SlideShare una empresa de Scribd logo
Open Data
Challenges
Paul Stone, NZ Open Government Data Programme,
Data Leadership and Capability, Stats NZ.
ODC Implementation Working Group, November 2019
Quality
Some data is better than
no data…
1. Good context
• Purpose of collection
• Method of collection
• Known strengths and
weaknesses
2. Opportunity for
feedback
3. Creative Commons
Licence
Image: Quality by Nick Youngson CC BY-SA 3.0 Alpha Stock Images
Accurac
y
• Context – inform how data is
collected and for what purpose.
• Be upfront about limitations in
the data or risk of human error
• Create a feedback loop - invite
data users to contribute and help
lift the accuracy of the data
Creative Commons
Licence – not liable for
quality
THE LICENSOR OFFERS THE LICENSED MATERIAL AS-IS AND
AS-AVAILABLE, AND MAKES NO REPRESENTATIONS OR
WARRANTIES OF ANY KIND CONCERNING THE LICENSED
MATERIAL… THIS INCLUDES… FITNESS FOR A PARTICULAR
PURPOSE…
Ignorant misuse
Context, context, context.
• Describe the collection
method and purpose
• Describe well the
variables in the data and
what they mean
• Don’t assume everyone is
ignorant.
Malicious
misuse Don’t let one bad
potential use prevent
the opportunity for
many good uses
Further clause on
liability in CC licence.
Creative Commons
Licence – not liable for
reuse (misuse)
…IN NO EVENT WILL THE LICENSOR BE LIABLE TO YOU ON
…DAMAGES ARISING OUT OF THIS PUBLIC LICENSE OR USE
OF THE LICENSED MATERIAL…
Reputation
• Transparency builds trust
• Good context reduces
misunderstanding
• An opportunity to contribute to
data quality is an opportunity to
engage and build relationships
All good reasons to release the
data – with good context.
Lack of resources
• Open by design
• Prioritise
o Alignment to organisational
strategy
o demand
• Don’t re-invent the wheel
• Start small
Lack of technology
• Keep it simple
• Start small
• Every agency has a website
• Most agencies have API
capability but just don’t use it
Privacy
Critical for maintaining
trust.
Toolbox:
• Privacy Impact Assessment
• Confidentialisation
• Reference Scenarios
(coming)
Culture
Probably the biggest challenge.
Shifting the mindset of the whole
organisation to open by default.
Challenges are manageable, not
insurmountable.
Key messages – like “we are
custodians of a public data asset”
Doesn’t AI make too
much data
dangerous?
Data considerations
Provenance
and
context
Indigenous
Data
Sovereignty
Data EthicsData Bias
Licensing
attribution
Don’t spray and walk away…
Twitter: @opendatanz
opendata@stats.govt.nz
Paul.stone@stats.govt.nz
Data.govt.nz
Contact

Más contenido relacionado

La actualidad más candente

Information as Galaxy
Information as GalaxyInformation as Galaxy
Information as Galaxy
Galaxy Consulting
 
A safer approach to build recommendation systems on unidentifiable data
A safer approach to build recommendation systems on unidentifiable dataA safer approach to build recommendation systems on unidentifiable data
A safer approach to build recommendation systems on unidentifiable data
Kishor Datta Gupta
 
Jules Polonetsky: Ethics & Privacy & Strategy in the Age of Big Data
Jules Polonetsky: Ethics & Privacy & Strategy in the Age of Big DataJules Polonetsky: Ethics & Privacy & Strategy in the Age of Big Data
Jules Polonetsky: Ethics & Privacy & Strategy in the Age of Big Data
Balanced Scorecard Institute-Spider Strategies Strategy Execution Summit 2015
 
Data analytics with managerial application ass 3
Data analytics with managerial application ass 3Data analytics with managerial application ass 3
Data analytics with managerial application ass 3
Nishant Kumar
 
Wikistrat-Executive-Summary-2015
Wikistrat-Executive-Summary-2015Wikistrat-Executive-Summary-2015
Wikistrat-Executive-Summary-2015Esa K. Vierikko
 
Supporting decisions with ML
Supporting decisions with MLSupporting decisions with ML
Supporting decisions with ML
Megan Neider
 
