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Opn a in h ao
           e D t C icg
               a
         Big Data for the Common
                   Good
            Virginia C arlson
            •




B ad Asc t no P b D t U es
 o r , so iaio f u lic aa sr
T e a - re W r
 h D tD ivn ol
     a        d
G vrmn D cmn
 oe et ou et
   n        s
S ut e D t
tc r a
 r ud a
G v .0
 o2
Data Types
  Operational data
     citizen services

  Administrative data
     internal workings

 Statistical data
     demo, econ, data
31 a
1 Cll
    s
Bil gnpc n
 ud I et s
   in s io
H ah et s
 el C n r
   t   e
Pb Me g oe
 ul et N t
  ic in   s
G v ml e Slie
 o E p ye ars
      o    a
S ut e D t
tc r a
 r ud a
• Six months
• Four partners
• Three rounds
• $300,000
• Data curation, public outreach
• Judges, public voting
• Build on previous competitions
D tSiett
 a cn s
  a   is!
Benefits!
M r Po lU in M r D t
 oe ep sg oe a
       e           a
P t tl o mny T c
 oe iaC m uit+ eh
   n
Bek o nn raSo
 r D w Ie lil
  a     tn   s
Broader Goals?
• Accountability
  • Lack of feedback mechanisms
• Efficiencies
  • Procurement
  • Lack of internal buy-in
• Innovation
  • SpotHero
  • BrightScope
C ne s
 ocrn
C r io
 ua n
   t
Fnin Pioits
ud g r rie
2012 - Open Data in Chicago

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2012 - Open Data in Chicago

Editor's Notes

  1. The halcyon age of data! Data is more prevalent than ever and helps us make better decisions everywhere - better decisions about what movies to watch, better decisions about how to get from A to B, better decisions about who to be friends with – everything.
  2. Part of open government movement (Gov 2.0), fed as well as local, but we’ll just look at local for now. Data for efficiency, accountability and innovation.
  3. Data scientists! You scrape, clean, analyze, visualize, build tools on data all day! And more than that, you do it all night! You’re at this conference you’re going to hackathons you’re excited to help! This is the first year more keynotes than not have been talking about doing more with the skills and data we have (quote some). So how do we get the excitement of the data science community to bear on the social sector?
  4. Code for America
  5. Curation really really difficult. Impulse is to do something groovy. Data illiteracy. Tale of Look at Cook.
  6. And at the national level, will “open data” replace statistical data?