems Work and Especially How They Fail
John Gall

93. What’s common practice
in the API space?

94. Open APIs and the Semantic Web (John Musser, ProgrammableWeb)
http://www.slideshare.net/jmusser/j-musser-semtechjun2011

95. “REST”
RESTish
Pragmatic REST
REST-inspired
Open APIs and the Semantic Web (John Musser, ProgrammableWeb)
http://www.slideshare.net/jmusser/j-musser-semtechjun2011

96. Open APIs and the Semantic Web (John Musser, ProgrammableWeb)
http://www.slideshare.net/jmusser/j-musser-semtechjun2011

97. Open APIs and the Semantic Web (John Musser, ProgrammableWeb)
http://www.slideshare.net/jmusser/j-musser-semtechjun2011

98. Open APIs and the Semantic Web (John Musser, ProgrammableWeb)
http://www.slideshare.net/jmusser/j-musser-semtechjun2011

102. <KeyFamilyRef>ALFS_SUMTAB</KeyFamilyRef>
<Series>
<SeriesKey>
<Value concept="LOCATION" value="AUS" />
<Value concept="SUBJECT" value="YGTT01L1_ST" />
<Value concept="FREQUENCY" value="A" />
</SeriesKey>
<Attributes>
<Value concept="TIME_FORMAT" value="P1Y" />
</Attributes>
<Obs>
<Time>2000</Time>
<ObsValue value="19153" />
</Obs>
<Obs>
<Time>2001</Time>
<ObsValue value="19413" />
</Obs>
<Obs>
<Time>2002</Time>
SDMX-ML
<ObsValue value="19651" />
</Obs>
<Obs>
<Time>2003</Time>
<ObsValue value="19895" />
</Obs>
<Obs>
<Time>2004</Time>
<ObsValue value="20127" />
fragment
</Obs>
<Obs>
<Time>2005</Time>
<ObsValue value="20395" />
</Obs>
<Obs>
<Time>2006</Time>
<ObsValue value="20698" />
</Obs>
<Obs>
<Time>2007</Time>
<ObsValue value="21072" />
</Obs>
<Obs>
<Time>2008</Time>
<ObsValue value="21499" />
</Obs>
<Obs>
<Time>2009</Time>
<ObsValue value="21955" />
</Obs>
<Obs>
<Time>2010</Time>
<ObsValue value="22342" />
</Obs>
</Series>

103. <KeyFamilyRef>ALFS_SUMTAB</KeyFamilyRef>
<KeyFamilyRef>ALFS_SUMTAB</KeyFamilyRef> <Series>
<SeriesKey>
<Series> <Value concept="LOCATION" value="AUS" />
<SeriesKey> <Value concept="SUBJECT" value="YGTT01L1_ST" />
<Value concept="FREQUENCY" value="A" />
<Value concept="LOCATION" value="AUS" /> </SeriesKey>
<Attributes>
<Value concept="SUBJECT" value="YGTT01L1_ST" /> <Value concept="TIME_FORMAT" value="P1Y" />
</Attributes>
<Value concept="FREQUENCY" value="A" /> <Obs>
</SeriesKey> <Time>2000</Time>
<ObsValue value="19153" />
<Attributes> </Obs>
<Obs>
<Value concept="TIME_FORMAT" value="P1Y" /> <Time>2001</Time>
<ObsValue value="19413" />
</Attributes> </Obs>
<Obs> <Obs>
<Time>2002</Time>
<Time>2000</Time> <ObsValue value="19651" />
</Obs>
<ObsValue value="19153" /> <Obs>
<Time>2003</Time>
</Obs> <ObsValue value="19895" />
<Obs> </Obs>
<Obs>
<Time>2001</Time> <Time>2004</Time>
<ObsValue value="20127" />
<ObsValue value="19413" /> </Obs>
<Obs>
</Obs> <Time>2005</Time>
<Obs> <ObsValue value="20395" />
</Obs>
<Time>2002</Time> <Obs>
<Time>2006</Time>
<ObsValue value="19651" /> <ObsValue value="20698" />
</Obs>
</Obs> <Obs>
<Obs> <Time>2007</Time>
<ObsValue value="21072" />
<Time>2003</Time> </Obs>
<Obs>
<ObsValue value="19895" /> <Time>2008</Time>
<ObsValue value="21499" />
</Obs> </Obs>
<Obs> <Obs>
<Time>2009</Time>
<Time>2004</Time> <ObsValue value="21955" />
</Obs>
<ObsValue value="20127" /> <Obs>
<Time>2010</Time>
</Obs> <ObsValue value="22342" />
<Obs> </Obs>
</Series>
<Time>2005</Time>

