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UNECE ModernStats World Workshop 2024

UNECE ModernStats World Workshop 2024

21 - 22 October 2024
Geneva Switzerland

Background:

Modern statistical production systems require standardization of the processes, information and architectures that are involved in producing statistics, so that those processes can be automated, and information (including data) can be seamlessly passed between different systems, perhaps using software components that have been developed by another organization for the same purpose.

The need to do this has never been more pressing, due to the multiplicity of different sources of data, different outputs required, and different technologies that may be used to choreograph all of the required elements required to produce statistics.

This workshop is organized by the Supporting Standards Group, which maintains a set of standards and models for processes, information, architectures and other activities needed to produce statistics, and supports collaboration activities for their implementation, to provide a foundation for modern production.

This year's workshop is focused on the objectives of interoperability, governance, and of transparency, traceability and provenance in production, discussing the role of various models and standards for achieving those objectives. There will also be sessions showcasing the use of models and the future of production.

Abstracts for the different topics of this workshop can be found below.

  • Practical information for planning your participation can be found here
  • Further details about the topics of this workshop can be found here
  • Register via the following site to receive further info about this event: https://indico.un.org/e/MWW2024

Abstracts:

Title Abstract

Topic: Interoperability using Standards and Models

 
The DDI Cross-Domain Integration (DDI-CDI) Specification: Overview and Implementations, CODATA and DDI pdf
The statistical production LEGO set: using standard models and tools to build metadata-driven pipelines at StatCan, Statistics Canada pdf
Using standards to develop a system for coherent metadata for production and dissemination in Denmark, Statistics Denmark pdf
Enhancing Interoperability and Transparency through Linked Open Data Standards: Lessons Learned from the ESS LOD Community of Practice, Eurostat pdf

Topic: Transparency, traceability and provenance

 
From micro to macro data: ModernStats models for the conceptual modelling of statistical metadata in an interoperability perspective, Italian National Institute of Statistics (Istat) pdf
Unlocking data transparency: how improved metadata empowers IMF data users., International Monetary Fund pdf
Describing and Querying Data Transformation Scripts: SDTL and SDTH, University of Michigan pdf

Topic: Governance

 
Streamlining statistical and data production, Statistics Finland pdf
The designed governance for a central metadata system, Istat pdf
A reference framework for structural metadata governance, OECD pdf
Simplifying the Reuse of Concepts Across Organisations, Federal Statistical Office (FSO) pdf

Topic: Using ModernStats models

 
Tau-Argus: Lessons learned of sharing an IT-tool in Official Statistics, Statistisches Bundesamt (Destatis) pdf
Applying GSBPM to processes based on new data sources, Istat pdf
Using standards to direct the flow of data: Modernizing production processes at Statistics Iceland, Statistics Iceland pdf
Adopting GSBPM in a national statistical institute, Statistics Denmark pdf
Modeling of Business Process Activities and Data: GSBPM, GSIM, and BPMN, National Institute of Statistics and Geography (INEGI, México) pdf

Topic: Modern production in 2025 and beyond

 
Incorporating AI into statistical standards: Enhancing GSBPM with (generative) AI, Statistics Finland pdf
Modernizing the BIS Data Bank: A Metadata-Driven Approach to Statistical Business Processes and SDMX Integration, Bank for International Settlements pdf
A dataset catalogue as a tool for automated and metadata driven statistical production, Statistics Sweden pdf
Modernization and agility powered by Communities of Practice, Statistics Netherlands pdf
Capabilities and Metadata Standards, US Bureau of Labor Statistics pdf
Tools For Automating Metadata-Driven Processes In Statistics Poland, Statistics Poland pdf