Open Government, Open Data and Data Management - Coradix
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The document discusses open data and data management. It acknowledges demands for more government transparency and outlines commitments to promote openness. It also recognizes the power of new technologies to harness data. Challenges of open data include privacy, data quality, skills and understanding data. Opportunities include economic innovation, accountability and timely access to quality data. Effective data management through governance, security, architecture and standards can address challenges and realize opportunities.
![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
taxpayer's
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.)](https://image.slidesharecdn.com/coradixdatamanagementv5rm-120817093301-phpapp01/85/Open-Government-Open-Data-and-Data-Management-Coradix-43-320.jpg)
Open Government, Open Data and Data Management - Coradix
- 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: 2009 Thank-you Obama
- 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 Participation Opportunities / 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. Neighborhood Knowledge Los Angeles (http:// nkla.ucla.edu) (NKLA) is a website dedicated to providing public access to vital data and information for neighborhood improvement in 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
- 18. Does Big Data = More Technology?
- 19. Big Data Challenges • Source: AIIM Industry Watch, Big Data Source: AIIM Industry Watch, Big Data
- 21. They set out to buy this
- 22. And this is what they got
- 23. Data Quality Problems are not cheap
- 26. Costs
- 29. Tank, Tanks, Tankers, Tanked
- 30. Legal Challenges
- 31. Result
- 35. Professional Data Management is new
- 36. Data Blueprint – Na9onal Cancer Ins9tute Re-‐architec9ng Data
- 37. Data Management Planning Online
- 38. 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
- 39. Recognize this ? Architectural Bubble Chart
- 40. Enterprise Architecture John Zachman’s Seminal article in 1987 launched Enterprise Architecture
- 41. W3C Linking Open Data
- 42. DBpedia A community-based effort structure Wikipedia Semantic techniques extend this to structured models
- 43. 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 taxpayer's 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.)
- 44. Canadians Government Citizen / Industry Participation Opportunities / 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
- 45. 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 Security Lack of consistency of standards- Master-Data Management Open Data architecture, 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