1. Transparency and Open Data:
Why Bother?
Being also a discourse on some lessons learnt
Professor Nigel Shadbolt FREng
7th June 2012
European Data Forum, Copenhagen
Nigel Shadbolt

2. open the data…

3. and the applications follow…

4. at all scales…

5. around the world…

6. leading to…
• Improved transparency &
accountability
• Better Public Services
• Participation… people enhance,
improve, capture the data
• Improved efficiency
• Creation of social value
• Economic value, innovation and
growth

7. Lesson: Open Data…
should be non-partisan

8. “Our ambition is to “We are determined to go further in breaking
become the world leader down the walled garden of government,
in open data, and using technology and information to provide
accelerate the greater transparency…”
accountability revolution
that the internet age has
made possible..
“My aim is clear: to make
the provision of data (with
“Greater transparency across reasonable formats and
Government is at the heart of our licenses) a routine task of
shared commitment to enable the public administrations.”
public to hold politicians and public
bodies to account

9. Lesson: Open Data…
needs a steady stream of
success

12. Lesson: Open Data…
is not a technical problem

13. It is about changing behaviour
UK Public Data
Principles

14. However…
★ Put your data on the Web with an Open Licence
★★ Make it available as structured data
★★★ Use open, standard formats
★★★★ Use URIs to identify things
★★★★★ Link your data to other people’s data

15. Create, Use and Share URIs
• National digital
infrastructure being built
• URIs for schools, roads,
bus stops, post codes,
admin boundaries...
• Some of the data links
across and connects
other data together
• Key data link points exist

16. Create, Use and Share URIs
• National digital
infrastructure being built
• URIs for schools, roads,
bus stops, post codes,
admin boundaries...
• Some of the data links
across and connects
other data together
• Key data link points exist

17. Create, Use and Share URIs
• Schools
• Post-codes
• Government posts
• Ministers
• Bus stops
• :
• :

18. Lesson: Open Data…
if it doesn’t scale it will fail

19. Datasets on data.gov.uk over time

20. Open Data – the network effect
• Network effects
– Accessibilitly
– Popularisation
– Centreless
– Timeliness
– Convergence
Courtesy Mathew Hurst

21. Lesson: Open Data…
needs location, location, location

22. www.ordnancesurvey.co.uk/opendata
See also: Linked data http://www.ordnancesurvey.co.uk/opendata/linkeddata.html

23. the connective tissue of open data

24. 24

26. Lesson: Open Data…
release data that matters

27. UK Reported Crime Data
• A tough data set to
release
• All reported crime each
month
• By crime type
• At the street level
• Police now use the
apps themselves

31. From Schools to Arterial Surgery

32. Lesson: Open Data…
must have a balanced ecosystem

33. Source Deloitte LLP

34. Research &
h
Academic c
• The Network Effect Cluster
r
• for data, people and organisations
• A Focal Point
• coordinate, convene, link and
integrate
Business
Cluster
r
s
ODI
I Public Sector
c
Clusterr
r
• The Power of Open
•
Tech City
h y
Standards, Data, Licences, SW
• Open Data as a Platform for
Interna onall
Agenciess
• Government Cluster
r
• Business
• Research

35. “The vision is to establish the Open Data Institute as a world leading
centre to innovate, exploit and research the opportunities for the UK
created by the Government’s Open Data policy.”
• Business Innovation
• Public Sector Innovation
• Training the Open Data Generation
• Developing and Researching Open Data
• Developing Open Data Standards and Policies
• Advisor to Government & International Collaboration

36. OGD 2.0
• We haven’t worked out
how to close the
feedback loops
• Publish out
• Acquire or Enhance
• Write Back

37. Lesson: Open Data…
needs Business

38. Economic Value, Innovation and Growth

39. 39

40. 40

41. Lesson: Open Data…
isn’t everything

42. Varieties of Data
• Big - Small
• Public – Private
• Open - Closed
• Personal - Non-Personal
• Anonymous - Identified
• Aggregate - Individual
© 2012 Deloitte Global Services Limited

43. midata
Nigel Shadbolt

44. Personal Data Asset Revolution…

45. Lesson: Open Data…
will need defending

46. Challenges
• Infrastructure
• Quality
• Interpretation
• Security and Privacy
• Evidence of impact
• Sir Humphrey 2.0

47. A sample of “data hugging” excuses
• It’s held separately by n different organisations, and we can’t join it up
• It will make people angry and scared without helping them
• It is technically impossible
• We do not own the data
• The data is just too large to be published and used
• Our website cannot hold files this large
• We know the data is wrong
• We know the data is wrong, and people will tell us where it is wrong
• We know the data is wrong, and we will waste valuable resources inputting the corrections people
send us
• People will draw superficial conclusions from the data without understanding the wider picture
• People will construct league tables from it
• It will generate more Freedom of Information requests
• It might be combined with other data to identify individuals/sensitive information
• It will cost too much to put it into a standard format
• Our IT suppliers will charge us a fortune to do an ad hoc extract

48. A sample of “data hugging” excuses
• It’s held separately by n different organisations, and we can’t join it up
• It will make people angry and scared without helping them
• It is technically impossible
• We do not own the data
• • All these sometimes have some truth in them
The data is just too large to be published and used
• • website they rationalise
OurOftencannot hold files this large the official fear of the unknown
• • know the data is wrong
We Data owners need to be helped through
• • know the data & precedent are your it is wrong
We Example is wrong, and people will tell us wherefriends
• • know first is wrong, and we will waste valuable resources not licence
We For the dataphase, compromise on data inputting the corrections people
send us
• People will draw superficial conclusions from the data without understanding the wider picture
• People will construct league tables from it
• It will generate more Freedom of Information requests
• It might be combined with other data to identify individuals/sensitive information
• It will cost too much to put it into a standard format
• Our IT suppliers will charge us a fortune to do an ad hoc extract

49. Lesson: Open Data…
keep reminding them

52. Open Data and the Power of Open
never one driver nor one reason
•Open Licences
•Open Standards
•Open Data
•Open Data Principles
•Open Participation
•Open Minds