With the recent introduction of Open Data APIs, namely SDMX-JSON, and other web services planned, the OECD is moving from a pure ‘browser centric’ architecture towards a more ‘web service oriented’ architecture, with powerful and scalable data delivery capabilities in machine-to-machine exchanges, enabling a much wider use of our data by third parties. This focus has, and will further enable more and more users to assemble content and data themselves, compare or integrate data, or collaborate with each other to produce new content. This also allowed for and has led to a number of new and accessible data experiences, now targeting those who do not understand, or have the desire to understand, specialised formats of a statistical nature. This is where the real value will be found in being ‘open, accessible, and understandable”.

1. Being Open, Accessible, and Understandable
Prepared and presented by Jonathan Challener, OECD
International Marketing And Outputs DataBase Conference
Évora, Portugal
21-25 September 2014
#imaodbc2014

2. Three distinct concepts of data as defined by the ODI data definitions

3. Three distinct concepts of data as defined by the ODI data definitions
Open data can be big, but doesn't have to
be. Big data is often based on personal
data, but not necessarily.

4. Big Open Personal (BOP) Data

5. Big Open Personal (BOP) Data
The data types are merging. Social media
being the main contributor to this
potential future ‘big open, and personal’
paradigm.

6. For now we are interested in Open Data
Information that is available for
anyone to use, for any purpose, at no
cost.

7. Data deluge is only getting bigger

8. We are all putting up the open signs,
inviting users into our data supermarkets

9. All too much for the average user

10. Not everyone is a data scientist!

11. Easy to consume

12. Easy to understand

13. Accessible
Find Free Food
In my city

14. Turn Data Into Free Food!
What if a city released a list of all trees
planted on its public property. You could
filter the data into a list of all the fruit
and nut trees in the city, transfer it into
an online database, and create a
smartphone app that helps anyone find
free food.

15. Learn about the trees of Paris
A complete list of 300,000 trees maintained by
the City of Paris is available via an android app.

16. Project Delta: making OECD data…
Accessible
Open
Find
Understand
Use
Free
Machine-readable
Indexable
Re-Useable
Available without
charge

17. Open
• All data open-ready via .Stat
• Open Data premium services
Accessible
• Data Lab (March 2013)
• Data Portal (2014)
• Search
• User-journeys across OECD online
Free
• Freemium strategy to maximise dissemination
and impact
• 100% data & content available for free in
a basic form
• Premium services on a cost-recovery basis
• OECD iLibrary v2 (2015)
• Sustainable financing for publishing
Project Delta:
Objectives and deliverables

18. 46%
63%
26%
86%
77%
82%
100%
Open Data
readiness
Open data
governance
Community of
end-users
Portal
accessibility
OECD 2013
OECD Target 2015
Open data evolution of the OECD
Low evolution expected in
regard to the community
of end-users!

19. Audience breakdown visiting oecd.org since 2009
Public sector
21%
IGOs
3%
NGOs
7%
Academia 42%
Corporate
Media
2%
24%
Other 1%
Significant increase in
the proportion of
academics, up 34%.

20. User needs…
Expert
user
Non-expert
Expert user needs:
• looks for specific data
• know what they are looking for
• wants fast and complete download to use in own tools
• citation is important
• embeds graphs
• …used to complicated tools
Non-expert user needs:
• only interested in main indicators and most relevant graphs
• looks for answers, no matter if analytical from pubs, particularly
overviews and summaries
• shares graphs
• …used to consumer tools
(less forgiving)

21. OECD Data Products
•.Stat browser
• Branded views
• Data API
• Key tables
• Easy to embed charts
• Factbook and “At a Glance” publications
• Ready-made tables
• Mobile apps
• Data portal indicators
• Simple API usage
Expert
user
Non-expert

22. Once
upon
a
time…

23. First we began with this

24. Audience > expert users

25. Audience > expert users
I’m a policy
analyst
I’m a
researcher/
statistician
I’m a
university
librarian
With both
time and skills!

