2. Building a Data-Driven Public Service
August 2016
Pia Waugh
@piawaugh |

3. What data?

4. What data? Specialist data Regular requests Administrative data
Reports
Tables
Maps
Analysis
Key indicators
Official Information Act requests
Lists (places, contracts, services)
Services analytics
Regular requests
Compliance information
Public reporting data
Budget
Policy & programme monitoring
...

5. Questions
What is your agency data vision and strategy? A holistic approach would yield greater benefits to everyone.
What barriers exist for agencies to better use, manage, share and publish data?
What is needed by data publishers and users to make data sharing and publishing part of BAU?
How can we bring the different NZ data agendas together?
What are the benefits of open data? Is it beneficial to agencies individually and better government as a whole?
What role should data.govt.nz play?

6. Public sector open data motivators
Efficiencies from proactively publishing common requests
Cheaper and more modular services delivery
Reduced regulatory burden through machine readable data supporting compliance and automated reporting
Better policy outcomes by leveraging cross-agency data
More consistency & less duplication across government
Improved opportunities to leverage innovation and collaboration (citizens, industry, other depts)
Opportunities to improve data quality through verifiable public contributions
Access to data from other agencies

7. NZ Data Landscape Reuse projects Catalogs Publishing Sharing &
Catalyst
projects
FigureNZ
GovHack
ODP
advocacy
Reuse projects
No catalogue
for sensitive
data
Specialist
catalogues
Data.govt.nz
(ostensibly AoG
catalogue)
Geoportal
Council
catalogues
Catalogs
Publishing
Stats
Aggregate
LINZ
AoG Publishing?
Sharing &
Integration
IDI
SIU
Internal
Analytics
LINZ
(spatial and
spatially
enabled
data)
AoG
Services
Analytics
Non-sensitive
Agency data
(internal,
on websites)
Council
data
Statistics
(statistical
data)
Sensitive
Agency data
(internal)
Data
Agency
LDS
Agency
LDS
Agency
LDS

8. How Do Agencies Publish?
Some agencies have specialised data expertise and publishing capabilities.
Some are developing capacity to publish.
Most, if they publish data at all, publish data un-usefully.
AoG data platform required for this barrier.
Skills, guidance and encouragement help. ?
DIA
Stats
LINZ

9. Data Needs in Agencies by Maturity
Immature Maturing Mature
Internal capacity Public and agency engagement Holistic data strategy Value & efficiencies Specialised access Mature sharing & publishing
Access to specialised platforms & expertise Building analytics capacity Efficiencies realisation Budget for data program Strategic implementation Greater collaboration Public & agency engagement
Data from other sources Internal business case dev Guidance and encouragement Publishing platform(s) Tools for internal reuse Build basic internal capacity Access to expertise Strategic development Safe sandbox (eg GovHack) Largely reliant on externals

10. Customer Pain Points
Most Agencies have little motivation, resources or expertise to publish data. In most cases do not have a broader data strategy. If agencies consumed more data (internally & across govt) it would naturally lead to more data sharing and public availability.
Data users find it hard to discover data and usually if it is findable, it isn't usable or machine readable. Often user logins are required. This creates a lack of experimentation of and confidence in government data resulting in a lack of reuse and lack of outcomes realised.
Every individual barrier to using or publishing data dramatically reduces activity and the possibility of benefits realisation!

11. User Needs for data.govt.nz
Data Users
(Public, Business,
Journalists, Media,
Agencies)
Discovery
Usage
Rights
Usable
Data
(MR, APIs)
Support,
Requests
Data Publishers
(Agencies)
Internal
Data Strategy
Easy
Management
Of Catalog
Easy Data
Publishing
Access to
Expertise, Docs
& Training
Access to
Data from
Across Govt
Value from
Open Data
Analytics &
Reporting
Case Studies
& Business
Case for OD
We need to educate on benefits and reduce barriers to using and publishing data so people can get on with it.

