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United Nations Economic Commission for Europe Statistical Division Enhanced Generic Models to Support the Standardisation of Statistical Production Steven.

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Presentation on theme: "United Nations Economic Commission for Europe Statistical Division Enhanced Generic Models to Support the Standardisation of Statistical Production Steven."— Presentation transcript:

1 United Nations Economic Commission for Europe Statistical Division Enhanced Generic Models to Support the Standardisation of Statistical Production Steven Vale UNECE steven.vale@unece.org

2 Introducing UNECE Statistics

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5 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

6 Using common standards, statistics can be produced more efficiently No domain is special! Do new methods and tools support this vision, or do they reinforce a stove-pipe mentality?

7 Standards-based Modernisaton 135 28% 43% 34,600

8 Introducing the GSBPM

9 Why do we need the GSBPM?  To define and describe statistical processes in a coherent way  To compare and benchmark processes within and between organisations  To make better decisions on production systems and organisation of resources

10 Key features  Not a linear model  Sub-processes are not followed in a strict order  It is a matrix, through which there are many possible paths

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12 The GSBPM is used by more than 50 statistical organisations worldwide

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14 What is GSIM?  A reference framework of information objects  It sets out definitions, attributes and relationships of information objects  It aligns with relevant standards such as DDI and SDMX

15 GSIM and GSBPM  GSIM describes the information objects and flows within the statistical business process.

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20 Outcomes GSBPM v5.0

21 Main Changes  Phase 8 (Archive) removed Archiving can happen at any stage in the statistical production process  New sub-process "Build or enhance dissemination components"  Clearer distinction between detection and treatment of errors  Sub-processes re-named to improve clarity  Descriptions of sub-processes improved  Terminology is less survey-centric

22 Outcomes Version 1.1 Simplified - 150 110 information objects Incorporates revised Neuchâtel Model of classification terminology Better aligned with other standards, particularly DDI

23 Mappings Fundamental Principles of Official Statistics

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25 Governance

26 More Information  HLG Wiki: www1.unece.org/stat/platform/display/hlgbas  LinkedIn group: “Business architecture in statistics”


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