104. <KeyFamilyRef>ALFS_SUMTAB</KeyFamilyRef> "KeyFamilyRef" : "ALFS_SUMTAB" ,
<Series> "Series" : {
<SeriesKey> "SeriesKey" : {
<Value concept="LOCATION" value="AUS" /> "location" : "AUS" ,
<Value concept="SUBJECT" value="YGTT01L1_ST" /> "subject" : "YGTT01L1_ST" ,
<Value concept="FREQUENCY" value="A" /> "frequency" : "A"
</SeriesKey> },
<Attributes> "Attributes" : {
<Value concept="TIME_FORMAT" value="P1Y" /> "time_format" : "P1Y"
</Attributes> },
<Obs> "Obs" : [
<Time>2000</Time> {"2000" : 19153},
<ObsValue value="19153" /> {"2001" : 19413},
</Obs> {"2002" : 19651},
<Obs> {"2003" : 19895},
<Time>2001</Time> {"2004" : 20127},
<ObsValue value="19413" /> {"2005" : 20395},
</Obs> {"2006" : 20698},
<Obs> {"2007" : 21072},
<Time>2002</Time> {"2008" : 21499},
<ObsValue value="19651" /> {"2009" : 21955},
</Obs> {"2010" : 22342}
<Obs> ]
<Time>2003</Time>
<ObsValue value="19895" />
</Obs>
<Obs>
<Time>2004</Time>
<ObsValue value="20127" />
</Obs>
<Obs>
<Time>2005</Time>

105. "KeyFamilyRef" : "ALFS_SUMTAB" ,
"Series" : {
"SeriesKey" : {
"location" : "AUS" ,
"subject" : "YGTT01L1_ST" ,
"frequency" : "A"
},
"Attributes" : {
"time_format" : "P1Y"
},
"Obs" : [
{"2000" : 19153},
{"2001" : 19413},
{"2002" : 19651},
{"2003" : 19895},
{"2004" : 20127},
{"2005" : 20395},
{"2006" : 20698},
{"2007" : 21072},
{"2008" : 21499},
{"2009" : 21955},
{"2010" : 22342}
]

106. "KeyFamilyRef" : "ALFS_SUMTAB" ,
"Series" : {
"SeriesKey" : {
"location" : "AUS" ,
"subject" : "YGTT01L1_ST" ,
"frequency" : "A"
},
"Attributes" : {
"time_format" : "P1Y"
},
"Obs" : {
"2000" : 19153,
"2001" : 19413,
"2002" : 19651,
"2003" : 19895,
"2004" : 20127,
"2005" : 20395,
"2006" : 20698,
"2007" : 21072,
"2008" : 21499,
"2009" : 21955,
"2010" : 22342
}

107. "KeyFamilyRef" : "ALFS_SUMTAB" ,
"Series" : {
"SeriesKey" : {
"location" : "AUS" ,
"subject" : "YGTT01L1_ST" ,
"frequency" : "A"
},
"Attributes" : {
"time_format" : "P1Y"
},
"Obs" : {
"time": [
"2000","2001","2002","2003",
"2004","2005","2006","2007",
"2008","2009","2010"
],
"value": [
19153,19413,19651,19895,
20127,20395,20698,21072,
21499,21955,22342
]
}

108. "KeyFamilyRef" : "ALFS_SUMTAB" ,
"Series" : {
"SeriesKey" : {
"location" : "AUS" ,
"subject" : "YGTT01L1_ST" ,
"frequency" : "A"
},
"Attributes" : {
"time_format" : "P1Y"
},
"Obs" : {
"time": [
"2000","2001","2002","2003",
"2004","2005","2006","2007",
"2008","2009","2010"
],
"value": [
19153,19413,19651,19895,
20127,20395,20698,21072,
21499,21955,22342
]
}

109. "KeyFamilyRef" : "ALFS_SUMTAB" ,
"Series" : {
"SeriesKey" : {
"location" : "AUS" ,
Natural to programmers "subject" : "YGTT01L1_ST" ,
"frequency" : "A"
},
"Attributes" : {
“time_format" : "P1Y"
},
"Obs" : {
"time": [
"2000","2001","2002","2003",
"2004","2005","2006","2007",
"2008","2009","2010"
],
"value": [
19153,19413,19651,19895,
20127,20395,20698,21072,
21499,21955,22342
]
}

