Logical Modelling of Statistical Data Using the SDMX Standard: Case Study on the Quarterly Gross Regional Domestic Product Table

Abstract

Poverty, as a national issue, necessitates data-driven policy planning informed by
accurate and consistent statistics. To ensure the optimal quality and consistency of statistical data
reporting across diverse regions, the adoption of an international standard is crucial. The
Statistical Data and Metadata Exchange (SDMX) standard facilitates the structured exchange of
data and metadata. This study aims to design and implement a statistical indicator data model
using the SDMX standard to improve table consistency. We utilized Quarterly Provincial Gross
Regional Domestic Product (GRDP) data as a case study and applied the Design Science
Research Method (DSRM) as the methodology. The results demonstrate that modeling the
GRDP data using SDMX yields a uniform and highly consistent table structure, significantly
enhancing the consistency of statistical data reporting across regions.