Guidelines on metadata management when implementing the generic statistical business process model (GSBPM)

Metadata management

Guidelines on metadata management when implementing the generic statistical business process model (GSBPM)

Bienio:
2024-2025
Coordinator
Departamento Administrativo Nacional de Estadística (DANE) of Colombia
Technical Secretariat
Statistics Division of ECLAC
Members
National Institute of Statistics and Censuses (INDEC) of Argentina
Brazilian Institute of Geography and Statistics (IBGE)
Instituto Nacional de Estadísticas (INE) of Chile
Instituto Nacional de Estadística y Censos (INEC) of Costa Rica
Oficina Nacional de Estadística e Información (ONEI) of Cuba
Instituto Nacional de Estadística y Censos (INEC) of Ecuador
Instituto Nacional de Estadística (INE) of Honduras
Instituto Nacional de Estadística y Geografía (INEGI) of Mexico
Instituto Nacional de Estadística y Censo (INEC) of Panama
Instituto Nacional de Estadística (INE) of Paraguay
National Institute of Statistics and Informatics (INEI) of Perú
Oficina Nacional de Estadística (ONE) of Dominican Republic
Instituto Nacional de Estadística (INE) of Uruguay
Objectives

General objective

Analyse the implementation of standards for the production and dissemination of official statistics (such as GSBPM) and the generation and management of metadata and encourage the exchange of good practices and the incorporation of innovations in the countries of the region to develop a technical manual with recommendations for metadata documentation and management in the production of statistics.

Specific objectives

  1. Identify the member countries of ECLAC that have implemented or are implementing GSBPM in statistics production processes.
  2. Conduct interviews and consult with selected countries’ national statistical offices, using digital forms, to obtain detailed information on the implementation of GSBPM and on metadata management.
  3. Review the existing documentation on statistics production processes in the selected countries, analysing their coverage and level of detail.
  4. Analyse metadata generation and management in the statistics production processes of selected countries, identifying good practices and challenges.
  5. Address the implications of using artificial intelligence tools to generate and manage documentation.
  6. Examine the regional context, explore a variety of innovations and good practices in the use of digital tools and media (such as videos and podcasts) and determine whether they can be considered metadata for producing statistics.
  7. Develop a technical manual with clear and practical recommendations for metadata documentation and management in the production of statistics, tailored to the particular characteristics of countries of the region.
  8. Foster the dissemination and adoption of the technical manual by national statistical offices in the region, through webinars, workshops and other media.