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GSIM Communication Paper v1.0 in Norwegian

(kindly provided by Statistics Norway)


Generic Statistical Information Model (GSIM):
Communication Paper for a General Statistical Audience
(Version 1.1, December 2013)


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About this document
This document provides an overview about the information represented in GSIM, and summaries of how the model will benefit statistical organizations and relationships to other models and standards.
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This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/. If you re-use all or part of this work, please attribute it to the United Nations Economic Commission for Europe (UNECE), on behalf of the international statistical community.
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Table of Contents
Introduction
Scope
What is GSIM?
Benefits of GSIM for the organization as a whole
GSIM and GSBPM
What does it mean for me?
The Business view
The Information Technology view
SDMX, DDI and other standards
Summary

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Introduction


1.Across the world statistical organizations undertake similar activities albeit with variations in the processes each uses. Each of these activities use and produce similar information (for example all organizations use classifications, create data sets and disseminate information). Although the information used by statistical organizations is at its core the same, all organizations tend to describe this information slightly differently (and often in different ways within each organization). In the past, there was no common way to describe the information that is used. This makes it difficult to communicate clearly within and between statistical organizations and without this there was no foundation for in-depth collaboration, standardization, or the sharing of tools and methods.

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6.This paper provides an introduction to GSIM, summarizing the key points for a relatively general statistical audience. For more technical detail, please see the specification document and related material, available on the UNECE web site

Footnote Macro

See: http://www1.unece.org/stat/platform/display/metis/Generic+Statistical+Information+Model+(GSIM)

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Scope

 

7. GSIM provides the information object framework supporting all statistical production processes such as those described in the Generic Statistical Business Process Model (GSBPM)

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See: www.unece.org/stats/gsbpm

, giving the information objects agreed names, defining them, specifying their essential properties, and indicating their relationships with other information objects. It does not, however, make assumptions about the standards or technologies used to implement the model.

8. GSIM does not include information objects related to business functions within an organization such as human resources, finance, or legal functions, except to the extent that this information is used directly in statistical production.

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What is GSIM?


9. GSIM contains objects which specify information about the real world – 'information objects'. Examples include data and metadata (such as classifications) as well as the rules and parameters needed for production processes to run (for example, data editing rules). GSIM identifies around 110 information objects, which are grouped into four top-level groups, and are explained in more detail in the specification documentation.


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Figure 1. GSIM Top-level information object Groups

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If, for example, the Business Process is related to the collection of data, there will be an Information Provider who agrees to provide the statistical organisation with data (via a Provision Agreement). This Provision Agreement specifies an agreed Data Structure and governs the Exchange Channel used for the incoming information. The Exchange Channel could be a Questionnaire or an Administrative Register. It will receive the information via a particular mechanism (Protocol) such as an interview or a data file exchange.
The Data Set produced by the Exchange Channel will be stored in a Data Resource and structured by a Data Structure.

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Benefits of GSIM for the organization as a whole


14.It is intended that GSIM may be used by organizations to different degrees. It may be used in some cases only as a model to which organizations refer when communicating internally or with other organizations to clarify discussion. In other cases an organization may choose to implement GSIM as the information model that defines their operating environment. Various scenarios for the use of GSIM are valid, although those organizations that make use of GSIM to its fullest extent may expect to realize the greatest benefits.

Long term benefits

15. GSIM provides a set of standardized information objects, which are the inputs and outputs in the design and production of statistics. By defining objects common to all statistical production, regardless of subject matter, GSIM enables statistical organizations to rethink how their business could be more efficiently organized.

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  • Build capability among staff by using GSIM as a teaching aid that provides a simple easy to understand view of complex information and clear definitions;
  • Validate existing information systems and compare with emerging international best practice and where appropriate leverage off international expertise;
  • Guide development or updating of international or local standards to ensure they meet the broadest needs of the international statistical community.

 

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GSIM and GSBPM


21.GSIM and GSBPM are complementary models for the production and management of statistical information. GSBPM models the statistical production process and identifies the activities undertaken by producers of official statistics that result in information outputs. These activities are broken down into sub-processes, such as "Impute" and "Calculate aggregates". As shown in Figure 6, GSIM helps describe GSBPM sub-processes by defining the information objects that flow between them, that are created in them, and that are used by them to produce official statistics. Image Removed

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Figure 4. GSIM and GSBPM

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25.GSIM supports a consistent approach to metadata, facilitating the primary role for metadata envisaged in Part A of the Common Metadata Framework "Statistical Metadata in a Corporate Context"

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http://www1.unece.org/stat/platform/display/metis/The+Common+Metadata+Framework

, that is, that metadata should uniquely and formally define the content and links between objects and processes in the statistical information system.
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What does it mean for me?

 

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The Business view


26. GSIM will help you to improve your communication with colleagues (both locally and internationally).

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37. Production will be based upon more standardized applications that are more robust to change and less vulnerable to changing personnel. An increase in the use of standardized applications, which can easily be shared across domains, will enable statisticians to more easily work in different domains.

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The Information Technology view


38. A main concern for information technologists is the duplication of effort due to the "stove-pipe" organization of statistical production. Unstable and differing requirements from these "stove-pipes" lead to tailor made one–off solutions, whilst a high turnover of IT staff can result in poorly documented and non-standard applications.

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43. At the international level there will be increased possibilities for co-design and co-development of common components based upon more robust user-requirements from a wider user-community. The IT developers will also have access to a larger development community that all speak the same language to describe their statistical information.

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SDMX, DDI and other standards


44. As a reference framework of information objects, GSIM has a complementary relationship with standards, such as SDMX (Statistical Data and Metadata eXchange) and DDI (Data Documentation Initiative), which are commonly used to represent and exchange statistical data and metadata.

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54. In this way GSIM benefited from the investment of time in analysis, modelling, testing and refinement when developing these standards and models to their current level of maturity. It also means GSIM does not vary "for no reason" from terms and definitions which are used in existing standards and models. Where it does vary it is for reasons such as existing relevant standards and models being inconsistent internally, with one another and/or statisticians reporting that alternative terms or definitions are more relevant to their business needs. A direct consequence of this was the revision of the Neuchâtel Model for Classifications, to fully align and integrate it with GSIM.

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Summary


55. This paper introduces GSIM to people working in statistical organisations. It outlines the benefits of the model as well as how the adoption of the model might impact staff in statistical organisations. The paper also discusses the interaction of GSIM and other frameworks and standards such as GSBPM, DDI and SDMX.

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