110. "KeyFamilyRef" : "ALFS_SUMTAB" ,
a “data” format "Series" : {
"SeriesKey" : {
"location" : "AUS" ,
Natural to programmers "subject" : "YGTT01L1_ST" ,
"frequency" : "A"
},
"Attributes" : {
string, number, bool, null “time_format" : "P1Y"
},
array (vector, list, sequence) "Obs" : {
"time": [
"2000","2001","2002","2003",
object (struct, hash table, "2004","2005","2006","2007",
associative array, map, "2008","2009","2010"
],
record, keyed list, dictionary) "value": [
19153,19413,19651,19895,
20127,20395,20698,21072,
21499,21955,22342
]
}

111. "KeyFamilyRef" : "ALFS_SUMTAB" ,
a “data” format "Series" : {
"SeriesKey" : {
"location" : "AUS" ,
Natural to programmers "subject" : "YGTT01L1_ST" ,
"frequency" : "A"
},
"Attributes" : {
“time_format" : "P1Y"
“JSON shines as a },
"Obs" : {
programming language- "time": [
independent representation "2000","2001","2002","2003",
"2004","2005","2006","2007",
of typical programming "2008","2009","2010"
language data structures.” ],
"value": [
James Clark 19153,19413,19651,19895,
Technical lead for the W3C XML 20127,20395,20698,21072,
activity which developed 21499,21955,22342
XML 1.0 Recommendation ]
}

112. "KeyFamilyRef" : "ALFS_SUMTAB" ,
"Series" : {
"SeriesKey" : {
"location" : "AUS" ,
Natural to programmers "subject" : "YGTT01L1_ST" ,
"frequency" : "A"
},
"Attributes" : {
value[0] = 19153 “time_format" : "P1Y"
value[1] = 19413 },
value[2] = 19651 "Obs" : {
"time": [
value[3] = 19895 "2000","2001","2002","2003",
value[4] = 20127 "2004","2005","2006","2007",
value[5] = 20395 "2008","2009","2010"
],
value[6] = 20698 "value": [
value[7] = 21072 19153,19413,19651,19895,
value[8] = 21499 20127,20395,20698,21072,
21499,21955,22342
value[9] = 21955 ]
value[10] = 22342 }

113. "KeyFamilyRef" : "ALFS_SUMTAB" ,
"Series" : {
"SeriesKey" : {
"location" : "AUS" ,
Natural to programmers "subject" : "YGTT01L1_ST" ,
"frequency" : "A"
},
"Attributes" : {
"time_format" : "P1Y"
},
"Obs" : {
"time": [
"2000","2001","2002","2003",
"2004","2005","2006","2007",
"2008","2009","2010"
],
"value": [
19153,19413,19651,19895,
20127,20395,20698,21072,
21499,21955,22342
]
}

114. "KeyFamilyRef" : "ALFS_SUMTAB" ,
"Series" : {
"SeriesKey" : {
"location" : "AUS" ,
Natural to programmers "subject" : "YGTT01L1_ST" ,
"frequency" : "A"
},
"Attributes" : {
"time_format" : "P1Y"
},
"Obs" : {
"time": [
"2000","2001","2002","2003",
"2004","2005","2006","2007",
"2008","2009","2010"
],
"value": [
19153,19413,19651,19895,
20127,20395,20698,21072,
21499,21955,22342
]
}

115. From document viewer
Natural to programmers
to application platform

116. Fragmented device market

117. Fragmented device market

119. Storage
Offline
Geolocation
Audio and Video
Canvas
Drag and Drop
…
JS APIs

124. SGML / DTD XML / XSD

128. JSONP callback
JSON with padding

129. C
O
R
S

130. http://caniuse.com/#feat=cors

131. Date: Wed, 22 Feb 2012 17:12:52 GMT
Server: Apache
Expires: Wed, 22 Feb 2012 18:12:52 GMT
Access-Control-Allow-Origin: *
Content-Length: 697
Connection: close
Content-Type: application/json;charset=utf-8
200 OK
http://api.idescat.cat/pob/v1/sug.json?q=bar

132. XML SDMX-ML
JSON
SDMX-JS?

133. XML
JSON

134. XML Xml2Json()
JSON
On-the-fly conversion

135. XML Xml2Json()
JSON
On-the-fly conversion
<text>Hello, World!</text>

136. XML Xml2Json()
JSON
On-the-fly conversion
<text>Hello, World!</text>
"text": "Hello, World!"

137. XML Xml2Json()
JSON
On-the-fly conversion
<text>Hello, World!</text>
<text>Goodbye, Life!</text>
"text": "Hello, World!"

