Open Data Landscape Jeni Tennison Technical Director, ODI.
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Transcript of Open Data Landscape Jeni Tennison Technical Director, ODI.
Open Data Landscape
Jeni TennisonTechnical Director, ODI
Open Data Institute
• Independent institute• £10m over 5 years from TSB• Matching with money from:– paying members– training & professional services– philanthropic investors– research grants
Adoption Curve
Pnautilus at en.wikipedia
Stakeholders
Government Business
Civil Society Researchers
Open Data for GrowthTrend #1
Change in Consumers
• Activists to entrepreneurs• Freedom of Information– right to know– transparency / accountability
• Right to Data–making that information easier to
analyse
• Sustainable publication– enabling businesses to be built
Change in Publishers
• Not just government any more• Third-sector benefits– International Aid Transparency Initiative
(IATI)
• Research benefits–more impact on the world
• Business benefits– reputational– outsourced R&D
Professionalising Open Data
• Enterprise-level tools– CKAN Socrata
• Training– Open Data in Practice training
• Professional services– consultancy & development
• Kitemarks– Open Data Certificate
https://certificates.theodi.org
Levels of Open Data
Expert – information infrastructure
Standard – routine publication
Pilot – trials supporting feedback
Raw – great start at the basics
Impact
• help identifying improvements– OpenStreetMap– transportAPI– legislation.gov.uk– data.police.uk– Ordnance Survey
• help setting bold targets– "Can NHS England be Expert?"– GDS adding targets to spend controls
Need for Business ModelsTrend #2
Selling Data
data customer
licensing
enforcing
selling
salespeople
lawyers
quantity
pric
e
newrevenue
Shifts in Demand
filmmusic
newspaperssoftware
data
Open Data is a Tool
data
enhanced informed
diversedata
Collaboration with Open Data
Trend #3
Collaborate
• distributed effort– reduced cost– enhanced value
• host benefits– improved data– moderation
• examples– MusicBrainz– OpenStreetMap– legislation.gov.uk lower
informedinformed
data
Tools
• Collaboration requires internal use– visualisation– analysis
• Distributed control– scrapers– aggregators
• Version control– "git for data"
Conclusions
Hype Curve
Jeremykemp at en.wikipedia
Navigating the Trough
• Build evidence– deep stories of open data success– capture interest & imagination– underlying hard figures
• Pave cowpaths– build on good practices
• Experiment– no one knows where we'll end up
[email protected] @JeniT
http://theodi.org