The Common Statistical Production Architecture (CSPA) was developed during 2013 in an international collaboration project under the High-Level Group for the Modernisation of Statistical Production and Services (HLG). That project included the development and specification of the architecture, as well as a practical test of its principles and applicability in a “proof of concept”. However, given the strict time limits for that project (one year), it deliberately did not include the implementation of the architecture for production systems within statistical organisations. A follow-up project to cover early implementations and the development of key supporting resources such as a catalogue of artefacts, was seen as a top priority by the Workshop on Modernisation of Statistical Production and Services (Geneva, 25-27 November 2013). The HLG subsequently agreed that this should form one of two key modernisation projects for 2014.

By the end of 2014, this project created the first “production” CSPA-compliant services, several of which were implemented by statistical organisations. As a practical application of CSPA, the project resulted in feedback and enhancements to the architecture based on implementation experiences. The result was CSPA v1.1, which was released in January 2015. Further services will be developed during 2015.

The project is open to all national and international statistical organisations that want to contribute. It aims to be complementary to other initiatives, including those of the Statistical Network and the European Statistical System, and to avoid duplication of efforts. It also aims to be as relevant as possible to the organization-specific needs and concerns of each contributing organisation.

This page contains public information and documents. The 2014 Home Page for CSPA Implementation project are restricted to project team members who have UNECE wiki accounts.

For more information, please see the 2014 Project Proposal

The CSPA-compliant services developed and under preparation are:

ServiceOrganisationsService DescriptionService SpecificationService Implementation Description

Confidentialized analysis of microdata

Australian Bureau of Statistics

Statistics Canada

Error correctionIstat 
Linear error localisationStatistics Netherlands 
Linear rule checkingStatistics Netherlands
List statistical classificationsStatistics Norway 
Retrieve statistical classificationStatistics Norway 
SDMX transformOECD
Sample selectionStatistics Netherlands 
Seasonal adjustment

Australian Bureau of Statistics


Statistics New Zealand

Statistical chart generatorOECD


If you are interested in being involved in the project, please contact Steven Vale (