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Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
Open Government, Open Data and Data Management - Coradix
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Open Government, Open Data and Data Management - Coradix

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Slides from Coradix Executive Breakfast on Open Government and Open Data - Ottawa, Aug 16, 2012

Slides from Coradix Executive Breakfast on Open Government and Open Data - Ottawa, Aug 16, 2012

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  • 1.  Open  Government  Open  Data  and  Data  Management    
  • 2. •  We  acknowledge  that  people  all  around  the  world   are  demanding  more  openness  in  government;  •  We  accept  responsibility  for  seizing  this  moment  to   strengthen  our  commitments  to  promote   transparency;  •  We  accept  responsibility  to  harness  the  power  of   new  technologies;  •  We  uphold  the  value  of  openness  in  our  engagement   with  ci9zens  
  • 3. The  Open  Data  Landscape  DOB: 2009Thank-youObama
  • 4. Ac9on  Plan  on  Open  Government  Source: Treasury Board of Canada Secretariat
  • 5. Tony  Clement   “Data is Canada’s new Natural Resource” Winnipeg Free Press, July 12, 2012
  • 6. Canadians Government Citizen / Industry ParticipationOpportunities / Benefits Timely Access to Elimination of effort and cost Quality Data responding to ad-hoc requests Economic Innovation Royalties from commercial Gov’t Accountability exploitation of liberated data Loss of Revenue from Data Privacy rights compromised Cost/Capacity of Provisioning Data Lack of skills to manipulate /Challenges / Risks understand (ie non-tech savvy) Lack of consistency of standards- architecture, meta-data, delivery Decisions compromised by relying on erroneous data Quality Issues Misinterpretation of Data Unable to explain contextual questions National / Individual Security
  • 7. NeighborhoodKnowledge LosAngeles (http://nkla.ucla.edu) (NKLA) is awebsite dedicated toproviding public access tovital data and information forneighborhood improvementin Los Angeles.
  • 8. Digital  Economy  “The  total  size  of  digital  economy  is  es=mated  at  $20.4  trillion,  equivalent  to  roughly  13.8%  of  all  sales  flowing  through  the  world  economy.”  Source:  The  New  Digital  Economy  How  it  will  transform  business,  Oxford  Economics  
  • 9. Source: McKinsey Global Institute, Big Data Next Frontier for Innovation
  • 10. Volume  of  Data  
  • 11. Velocity  of  Data  
  • 12. “Big  Brother  is  Watching”  
  • 13. Variety  of  Data  
  • 14. Data  Analysis  Source: AIIM Industry Watch, Big Data
  • 15. Content  Management  Source: AIIM Industry Watch, Big Data
  • 16. Implica9ons  •  Governance  •  Insight/Analy9cs  •  Privacy  •  Discoverability    •  Security  •  IP    
  • 17. Does  Big  Data  =  More  Technology?  
  • 18. Big  Data  Challenges   •  Source:  AIIM  Industry  Watch,  Big  Data  Source: AIIM Industry Watch, Big Data
  • 19. They  set  out  to  buy  this  
  • 20. And  this  is  what  they  got  
  • 21. Data  Quality  Problems  are  not   cheap  
  • 22. The  ERP  Experience  
  • 23. Costs
  • 24. Peopleso[  Anyone  ?  
  • 25. Peopleso[  Anyone  ?  
  • 26. Tank,  Tanks,  Tankers,  Tanked  
  • 27. Legal  Challenges  
  • 28. Result  
  • 29. This hitsclose tohome
  • 30. Professional  Data  Management  is  new  
  • 31. Data  Blueprint  –  Na9onal  Cancer   Ins9tute  Re-­‐architec9ng  Data  
  • 32. Data  Management  Planning  Online  
