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![Page 1: United Nations Economic Commission for Europe Statistical Division Standards and Statistical Production Architectures Steven Vale UNECE steven.vale@unece.org.](https://reader035.fdocuments.net/reader035/viewer/2022062802/56649ef35503460f94c05d32/html5/thumbnails/1.jpg)
United Nations Economic Commission for EuropeStatistical DivisionUnited Nations Economic Commission for EuropeStatistical Division
Standards and Statistical Production Architectures
Steven ValeUNECE
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High-Level Group for the Modernisation of Statistical Production and Services
Created by the Conference of European Statisticians in 2010
10 heads of national and international statistical organisations
Background
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The Challenges
Increasing cost &
difficulty of acquiring
data
New competitors & changing
expectations
Rapid changes in the environment
Competition for skilled resourcesReducing
budget
Riding the big data
wave
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These challenges are too big for statistical organisations to
tackle on their own
We need to work together
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Using common standards, statistics can be produced
in a more efficient way
No domain is special!
Do new methods and toolssupport this vision, or do they
reinforce a stove-pipe mentality?
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Common genericstatistics production
GSBPM GSIM
Methods Technology
StatisticalConcepts
InformationConcepts
StatisticalHowTo
ProductionHowTo
Standards-based modernization
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Projects
2012
2013
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GSBPM – Standard Processes
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GSIM and GSBPM
GSIM describes the information objects and flows within the statistical business process.
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So what is GSIM?
A reference framework of information objects:• Definitions
• Attributes
• Relationships
GSIM aligns with relevant standards such as DDI and SDMX
GSIM gives us standard
terminology
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“support the enhancement and implementation of the
standards needed for the modernisation of statistical production and services”
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Components
Implementing GSIM Mapping GSIM to DDI and SDMX Reviewing / revising GSBPM and GSIM Links to geo-spatial standards
• New task team to assess the role of geo-spatial standards in the modernisation of official statistics
Training and advocacy
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Aims
Increased: interoperability through sharing processes
and components ability to find real collaboration opportunities ability to make international decisions and
investments sharing of architectural design, knowledge and practices
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Historically statistical organisations have developed specialised processes and systems
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How does architecture help?
Many statistical organisations are modernising using Enterprise Architecture
It can help to remove silos and improve collaboration across an organisation.
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EA helps you get to this
Disseminate
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…but if each statistical organisation works in isolation…..
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NSI
1Collect Process Analyse Disseminate
Surv
ey A
Surv
ey B
NSI
2 Surv
ey A
Surv
ey B
?
?
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…but if statistical organisations work together
An industry architecture will make it easier to standardise and combine the components of statistical production,
regardless of where they are built
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NSI
1Collect Process Analyse Disseminate
Surv
ey A
Surv
ey B
NSI
2 Surv
ey A
Surv
ey B
?
?
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Lego pieces could be:
Brand newWrapped
legacy/existing
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An industry architecture is:
“a set of agreed common principles and standards
designed to promote interoperability in an industry”
“an architecture template for statistical production”
“a common vocabulary to discuss implementations”
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Proof of Concept
Demonstrate the process of working together
Demonstrate business viability to senior management
Prove the value of the architecture
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Catalogues
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Do you want to get involved?
Projects• Sprints / virtual task teams / reviews
Other activities / project proposals?
Let us [email protected]
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More information
HLG Wikiwww1.unece.org/stat/platform/display/hlgbas
Linked Group
Business Architecture in Statistics