Wh t Whats New from the N f th High-Level Group? Steven Vale - - PDF document

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Wh t Whats New from the N f th High-Level Group? Steven Vale - - PDF document

United Nations Economic Commission for Europe United Nations Economic Commission for Europe Statistical Division Statistical Division Wh t Whats New from the N f th High-Level Group? Steven Vale UNECE steven.vale@unece.org HLG


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United Nations Economic Commission for Europe Statistical Division United Nations Economic Commission for Europe Statistical Division

Wh t’ N f th What’s New from the High-Level Group?

Steven Vale UNECE

steven.vale@unece.org

 High Level Group for the Modernisation of

HLG Background

 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  10 heads of national and international

statistical organisations

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2 Increasing cost & New competitors Riding the big data wave difficulty of acquiring data competitors & changing expectations Rapid changes in the environment Competition for skilled resources Reducing budget wave

These challenges are too big These challenges are too big for statistical organisations to tackle on their own We need to work together

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T f i i li

A strategy for modernisation

 Transform vision to reality  New sources and products  Streamlined processes  Managing organisational change to support

d i ti d ll b ti modernisation and collaboration

 Transform vision to reality

A strategy for modernisation

a s o s o to ea ty

 New products  Rationalised processes

  • “Plug and play” architecture – based on the

GSBPM and GSIM

 Managing organisational change to support

modernisation and collaboration

Conference of European Statisticians, June 2012

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Information objects

 Things that flow between GSBPM sub-  Things that flow between GSBPM sub

processes

 Things that drive and integrate sub-

processes p

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GSIM and GSBPM

 GSIM describes the information objects and  GSIM describes the information objects and

flows within the statistical business process.

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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What next?

2 big projects for 2013

 Implementing GSIM

1: Standards

  • Help, support, training
  • Knowledge base
  • Platform for sharing experiences

 Reviewing / revising GSBPM and GSIM

Integrating standards

 Integrating standards

  • Map GSIM to SDMX and DDI
  • Geospatial standards
  • Fundamental Principles of Official Statistics
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2: Common Statistical Production Architecture

Generalized Statistical

GSBPM

Production System Statistical Production System

Common Generic Industrial Statistics GSIM Methods Technology

Implementing standards-based statistical production

“Plug and Play”

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CSPA: Progress and Plans

 Project proposal – Approved by HLG

  • Common architecture
  • Proof of concept

 “Sprint” Sessions:

  • Ottawa, 8-12 April
  • Rome, 10-14 June

 Virtual groups / More sprints? / Workshops?  All deliverables by end of 2013

Big Data

HLG released a paper “What does Big data

 HLG released a paper “What does Big data

mean for official statistics?”

  • www1.unece.org/stat/platform/x/toeZB

 Many Big data initiatives

C di ti l f HLG?

  • Coordinating role for HLG?
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Do you want to get involved?

 Sprints  Sprints  Virtual Task Teams  Reviews

Let us know

support.stat@unece.org

HLG governance issues

 The work is growing  Expectations are rising  More efficient structure needed

  • Re-organisation of UNECE expert groups
  • Clearer focus on modernisation

Clearer focus on modernisation

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CES Bureau HLG

HLG Secretariat Team Modernisation Committee Modernisation Committee Modernisation Committee Modernisation Committee Executive Board

Project HLG workshops Communications Standards Production and methods Products and sources Organisational framework and evaluation MSIS SAB Data editing Plug and play Data collection Confidentiality Big data Open data Micro-data METIS GSBPM / GSIM DDI / SDMX Geospatial standards Metadata flows HRMT Legal issues Licensing Evaluation management

More information

GSIM

 GSIM

  • http://www1.unece.org/stat/platform/display/metis/Ge

neric+Statistical+Information+Model+(GSIM)

 HLG

  • http://www1.unece.org/stat/platform/display/hlgbas