Fiona Smith (Open Data Institute) presented at the 2nd International Workshop: Creating Impact with Open Data in Agriculture and Nutrition in The Hague, 11 September 2015.

1. Tools for improving data
publication and use
Fiona Smith (International Development Research)
fiona_ph_smith #ODIHQ

2. What does an
open data-driven
organisation
look like?

3. understand that the value isn’t in the
data itself but in what you do with it
make data part of their core strategy
or a critical part of their strategy
use data to inform what they do and
the decisions they make
invest in training their domain
specialists to understand and use
data to enable specific outcomes
Integrated use of data and
publication of open data
driving decisions and new
business models
Adapted from a slide by Georgia
Phillips
Open data has potential if
organisations…

4. Minimal awareness of open data and no
recognition of its potential value to the
organisation
Ad hoc / tactical / inconsistent use
of open data
Targeted use of open data
amongst specialist teams
Integrated use of data
and publication of open
data driving decisions
and new business
models
● Senior management
championing open data and
sharing stories exemplifying the
benefits and value it can bring
● Teams across the
organisation consistently
using open data to generate
answers to problems, innovate
and operate more effectively
● Training, engagement and
events promoting the value
of open data being shared
internally and externally so
employees and clients feel
encouraged and empowered to
use and publish data
Managed and supported
use of open data across
the organisation.

6. Challenges
Data publisher Data user Policy maker
Challenges
● How to publish
open data?
● How to get more
people to use the
data once
released?
Challenges
● Is this data really
‘open’?
● Is the data
accurate and
trustworthy?
● Is this data
suitable for my
use?
Challenges
● How to track
progress of open
data policy?
● How to encourage
more high-value
data release?
● How to improve
quality?

7. What makes data useable?
Legal
Openly licensed & legally reusable (= ‘open’)
Clear rights statement, detailing any copyrights
Privacy issues addressed
Machine readable rights statement
Practical
Accessible on the web
Discoverable (linked to from other web pages)
Data is timestamped or up to date
Guaranteed timeliness (data always up to date)
Regular backups of data
Quality issues documented
Technical
Single consistent URL for downloading data
Data uses a machine readable format
Data uses open standard machine readable formats
Data published in content appropriate formats
Machine readable provenance documentation
Social
Machine readable metadata (documentation)
Contact details for people to provide feedback and ask questions
Social media accounts used to promote data
Forum or mailing list for users
Dedicated comms team building user community

8. What are Open Data
Certificates?
Tool to make open data transparent and accessible,
connecting publisher and users. Allows you to:
● test against best practice
● earn badges
● search certificates
● access data about data

9. 1. publish data (or thinking about it)
Some rights reserved: http://www.flickr.com/photos/tinou/171803338/sizes/z/in/photostream/

10. 2. earn your certificate
expert
standard
pilot
a great start at the basics of publishing open
data
an exceptional example of information
infrastructure
regularly published open data with robust
support that people can rely on
data users receive extra support from, and can
provide feedback to, the publisher
raw

11. 3. embed your badge

12. Good practice example: data.police.uk

13. We’re publishing open
data, so now what?

14. Open data pathway
● http://pathway.theodi.org
● self-service assessment tool
o answer questions & document evidence to score
progress
o set goals for improvement
o get suggested improvements
● suitable for any organisation

15. http://pathway.theodi.org/statistics

16. Open data maturity model
● http://theodi.org/guides/maturity-model
● the theory behind the tool
o identifies 15 areas of activity
o grouped into 5 themes: process, oversight, finance,
knowledge & community
● two parts:
o the grid is the actual model
o the guide is background documentation and help

17. Maturity Levels
Initial – Inconsistent and ad hoc
Repeatable – Refined processes but isolated within teams
Defined – Standardised cross organisational practices
Managed – Effectiveness of internal process and activities measured
Optimised – Fully integrated and refined process, maximal efficiency

18. Dimension: Data Management Processes
Activity: Data Release Process
Aim: Deliver data more efficiently to customers
1 2 3 4 5
Initial Repeatable Defined Managed Integrated /
Optimised
Little or no published
open data.
Those datasets that
are published are
done so using ad hoc,
possibly manual
processes
A repeatable process
for releasing open
data has been
defined for specific
projects or products,
but there are no
common standards
There is an
organisation wider
standard release
process for publishing
datasets.
This may be tailored
for individual projects.
This has been
adopted for some
published datasets
All datasets are
released according to
the standard
organisational
process
The organisation
collects and monitors
metrics on, e.g. time
taken to release and
refresh datasets, and
acts to optimise the
release process

20. More resources..http://bit.ly/ODIGODAN
● Free online resources
○ Case studies of change management and Startups; written
guides
○ E-learning (forthcoming)
● Networks
○ Open Data Leaders Network
○ Membership network (inc. corporate membership)
○ Node network (city and regional orgs working on open data)
○ Start-up programme
● Support services