The MEASURE project : Measuring Software Engineering, Manrique Lopez, OW2con'...
The MEASURE project : Measuring Software Engineering, Manrique Lopez, OW2con'...The MEASURE project : Measuring Software Engineering, Manrique Lopez, OW2con'...
The MEASURE project : Measuring Software Engineering, Manrique Lopez, OW2con'...
OW2
 
Got Chaos? Extracting Business Intelligence from Email with Natural Language ...
Got Chaos? Extracting Business Intelligence from Email with Natural Language ...Got Chaos? Extracting Business Intelligence from Email with Natural Language ...
Got Chaos? Extracting Business Intelligence from Email with Natural Language ...
Digital Reasoning
 
Data & Digital Ethics - CDAO Conference Sydney 2018
Data & Digital Ethics - CDAO Conference Sydney 2018Data & Digital Ethics - CDAO Conference Sydney 2018
Data & Digital Ethics - CDAO Conference Sydney 2018
Kate Carruthers
 
What do we do with all this big
What do we do with all this big What do we do with all this big
What do we do with all this big
Rajeev Ranjan Dwivedi
 

La actualidad más candente (10)

Information as Galaxy
Information as GalaxyInformation as Galaxy
Information as Galaxy
 
A safer approach to build recommendation systems on unidentifiable data
A safer approach to build recommendation systems on unidentifiable dataA safer approach to build recommendation systems on unidentifiable data
A safer approach to build recommendation systems on unidentifiable data
 
Jules Polonetsky: Ethics & Privacy & Strategy in the Age of Big Data
Jules Polonetsky: Ethics & Privacy & Strategy in the Age of Big DataJules Polonetsky: Ethics & Privacy & Strategy in the Age of Big Data
Jules Polonetsky: Ethics & Privacy & Strategy in the Age of Big Data
 
Data analytics with managerial application ass 3
Data analytics with managerial application ass 3Data analytics with managerial application ass 3
Data analytics with managerial application ass 3
 
Wikistrat-Executive-Summary-2015
Wikistrat-Executive-Summary-2015Wikistrat-Executive-Summary-2015
Wikistrat-Executive-Summary-2015
 
Supporting decisions with ML
Supporting decisions with MLSupporting decisions with ML
Supporting decisions with ML
 
The MEASURE project : Measuring Software Engineering, Manrique Lopez, OW2con'...
The MEASURE project : Measuring Software Engineering, Manrique Lopez, OW2con'...The MEASURE project : Measuring Software Engineering, Manrique Lopez, OW2con'...
The MEASURE project : Measuring Software Engineering, Manrique Lopez, OW2con'...
 
Got Chaos? Extracting Business Intelligence from Email with Natural Language ...
Got Chaos? Extracting Business Intelligence from Email with Natural Language ...Got Chaos? Extracting Business Intelligence from Email with Natural Language ...
Got Chaos? Extracting Business Intelligence from Email with Natural Language ...
 
Data & Digital Ethics - CDAO Conference Sydney 2018
Data & Digital Ethics - CDAO Conference Sydney 2018Data & Digital Ethics - CDAO Conference Sydney 2018
Data & Digital Ethics - CDAO Conference Sydney 2018
 
What do we do with all this big
What do we do with all this big What do we do with all this big
What do we do with all this big
 

Similar a Managing the Barriers to an Open Data Culture

identification, definition and setting up the project
identification, definition and setting up the projectidentification, definition and setting up the project
identification, definition and setting up the project
Nimra zaman
 
Data Policy for Open Science
Data Policy for Open ScienceData Policy for Open Science
Data Policy for Open Science
Research Data Alliance
 
Data Policy for Open Science
Data Policy for Open ScienceData Policy for Open Science
Data Policy for Open Science
Mark Parsons
 
Generating Big Value from Big Data
Generating Big Value from Big DataGenerating Big Value from Big Data
Generating Big Value from Big Data
Brendan Aldrich
 
Privacy by Design - taking in account the state of the art
Privacy by Design - taking in account the state of the artPrivacy by Design - taking in account the state of the art
Privacy by Design - taking in account the state of the art
James Mulhern
 