138. XML Xml2Json()
JSON
On-the-fly conversion
<text>Hello, World!</text>
<text>Goodbye, Life!</text>
"text": ["Hello, World!",
"Goodbye, Life!"]

139. XML Xml2Json()
JSON
On-the-fly conversion
<text>Hello, World!</text>
"text": ["Hello, World!"]

140. XML
JSON
Predefined map

141. XML
JSON
Predefined map
namespaces?
elements/attributes?
all strings?

142. “XMLish”
JSON
Predefined map

143. {"@concept" : "OBS_STATUS", "@value" : "P"}}},
{"generic:Time" : "2011-04", "generic:ObsValue" :
“XMLish”
{"@value" : "106.56246"}, "generic:Attributes" :
{"generic:Value" : {"@concept" : "OBS_STATUS",
"@value" : "P"}}}, {"generic:Time" : "2011-05",
JSON
"generic:ObsValue" : {"@value" : "113.26596"},
"generic:Attributes" : {"generic:Value" :
{"@concept" : "OBS_STATUS", "@value" : "P"}}},
{"generic:Time" : "2011-06", "generic:ObsValue" :
{"@value" : "114.22037"}, "generic:Attributes" :
{"generic:Value" : {"@concept" : "OBS_STATUS",
"@value" : "P"}}}, {"generic:Time" : "2011-07",
"generic:ObsValue" : {"@value" : "108.77534"},
"generic:Attributes" : {"generic:Value" :
{"@concept" : "OBS_STATUS", "@value" : "P"}}},
{"generic:Time" : "2011-08", "generic:ObsValue" :
{"@value" : "116.37424"}, "generic:Attributes" :

144. natural-born
JSON

145. natural-born
JSON
“JSON-G” genuine

146. natural-born
JSON
“JSON-G”
“JSON-C”
compact/customized

148. Price of an apple?
Save as many bytes
as possible

149. Price of an apple?
Nutrition value
Allergies
Recipes
Price
Forbidden fruit in
the Garden of Eden

150. Flexibility
Nutrition value
Allergies
Recipes
Price
Forbidden fruit in
the Garden of Eden

152. detail=full
detail=dataonly
detail=serieskeysonly
detail=nodata

154. ResponseGroup=Images,Reviews

156. fields=id,name,picture

158. fields=title,teaserbyline,none

160. :(id,first-name,last-name,positions:(title))

162. fields=id,scope/type

163. fields=entry(id,gd:when)

164. fields=entry(@gd:*,id,gd:when)

165. fields=entry(title,link[@rel='self' or @rel='edit'],
media:group(media:thumbnail))

166. fields=entry[media:group/yt:duration/@seconds
<= 120 and yt:statistics/@viewCount > 20]

167. simple
flexible
RESTish
JSON
lightweight
developer-centric
mobile-friendly

168. simple
flexible
RESTish
JSON
lightweight
Semantic Web-ish?
developer-centric
mobile-friendly

169. I have a dream for the Web [in which computers] become
capable of analyzing all the data on the Web – the content,
links, and transactions between people and computers. A
‘Semantic Web’, which should make this possible, has yet to
emerge, but when it does, the day-to-day mechanisms of
trade, bureaucracy and our daily lives will be handled by
machines talking to machines. The ‘intelligent agents’ people
have touted for ages will finally materialize.
Tim Berners-Lee
Director of the W3C, 1999

176. Statistical “Cube” Data. The group will produce a
vocabulary, compatible with SDMX, for expressing
some kinds of statistical data. This need not be as
expressive as all of SDMX, but may provide a subset
as in the RDF Data Cube vocabulary. It may also include ways to
annotate data to indicate its assumptions and comparability.

179. The Mainstream
Relevance “Law”
The mainstream
relevance of a
communication
environment is
proportional to
the quantity of
rubbish in that
environment.

180. The Mainstream
Relevance “Law”
The mainstream
relevance of a
communication
environment is
proportional to
the quantity of
rubbish in that
environment.