12. Data and Benefits What Government data broadly drives what outcomes?
Policy &
Investment
Prioritisation
Informing Policy,
Decision Making
Program Design,
Implementation
& Monitoring
Less
Duplication
Longitudinal
Analysis &
Research
(de-identified)
Secure
Sensitive
data
Public
Aggregate
data
Public
Non-sensitive
data
Agency
Efficiencies
Intervention,
Protection &
Enforcement
(identified)
3rd Party
Products
& Services
Service Delivery
Improvements
Public Analysis,
Engagement &
Value Add

13. Data and Benefits What systems support which outcomes?
Policy &
Investment
Prioritisation
Informing Policy,
Decision Making
Program Design,
Implementation
& Monitoring
Less
Duplication
Longitudinal
Analysis &
Research
(de-identified)
Banks, Insurance
Google
OECD, WB
Secure
Sensitive
data
Public
Aggregate
data
Public
Non-sensitive
data
Agency
Efficiencies
Stats, IDI, SIU ??
LINZ, data.govt.nz
Intervention,
Protection &
Enforcement
(identified)
3rd Party
Products
& Services
Service Delivery
Improvements
Public Analysis,
Engagement &
Value Add

14. Data and Benefits Investment is driving some outcomes more than others
Policy &
Investment
Prioritisation
Informing Policy,
Decision Making
Program Design,
Implementation
& Monitoring
Less
Duplication?
Longitudinal
Analysis &
Research
(de-identified)
Secure
Sensitive
data
Public
Aggregate
data
Public
Non-sensitive
data
Agency
Efficiencies?
Stats, IDI, SIU ??
LINZ, data.govt.nz
Intervention,
Protection &
Enforcement
(identified)
3rd Party
Products
& Services?
Service Delivery
Improvements?
Public Analysis,
Engagement &
Value Add?

15. Parts of a data strategy
Business
Reuse
(Products,
services)
Govt
Investment
(Catalyst
projects)
Analysis,
Presentation
(eg, datavis,
FigureNZ)
Better
Govt Policy,
Decisions,
Efficiencies
Public
Innovation
(eg,
Govhack)
Data reuse
Governance,
leadership
Advocacy
Incentives,
Performance
Data
Policy
Strategy
Infrastructure
(Specialist &
General)
Skills,
Resources,
Training
Full
Discovery
Standards
Implementation

16. Critical aspects for data.gov.au (for comparison)
Harvesting metadata from existing catalogues with common metadata mapping
Free data hosting (with automatic APIs) to serve the majority of agencies that can't easily publish data
Education of the business case for agencies
A committed central technical team – agency support, platform functional improvements, docs
A distributed publishing model where agencies manage their own data linked or hosted on data.gov.au.
Constant public success and communication
Modular, iterated technical design, scalable on the cloud

17. Future data.govt.nz options
Simple
catalogue only
Currently live
Consistent
catalogue
Tabular
data hosting
Automated
APIs
Basic Stats
Basic Charts
& Mapping
Beta
Future
Options
Consistent
catalogue
Tabular
data hosting
Automated
APIs
Analytics &
Reporting
Basic Charts
& Mapping
Metadata
Mapping
Data
Services
Distributed
Publishing
Quality
Frameworks
Collaborative
Strategy
AoG Data
Vision
Data Models
Sharing
Part of
Services
Delivery
Additional
Data Hosting
As Required
High Volume
Charging
Framework
Artifacts
Sharing
Hub
Guidance
And Shared
Resources
Scalable
Cloud
AoG Data
Practitioner
Community
Of Practice
Cross
Agency
Hackfests
Practitioner
Governance
Group
Exemplar
Agency
Projects
Business
Benefits
Case Studies
Sustainable
Reuse
Projects

18. Parallel Initiatives Needed To Drive Change
Data reuse projects to demonstrate value and drive appetite
Eg - Catalyst projects, FigureNZ
Development of data driven culture across govt
Eg - growing demand from policy teams, investment, services delivery
AoG holistic data publishing, sharing, skills and capability improvements
Eg – data.govt.nz, LINZ, Statistics
Specialist data programs and integration initiatives for specialised outcomes
Eg – SIU, DFP, LINZ, Statistics, IDI