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Prioritizing Open Data Sets by David Eaves
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Prioritizing Open Data Sets
3 simple rules
Rule 1: Look Backward, Look Sideways
• Look Backwards:– Most governments know what data and information has
been heavily requested by the public in the past– Past requests reveal both latent demand and potential
community– This is a good place to start
• Look Sideways:– Look at requests other governments make public, there are
trends– Examples of data sets that regularly top the list:
procurement, budget, crime, transit and transportation data
Rule 2: Target Policy Objectives
• Release data that will advance specific policy goals– Health– Accountability/anti-corruption– Education– Transport– Environment
No one visits your website
This is Vancouver Coastal Health’s Restaurant Inspection site.
No one visits it.
Repeat, no one visits your website
The only time anyone searches for restaurant inspection data...
..is after they’ve been food poisoned
e.g. Health Objectives
• When citizens see restaurant inspection data– Consumer behavior drives compliance:
• Well rated restaurants experience more business• Badly rated restaurants experience less business
– Consumer behavior and compliance create savings:• In Los Angeles County, Emergency Room Visits due to food
born related illnesses declined by 16% in year one, 6% in year two, 3% in year three
– Focused transparency can improve health outcomes and lower costs
Put the data where the citizen is
Rule 2: This is your goal
Rule 3: Partner when you must, Follow when you can
• Open data in structures that are common across multiple jurisdictions is much, much more powerful
• The power of a common structure: the General Transit Feed Specification allows access to transit schedules in 160+ cities in dozens of languages in Google Maps
• Copy others structure whenever you can
Rule 3: Partner when you must, Follow when you can
• Rule 3a:– Help foster cross jurisdictional standards by
copying other people’s data structures• Rule 3b:– When there is no standard, find private sector or
community actors who want to consume your data, and get them to help you create the data structure
– Tell the world about your structure!
Partnering• Creating a new standard requires scale, access to a
large user base, and an ability to compromise. E.g. For Transit, Portland engaged Google
• 4 Do’s and Don’ts– DON’T start by forming a standards committee, we
don’t have 10 years to spend coming to agreement– DO find a partner with scale and market penetration– DON’T promise exclusivity to that partner– DO create a governance model after the standard
succeeds