181. The Mainstream
Relevance “Law”
TV
e-mail
Twitter
...

182. simple?
flexible
RESTish
JSON?
lightweight?
Semantic Web-ish?
developer-centric?
mobile-friendly?

183. Open APIs and the Semantic Web (John Musser, ProgrammableWeb)
http://www.slideshare.net/jmusser/j-musser-semtechjun2011

184. Open APIs and the Semantic Web (John Musser, ProgrammableWeb)
http://www.slideshare.net/jmusser/j-musser-semtechjun2011

187. For some web developers the need to understand
the RDF data model and associated serializations and
query language (SPARQL) has proved a barrier to
adoption of linked data. This project seeks to develop
APIs, data formats and supporting tools to overcome
this barrier. Including, but not limited to, accessing
linked data via a developer-friendly JSON format.

188. Simplify + JSONify SDMX?
Reuse/adapt a generic data format?
semantic

189. Simplify + JSONify SDMX?
Reuse/adapt a generic data format?
semantic
Create a new simple standard for stats?

190. http://json-stat.org

191. http://json-stat.org
lightweight

192. http://json-stat.org
simple

193. http://json-stat.org
developer-centric

194. http://json-stat.org
flexible

195. http://code.google.com/p/json-stat/

196. {
"label": "Latest population figure of Catalonia",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1,1,1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "U" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "value": [7539618]
"label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"2011-01-01":0} , "label": {"2011-01-01":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index" : { "B" : 0 } , "label" : { "B" : "Catalonia" }
}
}
}
}

197. {
"label": "Latest population figure of Catalonia",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
"id"} ,
: ["metric", "time", "geo"],
"time" : {
"size" : [1, 1, 1],
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"2011-01-01":0} , "label": {"2011-01-01":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index" : { "B" : 0 } , "label" : { "B" : "Catalonia" }
}
}
}
}

198. {
"label": "Latest population figure of Catalonia",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"index" : { "pop" : 0 } ,
"category" : {
"index": {"2011-01-01":0} , "label": {"2011-01-01":"January 1st, 2011"}
"label" : { "pop" : "Population" }
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index" : { "B" : 0 } , "label" : { "B" : "Catalonia" }
}
}
}
}

199. {
"label": "Latest population figure of Catalonia",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"index" : { "pop" : 0 } ,
"category" : {
"index": {"2011-01-01":0} , "label": {"2011-01-01":"January 1st, 2011"}
"label" : { "pop" : "Population" }
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index" : { "B" : 0 } , "label" : { "B" : "Catalonia" }
}
}
}
}

200. {
"label": "Latest population figure of Catalonia",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"20110101":0} , "label": {"20110101":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index" : { "B" : 0 } , "label" : { "B" : "Catalonia" }
}
}
}
}

201. {
"label": "Latest population figure of Catalonia",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"20110101":0} , "label": {"20110101":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"index" : {"2011-01-01" : 0} ,
"category" : {
"index" : { "B" : 0 } , "label" : { "B" : "Catalonia" }
"label" : {"2011-01-01" : "January 1st, 2011"}
}
}
}
}

202. {
"label": "Latest population figure of Catalonia",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"20110101":0} , "label": {"20110101":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"index" : {"2011-01-01" : 0} ,
"category" : {
"index" : { "B" : 0 } , "label" : { "B" : "Catalonia" }
"label" : {"2011-01-01" : "January 1st, 2011"}
}
}
}
}

203. {
"label": "Latest population figure of Catalonia",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"20110101":0} , "label": {"20110101":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"index" : {"2011-01-01" : 0} ,
"category" : {
"index" : { "B" : 0 } , "label" : { "B" : "Catalonia" }
"label" : {"2011-01-01" : "January 1st, 2011"}
}
}
}
}

204. {
"label": "Latest population figure of Catalonia",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"20110101":0} , "label": {"20110101":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index":{"ISO-3166-2:ES-CT":0} , "label":{"ISO-3166-2:ES-CT":"Catalonia"}
}
}
}
}

205. {
"label": "Latest population figure of Catalonia",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"index" : { "ISO-3166-2:ES-CT" : 0 } ,
//
"time" : {
"label" : "When" , "desc" : "Longer text",
"label" : { "ISO-3166-2:ES-CT" : "Catalonia" }
"category" : {
"index": {"2011-01-01":0} , "label": {"2011-01-01":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index":{"ISO-3166-2:ES-CT":0} , "label":{"ISO-3166-2:ES-CT":"Catalonia"}
}
}
}
}