Wanted By The ODI!
Wanted By The ODI!Wanted By The ODI!
Wanted By The ODI!lisbk
 
[AIIM18] GDPR: whose job is it now? - Paul Lanois
[AIIM18] GDPR: whose job is it now? - Paul Lanois[AIIM18] GDPR: whose job is it now? - Paul Lanois
[AIIM18] GDPR: whose job is it now? - Paul Lanois
AIIM International
 
Towards data responsibility - how to put ideals into action
Towards data responsibility - how to put ideals into actionTowards data responsibility - how to put ideals into action
Towards data responsibility - how to put ideals into action
Mindtrek
 
Big Data Brown Bag
Big Data Brown BagBig Data Brown Bag
Big Data Brown Bagusmanqureshi
 
ETHICAL ISSUES WITH CUSTOMER DATA COLLECTION
ETHICAL ISSUES WITH CUSTOMER DATA COLLECTIONETHICAL ISSUES WITH CUSTOMER DATA COLLECTION
ETHICAL ISSUES WITH CUSTOMER DATA COLLECTIONPranav Godse
 
Examining the Big Data Frontier
Examining the Big Data FrontierExamining the Big Data Frontier
Examining the Big Data Frontier
GovLoop
 
Data science and ethics in fundraising
Data science and ethics in fundraisingData science and ethics in fundraising
Data science and ethics in fundraising
James Orton
 
Big Data, Big Investment
Big Data, Big InvestmentBig Data, Big Investment
Big Data, Big Investment
GGV Capital
 
Dark Data: Where the Future Lies
Dark Data: Where the Future LiesDark Data: Where the Future Lies
Dark Data: Where the Future Lies
Vince Kellen, Ph.D.
 
Practical Data Management Plans
Practical Data Management PlansPractical Data Management Plans
Practical Data Management Plans
IUPUI
 
Data mining and privacy preserving in data mining
Data mining and privacy preserving in data miningData mining and privacy preserving in data mining
Data mining and privacy preserving in data miningNeeda Multani
 
Module 3 - Improving Current Business with External Data- Online
Module 3 - Improving Current Business with External Data- Online Module 3 - Improving Current Business with External Data- Online
Module 3 - Improving Current Business with External Data- Online
caniceconsulting
 
IAC22 Safe Tech Audit Presentation Noreen Whysel.pptx
IAC22 Safe Tech Audit Presentation Noreen Whysel.pptxIAC22 Safe Tech Audit Presentation Noreen Whysel.pptx
IAC22 Safe Tech Audit Presentation Noreen Whysel.pptx
Noreen Whysel
 
Open Data Myths: busted!
Open Data Myths: busted!Open Data Myths: busted!
Open Data Myths: busted!
Cofluence
 
Ethics In DW & DM
Ethics In DW & DMEthics In DW & DM
Ethics In DW & DM
abethan
 

Similar a Managing the Barriers to an Open Data Culture (20)

identification, definition and setting up the project
identification, definition and setting up the projectidentification, definition and setting up the project
identification, definition and setting up the project
 
Data Policy for Open Science
Data Policy for Open ScienceData Policy for Open Science
Data Policy for Open Science
 
Data Policy for Open Science
Data Policy for Open ScienceData Policy for Open Science
Data Policy for Open Science
 
Generating Big Value from Big Data
Generating Big Value from Big DataGenerating Big Value from Big Data
Generating Big Value from Big Data
 
Privacy by Design - taking in account the state of the art
Privacy by Design - taking in account the state of the artPrivacy by Design - taking in account the state of the art
Privacy by Design - taking in account the state of the art
 
Wanted By The ODI!
Wanted By The ODI!Wanted By The ODI!
Wanted By The ODI!
 
[AIIM18] GDPR: whose job is it now? - Paul Lanois
[AIIM18] GDPR: whose job is it now? - Paul Lanois[AIIM18] GDPR: whose job is it now? - Paul Lanois
[AIIM18] GDPR: whose job is it now? - Paul Lanois
 
Towards data responsibility - how to put ideals into action
Towards data responsibility - how to put ideals into actionTowards data responsibility - how to put ideals into action
Towards data responsibility - how to put ideals into action
 
Big Data Brown Bag
Big Data Brown BagBig Data Brown Bag
Big Data Brown Bag
 
ETHICAL ISSUES WITH CUSTOMER DATA COLLECTION
ETHICAL ISSUES WITH CUSTOMER DATA COLLECTIONETHICAL ISSUES WITH CUSTOMER DATA COLLECTION
ETHICAL ISSUES WITH CUSTOMER DATA COLLECTION
 