  • 33. State  of  Colorado  •  How  Data  Management  Improved   –  The  EDM  program  helped  facilitate  much  greater  communica=on  between   business  and  IT   –  A  robust  Governance  process  and  commiOee  structure  was  established   –   A  set  of  Data  Principles  were  developed  and  accepted   –  Specific  ini=a=ves  were  undertaken  in  the  areas  of  Master  Data,  Architecture   and  Meta-­‐data  •  How  the  Business  Issue  was  addressed   –  Colorado  Unique  Personal  Iden=fier  (CUPID)  MDM  program  generated   benefits  in  quality,  sharing,  understanding,  security  and  stewardship   –  Educa=on  Longitudinal  Data  System  Architecture  ini=a=ve  reduced  the  gaps  in   school  readiness  and  academic  achievement  between  popula=ons  of  children   –  Improved  client-­‐service  through  access  to  integrated  health  informa=on   –  Improved  policy  making  through  a  more  informed  process  
  • 34. Recognize  this  ?   Architectural Bubble Chart
  • 35. Enterprise  Architecture  John Zachman’s Seminalarticle in 1987 launchedEnterprise Architecture
  • 36. W3C  Linking  Open  Data  
  • 37. DBpedia   A community-based effort structure Wikipedia Semantic techniques extend this to structured models
  • 38. For   Against  •  "Data  belong  to  the  human  race”   •  Government  funding  may  not  be  used  to  duplicate  or  •  Public  money  was  used  to  fund  the   challenge  the  ac=vi=es  of  the  private  sector   work  and  so  it  should  be  universally   •  Governments  have  to  be  accountable  for  the  efficient   available.   use  of  taxpayers  money:  If  public  funds  are  used  to  •  It  was  created  by  or  at  a  government   aggregate  the  data  and  if  the  data  will  bring  commercial   ins=tu=on   (private)  benefits  to  only  a  small  number  of  users,  the  •  Facts  cannot  legally  be  copyrighted.   users  should  reimburse  governments  for  the  cost  of  •  Sponsors  of  research  do  not  get  full   providing  the  data.   value  unless  the  resul=ng  data  are   •  The  government  gives  specific  legi=macy  for  certain   freely  available.   organisa=ons  to  recover  costs  (Stats  Canada)  •  Data  are  required  for  the  smooth   •  Privacy  concerns  may  require  that  access  to  data  is   process  of  running  communal   limited  to  specific  users  or  to  sub-­‐sets  of  the  data.   human  ac=vi=es  (map  data,  public   •  Collec=ng,  cleaning,  managing  and  dissemina=ng  data   ins=tu=ons).   are  typically  labour-­‐  and/or  cost-­‐intensive  processes  -­‐  •  In  scien=fic  research,  the  rate  of   whoever  provides  these  services  should  receive  fair   discovery  is  accelerated  by  beOer   remunera=on  for  providing  those  services.   access  to  data.   •  O]en,  targeted  end-­‐users  cannot  use  the  data  without   addi=onal  processing  (analysis,  apps  etc.)  
  • 39. Canadians Government Citizen / Industry ParticipationOpportunities / Benefits Timely Access to Elimination of effort and cost Quality Data responding to ad-hoc requests Economic Innovation Royalties from commercial Gov’t Accountability exploitation of liberated data Loss of Revenue from Data Privacy rights compromised Cost/Capacity of Provisioning Data Lack of skills to manipulate /Challenges / Risks understand (ie non-tech savvy) Lack of consistency of standards- architecture, meta-data, delivery Decisions compromised by relying on erroneous data Quality Issues Misinterpretation of Data Unable to explain contextual questions National / Individual Security
  • 40. Addressing  the  Challenges,  Realizing  the  Opportunity   Decisions compromised by Quality Issues relying on erroneous data Data Quality Management EDM   Privacy rights compromised Governance   Enterprise Data Security National / Individual SecurityLack of consistency of standards- Master-Data Management Open Dataarchitecture, meta-data, delivery Delivery Misinterpretation of Data Meta-Data Management Platform Can’t address contextual questions Data Architecture Timely Access to Lack of skills to Quality Data manipulate / understand EDM Competency Center Loss of Revenue Cost/Capacity of Citizen / Industry from Data Provisioning Data Participation Royalties from commercial Elimination of effort and cost Economic Innovation exploitation of liberated data responding to ad-hoc requests

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