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Welcome to the UNECE Virtual Standards Helpdesk



This wiki provides a "one-stop shop" for access to information about the standards necessary for the modernisation of official statistics. It is an initiative of the UNECE High-Level Group for the Modernisation of Official Statistics (HLG-MOS).

The standards referenced here are cross-cutting, supporting the modernisation of all types of statistical production, and are endorsed by the HLG-MOS. For domain-specific standards, please see the Global Inventory of Statistical Standards.

Registered users can post comments and ask questions in the discussion forum associated with each UNECE standard/model, once they are logged in.  If you wish to request a user account you may email




HLG-MOS Standards and Models

Modernisation Maturity Model and the Roadmap for Implementing Modernstats Standards

The MMM is a self-evaluation tool to assess the level of organizational maturity against a set of pre-defined criteria.  There are multiple aspects of maturity in the context of modernisation, and as such, the model that has been developed has several distinct dimensions. Maturity is indicated by the attainment of a particular "maturity level". A maturity level assessment will provide a clear picture of the organisational maturity level, which can then be compared between organisations, and between statistical domains/business units within an organisation.

The Roadmap sets out the optimal sequence of capability development activities, based on the experiences and lessons learned of the organisations that have already progressed to higher levels of modernisation maturity.


The MMM can be found here


Descriptions of the instruments that comprise the MMM Roadmap are provided here.

Generic Statistical Business Process Model (GSBPM)

The GSBPM describes and defines the set of business processes needed to produce official statistics. It provides a standard framework and harmonised terminology to help statistical organisations to modernise their statistical production processes, as well as to share methods and components.







Generic Statistical Information Model (GSIM)

The GSIM is a reference framework of information objects, which enables generic descriptions of the definition, management and use of data and metadata throughout the statistical production process. It provides a set of standardized, consistently described information objects, which are the inputs and outputs in the design and production of statistics. As a reference framework, GSIM helps to explain significant relationships among the entities involved in statistical production, and can be used to guide the development and use of consistent implementation standards or specifications.







Common Statistical Production Architecture (CSPA)

CSPA builds on existing standards such as the GSBPM and the GSIM to create an agreed set of common principles and standards designed to promote greater interoperability within and between statistical organizations. It provides the “industry architecture” for official statistics.








Generic Activity Model for Statistical Organisations (GAMSO)

The GAMSO extends the GSBPM by covering all activities of a statistical organisation. Version 1.0 was approved for release by the HLG-MOS on 1 March 2015.





Generic Statistical Data Editing Models

The GSDEMs provide a standard vocabulary with common definitions and models to facilitate the sharing of information and best practices in the field of statistical data editing. Version 1.0 was approved for release by the HLG-MOS on 26 November 2015.




The Common Metadata Framework

The Common Metadata Framework is published online, and is divided into four parts, each of which concentrates on different practical and theoretical aspects of statistical metadata systems, and provides vital knowledge for anyone working with statistical metadata


Other Relevant Standards

Data Documentation Initiative (DDI)

DDI is an initiative to create an international standard for describing data from the social, behavioral, and economic sciences. The DDI metadata specification now supports the entire research data life cycle. DDI metadata accompanies and enables data conceptualization, collection, processing, distribution, discovery, analysis, repurposing, and archiving.







Statistical Data and Metadata eXchange (SDMX)

SDMX is an initiative to foster standards for the exchange of statistical information.






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