Examining the Big Data Frontier
Examining the Big Data FrontierExamining the Big Data Frontier
Examining the Big Data Frontier
 
Data science and ethics in fundraising
Data science and ethics in fundraisingData science and ethics in fundraising
Data science and ethics in fundraising
 
Big Data, Big Investment
Big Data, Big InvestmentBig Data, Big Investment
Big Data, Big Investment
 
Dark Data: Where the Future Lies
Dark Data: Where the Future LiesDark Data: Where the Future Lies
Dark Data: Where the Future Lies
 
Practical Data Management Plans
Practical Data Management PlansPractical Data Management Plans
Practical Data Management Plans
 
Data mining and privacy preserving in data mining
Data mining and privacy preserving in data miningData mining and privacy preserving in data mining
Data mining and privacy preserving in data mining
 
Module 3 - Improving Current Business with External Data- Online
Module 3 - Improving Current Business with External Data- Online Module 3 - Improving Current Business with External Data- Online
Module 3 - Improving Current Business with External Data- Online
 
IAC22 Safe Tech Audit Presentation Noreen Whysel.pptx
IAC22 Safe Tech Audit Presentation Noreen Whysel.pptxIAC22 Safe Tech Audit Presentation Noreen Whysel.pptx
IAC22 Safe Tech Audit Presentation Noreen Whysel.pptx
 
Open Data Myths: busted!
Open Data Myths: busted!Open Data Myths: busted!
Open Data Myths: busted!
 
Ethics In DW & DM
Ethics In DW & DMEthics In DW & DM
Ethics In DW & DM
 

Más de enotsluap

Auckland meetup nov 19
Auckland meetup nov 19Auckland meetup nov 19
Auckland meetup nov 19
enotsluap
 
Open and transparent practices through open data
Open and transparent practices through open dataOpen and transparent practices through open data
Open and transparent practices through open data
enotsluap
 
Hawke's Bay Chamber
Hawke's Bay ChamberHawke's Bay Chamber
Hawke's Bay Chamber
enotsluap
 
Open Data - What and Why
Open Data - What and WhyOpen Data - What and Why
Open Data - What and Why
enotsluap
 
Open Data and Social Enterprise
Open Data and Social EnterpriseOpen Data and Social Enterprise
Open Data and Social Enterprise
enotsluap
 
Hawke's Bay Open Data Conference - 2 May 2019
Hawke's Bay Open Data Conference - 2 May 2019Hawke's Bay Open Data Conference - 2 May 2019
Hawke's Bay Open Data Conference - 2 May 2019
enotsluap
 
Ipanz april 2019
Ipanz   april 2019Ipanz   april 2019
Ipanz april 2019
enotsluap
 
Open data 2019
Open data 2019Open data 2019
Open data 2019
enotsluap
 
Auckland IPANZ New Professionals
Auckland IPANZ New ProfessionalsAuckland IPANZ New Professionals
Auckland IPANZ New Professionals
enotsluap
 
Symbiotic relationships: bringing about change for open data together
Symbiotic relationships: bringing about change for open data togetherSymbiotic relationships: bringing about change for open data together
Symbiotic relationships: bringing about change for open data together
enotsluap
 
Data Driven Meetup Wellington
Data Driven Meetup WellingtonData Driven Meetup Wellington
Data Driven Meetup Wellington
enotsluap
 
NZ Analytics Forum - Open Data Landscape
NZ Analytics Forum - Open Data LandscapeNZ Analytics Forum - Open Data Landscape
NZ Analytics Forum - Open Data Landscape
enotsluap
 
Open Data Meetups - Auckland and Christchurch
Open Data Meetups - Auckland and ChristchurchOpen Data Meetups - Auckland and Christchurch
Open Data Meetups - Auckland and Christchurch
enotsluap
 
IOGDC 2012 presentation (Paul Stone)
IOGDC 2012 presentation (Paul Stone)IOGDC 2012 presentation (Paul Stone)
IOGDC 2012 presentation (Paul Stone)
enotsluap
 