26. Audience > expert users with machines
I’m a policy
analyst
I’m a
researcher/
statistician
I’m a
university
librarian

27. Audience > Org2Org via machine to machine
<?xml version="1.0"?>
<message:MessageGroup
xmlns:message="http://www.SDMX.org/resources/SDMXML/schemas/v2_0/message"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://www.SDMX.org/resources/SDMXML/schemas/v2_0/generic
http://www.sdmx.org/docs/2_0/SDMXGenericData.xsd
http://www.SDMX.org/resources/SDMXML/schemas/v2_0/message
http://www.sdmx.org/docs/2_0/SDMXMessage.xsd"
xmlns:common="http://www.SDMX.org/resources/SDMXML/schemas/v2_0/common"
xmlns="http://www.SDMX.org/resources/SDMXML/schemas/v2_0/generic"><Header
xmlns="http://www.SDMX.org/resources/SDMXML/schemas/v2_0/message">
<ID>none</ID><Test>false</Test><Truncated>false</Truncated><Prepared>2013-04-
15T11:46:19</Prepared>
<Sender id="OECD"><Name xml:lang="en">Organisation for Economic Co-operation and
Development</Name>
<Name xml:lang="fr">Organisation de coopération et de développement
économiques</Name></Sender></Header>
<DataSet

28. With both time
and skills!

29. Simple
Lightweight
data
formats <b>This is bold</b>

30. {“SDMX”:“JSON”}

32. API services

33. Audience > developers

34. Who don’t have the desire to understand data…

35. …in specialised formats of a statistical nature

36. A good start…

37. to becoming open ready
{“SDMX”:“JSON”}

38. but more is needed

39. I’m a
student
I’m a
journalist
I’m a
citizen with
a cause
I’m an
inquisitive
user
To reach a wider audience

40. Easy to consume

41. Easy to understand

42. Accessible
Find Free Food
In my city

44. data.oecd.org

45. data.oecd.org
Data portal vision (from the point of view of
the user: “Let me easily access the OECD
statistical data and analysis. Let me find,
understand and use the data I need.”

46. A complex back office layer bringing
together various pieces of information
from several sources.

47. Enabling a front office compilation for consumption of key
indicators with links to relevant summaries and publications, as
well as access to complete databases in .Stat.

48. Quick access to
key indicators via
search or browse

49. Filtered search to
display different
result types and
by topic

50. Topic pages

51. Country
profiling

52. Full screen view

53. Quickly share something of interest

54. and there’s more….

55. Custom visualisations – Better Life Index

56. Custom visualisations – Better Life Index
How happy is my
country?
One of our most popular publications.

57. Environmental
indicators

58. Embeddable
tables

59. Mobile apps

60. Many interfaces to data

61. Is this too much?

62. Integrated experience

63. I’m a
student
I’m a
journalist
I’m a
citizen with
a cause
I’m an
inquisitive
user
I’m a policy
analyst
I’m a
researcher/
statistician
I’m a
university
librarian
Users

64. In control
I’m a
student
I’m a
journalist
I’m a
citizen with
a cause
I’m an
inquisitive
user
I’m a policy
analyst
I’m a
researcher/
statistician
I’m a
university
librarian

65. Data Portal next version?
Personalised dashboard
Allow users to copy visualisations
to a clipboard and create their
own dashboard.

66. Find Free Food
In my city

68. Build on the momentum

69. Larger user engagement

70. Will the worlds of Official Statistics and statistics
produced by the public converge?

71. Being Open, Accessible, and Understandable
Thank You
Prepared and presented by Jonathan Challener - Project Manager, OECD
jonathan.challener@oecd.org
@Challener
slideshare.net/JonathanChallener
International Marketing And Outputs DataBase Conference
Évora, Portugal
21-25 September 2014

72. Sources used
• Image: http://yowpyowp.blogspot.com/2010/09/they-drew-flintstones.html
• Image: https://www.adaptiveportfolios.com/media/1_momentum-716.jpg
• Image: http://www.snoutypig.com/2013/04/16/snouty-pride-thats-not-all-folks
• http://www.oecd.org/site/envind/
• http://www.oecdbetterlifeindex.org/
• http://data.oecd.org
• Image: http://www.telegraph.co.uk
• http://stats.oecd.org/opendataapi/OData.html
• http://stats.oecd.org
• Reference: SDMX DataStructure-OECD.FDI(1.2).xml
• Reference: OECD data publishing with APIs
• Reference: Study by the OECD on users of OECD.org (2013)
• Reference: OECD Delta-Benchmark - final report
• Reference: http://www.wired.com/2014/08/dat/?utm_source=dlvr.it&utm_medium=tumblr
• Image: http://blog.etq.com/Portals/41636/images/MrData.jpg
• Reference: http://seradigm.co.nz/category/opendata
• Image: http://commons.wikimedia.org/wiki/File:Planking_in_supermarket.jpg
• Reference: https://github.com/theodi/data-definitions
• #imaodbc2014