Transcript Conference_EFGS2015_1010_0_ABS_Martin

Towards a Global Statistical
Geospatial Framework
Martin Brady
Director Geospatial Solutions Section
Australian Bureau of Statistics
European Forum for Geography and Statistics
November 2015
 International collaboration
 Statistical – Geospatial Integration in Australia
 Global Statistical Geospatial Framework
 Statistical and geospatial data and metadata
interoperability
 Protecting confidentiality
The challenge
‘The work on global geospatial information
management over the past two to three
years has confirmed that one of the key
challenges is a better integration of
geospatial and statistical information as
a basis for sound and evidence-based
decision-making.’
Secretary General of the
UN Economic and Social Council, 2012.
Geospatial program review
 Greater collaboration
- outreach and information sharing
- shared best practice and standards
- partnership between statistical and geospatial
 A common approach to linking statistics to location
– a global statistical-geospatial framework
 Establish an expert group to progress issues
 Hold a global forum to discuss issues and
experiences
A new partnership
UN Economic and Social Council
(ECOSOC)
UN Statistical Commission
(UNSC)
 ABS Geospatial program
review – proposed a global
framework
UN Committee of Experts on
Global Geospatial Information
Management (UN-GGIM)
 List of nine issues included
'linking of spatial to statistics'
UN Expert Group
Statistical-Geospatial Integration
UN Global Forum
Statistical-Geospatial Integration
United Nations Expert Group on the Integration of
Statistical and Geospatial Information
Expert Group - Objectives
 Coordination and dialogue between statistical and
geospatial communities.
 Propose work plans and guidelines to advance
the implementation of a global framework.
 Address technical, institutional and information
policy issues of a global framework.
 Pursue the implementation of the framework in
the 2020 Round of Population Censuses, as well
as other censuses and global data initiatives.
The future
‘When both statistical and geospatial
information are integrated within a
statistical-spatial framework, the
geo-statistical results can significantly
improve the quality of official statistics
and Population Censuses, and the
measuring and monitoring of the
sustainable development goals.’
Summary Report of the Global Forum on the Integration
of Statistical and Geospatial Information, 2014
 Statistical – Geospatial Integration in Australia
Open data
Big Data
SSF Vision
SSF Goals
Informed decision making is enhanced
by using location in a common framework
to allow seamless integration of administrative,
statistical and spatial information resources.
All statistical data
is consistently
spatially enabled
Users can discover, access,
integrate, analyse and
visualise statistical
information seamlessly for
regions of interest
The Framework
Statistical Community
Spatial Community
Socio-Economic Datasets
Core Statistical
Tax
Census, Demographics,
Agriculture, Building,
Labour Force, etc.
Income and
Business Tax
Foundation Spatial Data Framework
– Fundamental Elements
Admin. & statistical boundaries
Addressing, Place Names
Immigration
Health
Medicare,
Pharmaceuticals,
Workforce
Social Welfare
Unemployment,
Disability,
Family Support
Land
Valuation
and Use
SSF
bridge
Transport, Water
Land and Property
Elevation and Depth
Imagery
Others …
Positioning
Population grid – geospatial from statistics
Land Account – statistics from geospatial
Geospatial Input
State Valuations:
• Land use
• Land value
Irrigated Pasture
Statistical Output
Geoscience
Australia’s
Dynamic Land
Cover grid
Trees - open
Inland Water
Land parcel
(Property)
Rain-fed pasture
Detailed Land Account tables:
Land cover by land use, area and value
Trees - closed
Small area land account summary data:
- Land value
- Land cover
- Land use
- Cadastral change
Integrated with other small area data:
+ Population
+ Building approvals
Adding Geospatial Information to Statistics
Address points from Health Survey - spatial link to built environment data
Access to
Greenspace
Population
Density
Commuting
Distance
Access to
Health Services
Adding Geospatial Information to Statistics
Statistics
Access to
Greenspace
Geo-statistics
Person
Age
Sex
Body Mass
Index
Distance to
Greenspace
1
F
30
19
0.25
2
F
28
32
2.01
3
M
42
27
0.36
The future…
Statistical data linked with spatial data using registers
Sample selection or
geocoded admin.
addresses
Statistical dataset
Address Register
Web Service
compares address
points and
greenspace
Greenspace
Dataset of address
point identifiers with
attribute of walking
distance to
greenspace
 Global Statistical Geospatial Framework
 Statistical and geospatial data and metadata
interoperability
 Protecting confidentiality
UN Expert Group
Global Statistical Geospatial Framework
 Bring together a proposal adapted from
Australian Statistical Spatial Framework
 Include input from:
• Mexico’s National Geostatistical Framework.
• EFGS/Eurostat on the GSBPM model for
geospatial.
• Other country examples of adoption/application.
Global Statistical Geospatial Framework
Next Steps
UNSD to:
 UNSD to undertake consultation
– starting Nov 2015
 Proposal for adoption in 2016
– UN Statistical Commission
– UN-GGIM Committee of Experts
UN Expert Group
- Areas for further work
 2020 Round of Population Censuses
 Collaboration and partnership
 Consistent terminology
 Protecting confidentiality
 Interoperable data and metadata between
statistical and geospatial domains
UN Expert Group
- Areas for further work (cont.)
 Geography for data release
- Administrative, statistical and grid geographies
 Authoritative geocoding
 Big data in official statistics and geospatial
information
Geospatial and statistical data and
metadata interoperability
 Statistical and geospatial data is not easily
transformed and integrated.
 Too much time is spent preparing and managing
data, instead of analysing.
 Machine to machine is not integrated.
 UNSD / UN-GGIM establishing a Working Group.
– Expert Group and standards organizations
Common Statistical Production
Architecture
Business
Architecture
Information
Architecture
Application
Architecture
Technology
Architecture
• General Statistical
Business Process
Model – GSBPM
• General Statistical
Information Model
– GSIM
• Data
Documentation
Initiative – DDI
• Statistical Data
and Metadata
Exchange –
SDMX
• National Statistical
Office - NSO
Geospatial Data
and Metadata
Working Group
 International Organization of Standardization –
(ISO)
 Open Geospatial Consortium – (OGC)
 International Hydrographic Organization – (IHO)
 Statistics Community ??
- National Statistical Offices
- HLG Modernisation Committee on Standards?
Protecting confidentiality for
regionalised data
 “Geographic Differencing” is a specific
privacy risk for regionalised data.
 It is similar to other classification
differencing risks, for example occupations.
 Greater risk due to variety of geographies
used within countries.
Geographic differencing
 Simple geographic differencing
– Statistical data for Region 1 is
subtracted from Region 2.
Perturbation or controlled rounding
– protecting against geographic differencing
Thank you
For more information
E-mail: [email protected]
Search: Statistical Spatial Framework