Hawkes bay local governent workshop 9 december 2015
Hawkes bay local governent workshop 9 december 2015Hawkes bay local governent workshop 9 december 2015
Hawkes bay local governent workshop 9 december 2015
enotsluap
 
Open Government Data - Inner City Association, Wellington
Open Government Data - Inner City Association, WellingtonOpen Government Data - Inner City Association, Wellington
Open Government Data - Inner City Association, Wellington
enotsluap
 
Govis 2015 building trust through transparency and open data
Govis 2015   building trust through transparency and open dataGovis 2015   building trust through transparency and open data
Govis 2015 building trust through transparency and open data
enotsluap
 
Open data and innovation in my community
Open data and innovation in my communityOpen data and innovation in my community
Open data and innovation in my community
enotsluap
 
Open data - GIG April 2015
Open data - GIG April 2015Open data - GIG April 2015
Open data - GIG April 2015
enotsluap
 
Community and voluntary sector research forum march 2015
Community and voluntary sector research forum march 2015Community and voluntary sector research forum march 2015
Community and voluntary sector research forum march 2015
enotsluap
 

Más de enotsluap (20)

Auckland meetup nov 19
Auckland meetup nov 19Auckland meetup nov 19
Auckland meetup nov 19
 
Open and transparent practices through open data
Open and transparent practices through open dataOpen and transparent practices through open data
Open and transparent practices through open data
 
Hawke's Bay Chamber
Hawke's Bay ChamberHawke's Bay Chamber
Hawke's Bay Chamber
 
Open Data - What and Why
Open Data - What and WhyOpen Data - What and Why
Open Data - What and Why
 
Open Data and Social Enterprise
Open Data and Social EnterpriseOpen Data and Social Enterprise
Open Data and Social Enterprise
 
Hawke's Bay Open Data Conference - 2 May 2019
Hawke's Bay Open Data Conference - 2 May 2019Hawke's Bay Open Data Conference - 2 May 2019
Hawke's Bay Open Data Conference - 2 May 2019
 
Ipanz april 2019
Ipanz   april 2019Ipanz   april 2019
Ipanz april 2019
 
Open data 2019
Open data 2019Open data 2019
Open data 2019
 
Auckland IPANZ New Professionals
Auckland IPANZ New ProfessionalsAuckland IPANZ New Professionals
Auckland IPANZ New Professionals
 
Symbiotic relationships: bringing about change for open data together
Symbiotic relationships: bringing about change for open data togetherSymbiotic relationships: bringing about change for open data together
Symbiotic relationships: bringing about change for open data together
 
Data Driven Meetup Wellington
Data Driven Meetup WellingtonData Driven Meetup Wellington
Data Driven Meetup Wellington
 
NZ Analytics Forum - Open Data Landscape
NZ Analytics Forum - Open Data LandscapeNZ Analytics Forum - Open Data Landscape
NZ Analytics Forum - Open Data Landscape
 
Open Data Meetups - Auckland and Christchurch
Open Data Meetups - Auckland and ChristchurchOpen Data Meetups - Auckland and Christchurch
Open Data Meetups - Auckland and Christchurch
 
IOGDC 2012 presentation (Paul Stone)
IOGDC 2012 presentation (Paul Stone)IOGDC 2012 presentation (Paul Stone)
IOGDC 2012 presentation (Paul Stone)
 
Hawkes bay local governent workshop 9 december 2015
Hawkes bay local governent workshop 9 december 2015Hawkes bay local governent workshop 9 december 2015
Hawkes bay local governent workshop 9 december 2015
 
Open Government Data - Inner City Association, Wellington
Open Government Data - Inner City Association, WellingtonOpen Government Data - Inner City Association, Wellington
Open Government Data - Inner City Association, Wellington
 
Govis 2015 building trust through transparency and open data
Govis 2015   building trust through transparency and open dataGovis 2015   building trust through transparency and open data
Govis 2015 building trust through transparency and open data
 
Open data and innovation in my community
Open data and innovation in my communityOpen data and innovation in my community
Open data and innovation in my community
 
Open data - GIG April 2015
Open data - GIG April 2015Open data - GIG April 2015
Open data - GIG April 2015
 
Community and voluntary sector research forum march 2015
Community and voluntary sector research forum march 2015Community and voluntary sector research forum march 2015
Community and voluntary sector research forum march 2015
 

