Prioritizing Open Data Sets
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Prioritizing Open Data Sets

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Prioritizing Open Data Sets by David Eaves

Prioritizing Open Data Sets by David Eaves

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Prioritizing Open Data Sets Prioritizing Open Data Sets Presentation Transcript

  • 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
  • David Eaves
    www.eaves.ca
    david@eaves.ca
    @daeaves