206. {
"label": "Latest population figure of Catalonia",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"index" : { "ISO-3166-2:ES-CT" : 0 } ,
//
"time" : {
"label" : "When" , "desc" : "Longer text",
"label" : { "ISO-3166-2:ES-CT" : "Catalonia" }
"category" : {
"index": {"2011-01-01":0} , "label": {"2011-01-01":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index":{"ISO-3166-2:ES-CT":0} , "label":{"ISO-3166-2:ES-CT":"Catalonia"}
}
}
}
}

207. {
"label": "Population of Catalonia, January 1st, 2011",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"20110101":0} , "label": {"20110101":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index":{"ISO-3166-2:ES-CT":0} , "label":{"ISO-3166-2:ES-CT":"Catalonia"}
}
}
}
}

208. {
"label": “Population of Catalonia, January 1st, 2011",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"2011-01-01":0} , "label": {"2011-01-01":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index":{"ISO-3166-2:ES-CT":0} , "label":{"ISO-3166-2:ES-CT":"Catalonia"}
}
}
}
}

209. {
"label": “Population of Catalonia, January 1st, 2011",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"type" : { "pop" : "count" } ,
"index": {"2011-01-01":0} , "label": {"2011-01-01":"January 1st, 2011"}
}
} , "base" : { "pop" : "Person" } ,
"geo" : {
//
"symbol" : {
"label" : "Where" , "desc" : "Longer text",
"pop" : null } ,
"mult"
"category" : {
: { "pop" : 0 }
"index":{"ISO-3166-2:ES-CT":0} , "label":{"ISO-3166-2:ES-CT":"Catalonia"}
}
}
}
}

210. {
"label": “Population of Catalonia, January 1st, 2011",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"2011-01-01":0} , "label": {"2011-01-01":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index":{"ISO-3166-2:ES-CT":0} , "label":{"ISO-3166-2:ES-CT":"Catalonia"}
}
}
}
}

211. {
"label": “Population of Catalonia, January 1st, 2011",
"value": [7539618] ,
"long" : 2.178389,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"lat" : 41.383531
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"2011-01-01":0} , "label": {"2011-01-01":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index":{"ISO-3166-2:ES-CT":0} , "label":{"ISO-3166-2:ES-CT":"Catalonia"}
}
}
}
}

212. {
"label": “Population of Catalonia, January 1st, 2011",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"20110101":0} , "label": {"20110101":"January 1st, 2011"}
}
} ,
"geo" : {
"index" : {"20110101" : 0} ,
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"label" : {"20110101" : "January 1st, 2011"}
"index":{"ISO-3166-2:ES-CT":0} , "label":{"ISO-3166-2:ES-CT":"Catalonia"}
}
}
}
}

213. {
"label": “Population of Catalonia, January 1st, 2011",
"value": [7539618] ,
"index"
"dimension" : {: {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"from" : "20000101"
"metric": {
,
//
"to" : "20110101"
"label" : "What" , "desc" : "Longer text",
"category" : {
} "index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"20110101":0} , "label": {"20110101":"January 1st, 2011"}
}
} ,
"geo" : {
"index" : {"20110101" : 0} ,
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"label" : {"20110101" : "January 1st, 2011"}
"index":{"ISO-3166-2:ES-CT":0} , "label":{"ISO-3166-2:ES-CT":"Catalonia"}
}
}
}
}

214. {
"label": “Population of Catalonia, January 1st, 2011",
"value": [7539618] ,
"dimension" : {
"id" : ["metric", "time", "geo"], "size" : [1, 1, 1],
"metric": {
// "label" : "What" , "desc" : "Longer text",
"category" : {
"index" : { "pop" : 0 } , "label" : { "pop" : "Population" } ,
"unit" : {"type" : {"pop" : "count"} , "base" : {"pop" : "Person"} ,"symbol" : { "pop" : null} ,"mult" : {"pop" : 0} }
}
} ,
"time" : {
// "label" : "When" , "desc" : "Longer text",
"category" : {
"index": {"20110101":0} , "label": {"20110101":"January 1st, 2011"}
}
} ,
"geo" : {
// "label" : "Where" , "desc" : "Longer text",
"category" : {
"index":{"ISO-3166-2:ES-CT":0} , "label":{"ISO-3166-2:ES-CT":"Catalonia"}
}
}
}
}

215. "value": [3732196, 3807422 , 7539618]