Último

一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
74nqk8xf
 
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
mbawufebxi
 
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfEnhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
GetInData
 
Influence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business PlanInfluence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business Plan
jerlynmaetalle
 
Adjusting primitives for graph : SHORT REPORT / NOTES
Adjusting primitives for graph : SHORT REPORT / NOTESAdjusting primitives for graph : SHORT REPORT / NOTES
Adjusting primitives for graph : SHORT REPORT / NOTES
Subhajit Sahu
 
一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理
一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理
一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理
mzpolocfi
 
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
g4dpvqap0
 
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
ahzuo
 
Machine learning and optimization techniques for electrical drives.pptx
Machine learning and optimization techniques for electrical drives.pptxMachine learning and optimization techniques for electrical drives.pptx
Machine learning and optimization techniques for electrical drives.pptx
balafet
 
My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.
rwarrenll
 
Algorithmic optimizations for Dynamic Levelwise PageRank (from STICD) : SHORT...
Algorithmic optimizations for Dynamic Levelwise PageRank (from STICD) : SHORT...Algorithmic optimizations for Dynamic Levelwise PageRank (from STICD) : SHORT...
Algorithmic optimizations for Dynamic Levelwise PageRank (from STICD) : SHORT...
Subhajit Sahu
 
Global Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headedGlobal Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headed
vikram sood
 
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
apvysm8
 
Everything you wanted to know about LIHTC
Everything you wanted to know about LIHTCEverything you wanted to know about LIHTC
Everything you wanted to know about LIHTC
Roger Valdez
 
一比一原版(CBU毕业证)卡普顿大学毕业证如何办理
一比一原版(CBU毕业证)卡普顿大学毕业证如何办理一比一原版(CBU毕业证)卡普顿大学毕业证如何办理
一比一原版(CBU毕业证)卡普顿大学毕业证如何办理
ahzuo
 
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
slg6lamcq
 
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
u86oixdj
 
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
Timothy Spann
 
Ch03-Managing the Object-Oriented Information Systems Project a.pdf
Ch03-Managing the Object-Oriented Information Systems Project a.pdfCh03-Managing the Object-Oriented Information Systems Project a.pdf
Ch03-Managing the Object-Oriented Information Systems Project a.pdf
haila53
 
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
v3tuleee
 

Último (20)

一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
 
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
 
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfEnhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
 
Influence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business PlanInfluence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business Plan
 
Adjusting primitives for graph : SHORT REPORT / NOTES
Adjusting primitives for graph : SHORT REPORT / NOTESAdjusting primitives for graph : SHORT REPORT / NOTES
Adjusting primitives for graph : SHORT REPORT / NOTES
 
一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理
一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理
一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理
 
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
 
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
 
Machine learning and optimization techniques for electrical drives.pptx
Machine learning and optimization techniques for electrical drives.pptxMachine learning and optimization techniques for electrical drives.pptx
Machine learning and optimization techniques for electrical drives.pptx
 
My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.
 
Algorithmic optimizations for Dynamic Levelwise PageRank (from STICD) : SHORT...
Algorithmic optimizations for Dynamic Levelwise PageRank (from STICD) : SHORT...Algorithmic optimizations for Dynamic Levelwise PageRank (from STICD) : SHORT...
Algorithmic optimizations for Dynamic Levelwise PageRank (from STICD) : SHORT...
 
Global Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headedGlobal Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headed
 
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
 
Everything you wanted to know about LIHTC
Everything you wanted to know about LIHTCEverything you wanted to know about LIHTC
Everything you wanted to know about LIHTC
 
一比一原版(CBU毕业证)卡普顿大学毕业证如何办理
一比一原版(CBU毕业证)卡普顿大学毕业证如何办理一比一原版(CBU毕业证)卡普顿大学毕业证如何办理
一比一原版(CBU毕业证)卡普顿大学毕业证如何办理
 
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
 
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
 
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
 
Ch03-Managing the Object-Oriented Information Systems Project a.pdf
Ch03-Managing the Object-Oriented Information Systems Project a.pdfCh03-Managing the Object-Oriented Information Systems Project a.pdf
Ch03-Managing the Object-Oriented Information Systems Project a.pdf
 
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
 

Managing the Barriers to an Open Data Culture