64th ISI World Statistics Congress - Ottawa, Canada

64th ISI World Statistics Congress - Ottawa, Canada

Standards-based modernisation of official statistics: the added value and recent advancements of the ModernStats models

Organiser

ZV
Zoltán Vereczkei

Participants

  • SD
    Mr Stephane Dufour
    (Chair)

  • IC
    Ms Inkyung Choi
    (Presenter/Speaker)
  • The journey of standard-based modernisation: where we started and where we are now

  • JM
    Dr Juan Muñoz
    (Presenter/Speaker)
  • Foundations for statistical organisations: GAMSO and GSBPM

  • FR
    Dr Flavio Rizzolo
    (Presenter/Speaker)
  • Common language in information: GSIM and CSDA in action

  • FC
    Franck Cotton
    (Presenter/Speaker)
  • Coming together: Core Ontology for Official Statistics

  • Abstract

    Organisations producing official statistics around the world are constantly innovating and modernising their statistical production. A key success factor in the modernisation of official statistics is to have common foundations to enable knowledge sharing, cooperation and joint innovation projects both within the organisation and across different organisations. To be able to talk about similarities in challenges, ideas and potential solutions, it is necessary to have a common language and understanding of the processes providing a frame for the production of official statistics.

    The so-called “ModernStats models” provide standard frameworks for the official statistical community in the UNECE region and beyond, and are developed, supported and promoted by different organisations and countries working together under the umbrella of the Conference of European Statisticians (CES).

    After the adoption of the Generic Statistical Business Process Model (GSBPM) by the international community in 2008 (joint UNECE/Eurostat/OECD work session on statistical metadata – METIS), various ModernStats models have been developed to address different challenges that the official statistics community faces. The suite of ModernStats models include the Generic Statistical Information Model (GSIM), the Generic Activity Model for Statistical Organizations (GAMSO), the Common Statistical Data Architecture (CSDA), the Common Statistical Production Architecture (CSPA) and many more; with new models such as the Core Ontology for Official Statistics (COOS) currently in development. These models not only provide a conceptual description of different aspects of statistical production but also function as anchors for implementation standards and models, most notably DDI and SDMX, to be used in the development of statistical data management solutions.

    The landscape of standards and solutions available for statistical organisations and other producers of official statistics has never been richer than it is today but it also complex and very often challenging. Any statistical organisation willing to find its way in this complex system will turn their attention to process and information models. The need for relevant guidance for official statistics in this regard is now higher than ever before, setting the course for the evolution of the ModernStats models.

    More and more countries and organisations are using the ModernStats models on the national level and in defining innovative ideas. The tendency of countries turning towards these standards for structure and guidance is evident seeing that scientific papers, innovative ideas and developments are quite often presented and explained in papers and at conferences with references made to these models. In order to support the official statistical community, it is essential to understand how ModernStats models help statistical organisations in their modernisation programmes.

    The session will give insight into the value and the statistical potential of these framework standards, show how they have evolved in the last 15 years and reflect on how the statistical community behind these models will ensure that the models will remain relevant considering the challenges for official statistics in the future.