From a talk at the Berkman Center for Internet and Sociey on 25th November 2014. https://cyber.law.harvard.edu/events/luncheon/2014/11/davies

1. Unpacking open data: power,
politics and the influence of
infrastructures
Harvard Berkman Centre for Internet and Society
November 25th 2014
Tim Davies | tim.davies@soton.ac.uk | @timdavies

5. Overview
1) Framing and method
2) A brief history
3) Unpacking the standard model
4) Questioning the standard model
5) Shaping information infrastructures
6) Re-imagining an open data agenda

6. Framing & method

7. Null hypothesis"
(examples)
• H1: Open data is not delivering widespread
inclusive civic engagement;
• H2: Open data is not delivering scaleable
innovation;
• H3: Open data is not substantially shifting the
balance of power between citizen and state;

8. www.opendatabarometer.org
http://ssrn.[ ] com/abstract=2492520
www.opendataresearch.org/reports/
standard.open-contracting.org

10. “The group is offering a set of fundamental principles for open
government data. By embracing the eight principles, governments of
the world can become more effective, transparent, and relevant to
our lives.”
Carl Malamud (2007), https://public.resource.org/8_principles.html
Civic technology

11. Public Sector Information Industry

12. Political crisis

13. Unpacking the standard model

14. Open Data Barometer - 2013 Overall Ranking

15. Proactively published | Machine Readable | Legally re-usable

16. Machine Readable | Proactively published | Legally re-usable
JSON

17. Open datasets
Impact Theory of change
Intermediaries & Apps

18. Photo credit: Transparent Chennai
Politics Co-production Markets
http://www.opendataimpacts.net/report

19. Questioning the standard model
Picture credit: Some rights reserved by Birmingham Museum and Art Gallery

20. Number of datasets in sample meeting standard model definition
0$ 10$ 20$ 30$ 40$ 50$ 60$ 70$
1050$
1660$
1865$
1790$
2390$
2685$
2660$
2655$
2530$
2985$
2860$
3$
3$
3$
3$
8$
4$
4$
4$
5$
5$
10$
6$
6$
7$
n = 77"
!
2013 Open
Data
Barometer
!
Maximum
possible
dataset
score =
7700
0$ 500$ 1000$ 1500$ 2000$ 2500$ 3000$ 3500$ 4000$
Countries
Census$
Trade$
Educa=on$
Budget$
Environment$
Health$
Elec=ons$
Crime$
Map$
Spend$
Legisla=on$
Transport$
Company$
Land$
Dataset score
Aggregate openness score for each data category
3330$
3740$
3650$
Openness score based on weighted response to 10 variables per dataset, covering existence, accessibility, machine-readability, bulk downloads,
free of charge, license, sustainability, timeliness, discoverability, and linked-data versions of datasets.

21. Table 4. Primariness of published spending
Entity of the federation committed settled paid budgetary unit function sub-function
nature of
spending
source of
funds
type of
tender
no. of the
process +Ɯ /6 good/service
provided
City Hall of Rio de Janeiro ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Sao Luis ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Joao Pessoa ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
ƛ ,#1%,*-1/,))/
+/)Ȕ
Federal Executive ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Teresina ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
Federal Senate ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Palmas ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Maceio ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Curitiba ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Salvador ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Sao Paulo ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Boa Vista ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Recife ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Belem ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Florianopolis ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Macapa ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Fortaleza ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Porto Alegre ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Cuiaba ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
Government of the Federal District ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Vitoria ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Goiania ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Porto Velho ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Belo Horizonte ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Natal ˛ ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Aracaju ˛ ˛ ˛ ˛ ˛ ˛
City Hall of Campo Grande ˛ ˛
City Hall of Rio Branco ˛ ˛
City Hall of Manaus ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛ ˛
Source and Prepared by: Gpopai/Usp, 2014.

22. USA (2009) | Denmark (2009) | UK (2010) |
Kenya (2011) | India (2012) | Philippines (2014)

23. Common elements across country policies
Policy component Countries
Launching a portal UK, USA, Kenya, India,
Philippines, Denmark
Specifying license UK, USA, Denmark,
Philippines
Zero-charge for data UK, USA, Denmark
Departmental action plans (1) or officials responsible for
1: UK, USA
open data in each agency (2)
2: USA, India
Specification of meta-data standards USA, Philippines, India, UK
Emphasis on visualisations and info-graphics Philippines, India
Specific datasets or categories of data to be released UK, USA
Adopting the ‘five stars of linked open data’ UK, Philippines, India
Emphasis on ‘high-value’ datasets USA, UK, Philippines,
India, Denmark
Re-thinking government information infrastructures:
rationalising databases and adopting data standards
Explicit in Danish and
Indian policies, implied in
USA, UK and Philippines

25. Shaping information infrastructures

29. Null hypothesis
(revisited)
• H1: Open data is not delivering widespread
inclusive civic engagement;
• H2: Open data is not delivering scaleable
innovation;
• H3: Open data is not substantially shifting the
balance of power between citizen and state;

30. Re-imagining open data

31. Decontextualised data Data in context

32. Decontextualised data Data in context
Epiphenomenal data Active Data

33. Decontextualised data Data in context
Epiphenomenal data Active Data
Inclusive information
infrastructure
Raw data now

34. Decontextualised data Data in context
Epiphenomenal data Active Data
Inclusive information
infrastructure
Raw data now

35. Unpacking open data: power,
politics and the influence of
infrastructures
Tweet via: #berkman
Tim Davies | tim.davies@soton.ac.uk | @timdavies

36. Unpacking open data: power,
politics and the influence of
infrastructures
Live-stream participants:
you can tweet questions or comments on the #berkman tag
Tim Davies | tim.davies@soton.ac.uk | @timdavies

37. Image Credits Hossen27: https://commons.wikimedia.org/wiki/File:Below_Auckland_Harbour_Bridge_Hossen27.jpg
!
Bidgee: https://commons.wikimedia.org/wiki/
File:Rural_landscape_of_Wantabadgery_near_Mundarlo_from_the_air.jpg
!
Martin Richards: https://commons.wikimedia.org/wiki/File:Houses_of_parliament_London.jpg
!
Lin Kristensen: https://commons.wikimedia.org/wiki/File:Timeless_Books.jpg
!
Epic Fireworks: https://commons.wikimedia.org/wiki/File:Maersk_container_with_Fireworks.jpg
!
David Orban: http://donneesouvertes.info/2012/04/30/comment-lopen-data-est-devenu-un-objet-politique/
!
Strebe: https://commons.wikimedia.org/wiki/File:Gall%E2%80%93Peters_projection_SW.jpg
!
Sergiu Bacioiu: https://commons.wikimedia.org/wiki/File:Ripple_effect_on_water.jpg
!
National Museum of American History: https://en.wikipedia.org/wiki/File:Cardboard_ballot_box_-_Smithsonian.jpg
!
Christian Frausto Bernal: https://commons.wikimedia.org/wiki/File:MercadodeSanJuandeDios.jpg
!
Brewdog: https://commons.wikimedia.org/wiki/File:San_Francisco_Oakland_Bay_Bridge_New_east_span.jpg
!
Luke Johnson: http://www.theguardian.com/politics/2014/sep/12/mps-expenses-under-fire

38. Offcuts

40. Policy emphasis
shifts over time
!
India, USA, UK - from
democratic to
economic
!
Denmark - efficiency
innovation
!
Kenya - innovation,
tech
!
Philippines -
accountability