216. "value": [3732196, 3807422 , 7539618]
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 1, 1, 3]

217. "value": [3732196, 3807422 , 7539618]
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 1, 1, 3]
"sex" : {
"category" : {
"index" : {"M" : 0 , "F" : 1 , "T" : 2} ,
"label" : {
"M" : "Men" ,
"F" : "Women" ,
"T" : "Total"
}
}
}

218. "value": [3732196, 3807422 , 7539618]
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 1, 1, 3]
"sex" : {
"category" : {
"index" : {"M" : 0 , "F" : 1 , "T" : 2} ,
"label" : {
"M" : "Men" ,
"F" : "Women" ,
"T" : "Total"
}
} Names not predetermined!
}

219. "value": [3732196, 3807422 , 7539618]
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 1, 1, 3]
"sex" : {
"category" : {
"index" : {"M" : 0 , "F" : 1 , "T" : 2} ,
"label" : {
"M" : "Men" ,
"F" : "Women" ,
"T" : "Total"
}
} value[dimension["sex"].category.index["F"]]
}

220. "value": [3732196, 3807422 , 7539618]
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 1, 1, 3]
"sex" : {
"category" : {
"id" : ["M", "F", "T"] ,
"label" : ["Men", "Women", "Total"]
}
}
value[dimension["sex"].category.index["F"]]

221. "value": [3732196, 3807422 , 7539618]
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 1, 1, 3]
"sex" : {
"category" : {
"id" : ["M", "F", "T"] ,
"label" : ["Men", "Women", "Total"]
}
}
for( ; ; ){ ... }
value[dimension["sex"].category.index["F"]]

222. "value": [3732196, 3807422 , 7539618]
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 1, 1, 3]
"sex" : {
"category" : {
"index" : {"M" : 0 , "F" : 1 , "T" : 2} ,
"label" : {
"M" : "Men" ,
"F" : "Women" ,
"T" : "Total"
}
}
}

223. "value": [3732196, 3807422 , 7539618]
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 1, 1, 3]
"sex3" : {
"attribute" : "sex" ,
"category" : {
"index" : {"M" : 0 , "F" : 1 , "T" : 2} ,
"label" : {
"M" : "Men" ,
"F" : "Women" ,
"T" : "Total"
}
}
}

224. "value": [
3058628, 3115336, 3201029, 3309850, 3366329, 3468235, 3543706, 3578176, 3661028, 3713765, 3724515, 3732196,
3203371, 3246029, 3305411, 3394296, 3446990, 3526971, 3590991, 3632332, 3703050, 3761655, 3787866, 3807422,
6261999, 6361365, 6506440, 6704146, 6813319, 6995206, 7134697, 7210508, 7364078, 7475420, 7512381, 7539618
]

225. "value": [
3058628, 3115336, 3201029, 3309850, 3366329, 3468235, 3543706, 3578176, 3661028, 3713765, 3724515, 3732196,
3203371, 3246029, 3305411, 3394296, 3446990, 3526971, 3590991, 3632332, 3703050, 3761655, 3787866, 3807422,
6261999, 6361365, 6506440, 6704146, 6813319, 6995206, 7134697, 7210508, 7364078, 7475420, 7512381, 7539618
]
↓ cryptic
↑ single model

226. "value": [
3058628, 3115336, 3201029, 3309850, 3366329, 3468235, 3543706, 3578176, 3661028, 3713765, 3724515, 3732196,
3203371, 3246029, 3305411, 3394296, 3446990, 3526971, 3590991, 3632332, 3703050, 3761655, 3787866, 3807422,
6261999, 6361365, 6506440, 6704146, 6813319, 6995206, 7134697, 7210508, 7364078, 7475420, 7512381, 7539618
]
↓ cryptic
↑ single model
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 12, 1, 3]

227. "value": [
3058628, 3115336, 3201029, 3309850, 3366329, 3468235, 3543706, 3578176, 3661028, 3713765, 3724515, 3732196,
3203371, 3246029, 3305411, 3394296, 3446990, 3526971, 3590991, 3632332, 3703050, 3761655, 3787866, 3807422,
6261999, 6361365, 6506440, 6704146, 6813319, 6995206, 7134697, 7210508, 7364078, 7475420, 7512381, 7539618
]
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 12, 1, 3]

