Generic Statistical Information Model (GSIM) Thérèse Lalor and Steven Vale United Nations Economic...
Transcript of Generic Statistical Information Model (GSIM) Thérèse Lalor and Steven Vale United Nations Economic...
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Generic Statistical Information Model (GSIM)
Thérèse Lalor and Steven Vale United Nations Economic Commission for Europe
(UNECE)
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The Challenges
Increasing cost & difficulty of
acquiring data
New competitors & changing
expectations
Rapid changes in the environment
Competition for skilled resources
Reducing 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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A High Level Group consisting of 10 heads of national and international statistical
organizations was created
Response from Official Statistics
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Using common standards, statistics can be produced
in a more efficient wayNo domain is special!
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Common Generic lndustrialised Statistics
GSBPM GSIM
Methods Technology
Business Concepts Information Concepts
Statistical HowTo Production HowTo
conc
eptu
alpr
actic
al
Common Generic lndustrialised Statistics
GSBPM GSIM
Methods Technology
Business Concepts Information Concepts
Statistical HowTo Production HowTo
conc
eptu
alpr
actic
al
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The GSBPM
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The GSBPM is used by more than50 statistical organizationsworldwide to manage and
document statistical production
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GSIM is complementary to GSBPM
Another model is needed to describe information objects and flows within the statistical business
process
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Introducing the GSIM
You are here
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What is GSIM?
• A reference framework of information objects
• It sets out definitions, attributes and relationships regarding information objects
• It aligns with relevant standards such as DDI and SDMX
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Purposes of GSIM
Improve communication Generate economies of scale Enable greater automation Provide a basis for flexibility and innovationBuild staff capability by using GSIM as a teaching
aid Validate existing information systems
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GSIM is a conceptual model: It is a new way of thinking for statistical organizations
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GSIM enables:
•Communication•Coordination•Cooperation•Collaboration
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Other relevant standards
Geospatial standards
DDI
SDMX
GSIMConceptual model
Implementationstandards
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CONCEPTS
PRODUCTIONBUSINESSSTRUCTURES
Statistical Need
Business Case
PopulationConcept
Statistical ProgramDesignchanges
design of
Statistical Program
Statistical Activity
has
includes
Data Channel
has
DataResource
uses
Process Step
Data Set
uses
includes
UnitClassification Variable
Data Structure
specifies
Process output
Process Input
specifies
has
describes
identifies defines
measuresdefines
is associated with
comprises
describes
specifies
may include
may include
may initiate
comprises
• Acquisition Activity
• Production Activity
• Dissemination Activity
initiates
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GSIM: The “sprint’ approach •The HLG-BAS decided to accelerate the development of the GSIM•“Sprints” – 2 week workshops for 10-12 experts (IT, methodology, statistics, ...)•Sprint 1 – Slovenia, February 2012•Sprint 2 – Republic of Korea, April 2012•Integration Workshop, Netherlands, September 2012
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Moving to GSIM in practice
GSIM could lead to:•A foundation for standardized statistical metadata use throughout systems•A standardized framework to aid in consistent and coherent design capture•Increased sharing of system components
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Moving to GSIM in practice
•Common terminology across and between statistical agencies.
•It allows NSIs and standards bodies, such as SDMX and DDI, to understand and map common statistical information and processes.
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GSIM v1.0
•Released in December 2012
•We need people to use GSIM “in anger”. Then we will know how best to improve it.
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More informationGSIM
http://www1.unece.org/stat/platform/display/metis/Generic+Statistical+Information+Model+(GSIM)
Poster Session @ EDDI Today at lunch time