Steve Peters: Monsters and Transformers

This deck was used to support Steve's talk at http://power-of-data-2017.swirrl.com/ about how quality data analysis can make for more efficient and effective policy and service delivery. From data monsters, who breathe the fire of expensive licences and hide data in caves, to data engineers who are integral to good data infrastructure, he provides real-world examples of how data analysis has led to a better understanding and measuring the impact of complex real-world problems across authorities.

Transcript

1. Is  it  a  monster,  or  a  transformer?
   What’s that coming over the hill?
   Steve  Peters
   @Open_Data 15th June  2017
   Presentation  to  Swirrl’s “Unlocking  the  power  of  government  data”  
   conference
   

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3. Fixing  our  broken  housing  market
   Data is key to understanding DCLG’s
   policy choices and outcomes
   Supporting  more  effective  &  efficient  local  services
   For  example….
   

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4. Finding our way through the data swamp
   

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5. Get  the  right  data,  more  
   easily
   Use  Data Publish  Data
   Automated  for  easy  use  and  
   integration  into  
   development  and  evaluation  
   of  policy
   Accessible,  open  and  
   collaborative
   Tools  and  
   Technology
   People  and  
   Skills
   DCLG Data Programme
   Acquire  Data
   Governance
   

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6. Local  Brownfield  Land  Registers
   We are making progress…
   http://www.legislation.gov.uk/uksi/2017/403/schedule/2/made
   https://mappinggm.org.uk/gmodin/
   Acquire  Data
   

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7. Interactive  performance  dashboards,  to  automatically  display  key  metrics  
   We are making progress…
   Use  Data
   

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8. Publish  Data
   We are making progress…
   

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9. We are making progress…
   Skills  and  Capability
   target  building
   buildings  within  100m
   touching  buildings  with  a  
   height  difference  >  3  metres
   touching  
   buildings
   We  are  beginning  to  apply  new  Data  Science  techniques  to  enrich  our  data  sources,  analysis  and  insights:  for  
   example….
   Scope  for  Building  upwards…
   Locations  of  Mosques
   

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10. We are making progress…
    Explore,  visualise  and  
    extract  our  data  in-­‐situ….
    Connect  directly  to  our  data  (via  our  APIs)  and  
    re-­‐use  it  in  your  website  
    Tools  and  infrastructure
    Building  a  trusted  and  
    maintained  source  of  DCLG  
    data  in  fully  open,  re-­‐usable  
    (linked  data)  formats
    

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11. Where next?
    But…
    How  best  to  clarify  
    where  we  want  to  
    be?
    And  how  we’ll  get  
    there  within  reality  
    of  significant  
    resource  
    constraints.
    

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12. needs
    YOU
    Our data
    Where next?
    Mario  
    says
    

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