228. "value": [
3058628, 3115336, 3201029, 3309850, 3366329, 3468235, 3543706, 3578176, 3661028, 3713765, 3724515, 3732196,
3203371, 3246029, 3305411, 3394296, 3446990, 3526971, 3590991, 3632332, 3703050, 3761655, 3787866, 3807422,
6261999, 6361365, 6506440, 6704146, 6813319, 6995206, 7134697, 7210508, 7364078, 7475420, 7512381, 7539618
]
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Male
Female
Total
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 12, 1, 3]

229. "value": [
3058628, 3115336, 3201029, 3309850, 3366329, 3468235, 3543706, 3578176, 3661028, 3713765, 3724515, 3732196,
3203371, 3246029, 3305411, 3394296, 3446990, 3526971, 3590991, 3632332, 3703050, 3761655, 3787866, 3807422,
6261999, 6361365, 6506440, 6704146, 6813319, 6995206, 7134697, 7210508, 7364078, 7475420, 7512381, 7539618
]
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Male
Female “CSV revisited”
Total
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 12, 1, 3]

230. "value": [
3058628, 3115336, 3201029, 3309850, 3366329, 3468235, 3543706, 3578176, 3661028, 3713765, 3724515, 3732196,
3203371, 3246029, 3305411, 3394296, 3446990, 3526971, 3590991, 3632332, 3703050, 3761655, 3787866, 3807422,
6261999, 6361365, 6506440, 6704146, 6813319, 6995206, 7134697, 7210508, 7364078, 7475420, 7512381, 7539618
]
getDataById(ds, {"sex" : "M" , "time" : "20090101"})
"id" : ["metric", "time", "geo", "sex"] ,
"size" : [1, 12, 1, 3]

231. "value": [
3058628, 3115336, 3201029, 3309850, 3366329, 3468235, 3543706, 3578176, 3661028, 3713765, 3724515, 3732196,
3203371, 3246029, 3305411, 3394296, 3446990, 3526971, 3590991, 3632332, 3703050, 3761655, 3787866, 3807422,
6261999, 6361365, 6506440, 6704146, 6813319, 6995206, 7134697, 7210508, 7364078, 7475420, 7512381, 7539618
]
"status": [
"a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "p", "e",
"a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "p", "e",
"a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "p", "e"
]

232. "value": [3732196, 3807422 , 7539618]
"sex" : {
"category" : {
"index" : {"M" : 0 , "F" : 1 , "T" : 2} ,
"label" : {
"M" : "Men" ,
"F" : "Women" ,
"T" : "Total"
} ,
}
}

233. "value": [3732196, 3807422 , 7539618]
"sex" : {
"category" : {
"index" : {"M" : 0 , "F" : 1 , "T" : 2} ,
"label" : {
"M" : "Men" ,
"F" : "Women" ,
"T" : "Total"
} ,
"uri" : "http://jsonstat.dataprovider.org/dimension/sex.json",
}
}

234. "value": [3732196, 3807422 , 7539618]
"sex" : {
"category" : {
"uri" : "http://jsonstat.dataprovider.org/dimension/sex.json",
}
}

235. The JSON-stat
Community
Welcomes You!

236. The JSON-stat
Community
Welcomes You!
Needs You!

237. Standards for statistical data dissemination
a wish list
Xavier Badosa (@badosa)
Statistical Institute of Catalonia
Thank you
OECD Statistical Information System
Collaboration Community (SIS-CC)
Workshop 2012. Paris, 12-14 March

238. Dan Taylor
borman818 / Daniel Borman
Christian Cable
Ian Muttoo
Donald Macleod
Lushbunny
shaggy359
Wikimedia Commons
http://en.wikipedia.org/wiki/File:IBM_PC_5150.jpg
http://en.wikipedia.org/wiki/File:Asimo_look_new_design.jpg
Richard Cyganiak

239. Photos of products and webpages have been taken from the respective
companies’ websites. 1993 Mosaic webpage, © Board of Trustees of the
University of Illinois, taken from the Computer History Museum website.
Superman logo (free licence) from vectortemplates.com. Authors’
pictures taken from respective websites or Twitter accounts, except Tim
Berners-Lee taken from a video session. HTML5 logo from W3C. Image from
Stanley Kubrick’s Dr. Strangelove or: How I Learned to Stop Worrying and
Love the Bomb, © Columbia Pictures. Homo erectus’ drawing taken from
recursos.cnice.mec.es (Spanish Ministry of Education & Science). Homo
sapiens neanderthalis’ drawing taken from vanedf11.blogspot.com.