Volume 49 - Article 40 | Pages 1117–1162  

Programmatic access to open statistical data for population studies: The SDMX standard

By Frans Willekens

Abstract

Background: The public sector publishes vast amounts of open data and metadata. APIs (application programming interfaces) are transforming the way data are collected, documented, and disseminated. The transformation is slow, however, due to differences in communication protocol, data definition, and data format. The development is of particular relevance to demography, being a data-intensive science. It paves the way to the automation of data acquisition and the integration of data acquisition and data analysis. Together with the parallel development of literate programming, which allows the integration of text and computer code in a single document, programmatic access to data makes workflows transparent, verifiable, and easy to replicate by others. The Statistical Data and Metadata Exchange (SDMX) standard, which has emerged as a popular option for data and metadata exchange, makes finding and retrieving data and metadata easy and swift. Query strings form URLs with a standardised syntax.

Objective: The aim of this paper is to describe the SDMX standard and demonstrate its benefits to our profession by retrieving demographic data and the associated metadata from online databases disseminated by a variety of data providers. The software environment used is R.

Contribution: This is the first review of the SDMX standard aimed at the study of population. The paper includes the R code to access databases and download data and metadata. The paper includes several hyperlinks to relevant documents issued by data providers, giving readers immediate access to the referenced material.

Author's Affiliation

  • Frans Willekens - Nederlands Interdisciplinair Demografisch Instituut (NIDI), the Netherlands EMAIL

Other articles by the same author/authors in Demographic Research

Interdisciplinary Research on Healthy Aging: Introduction
Volume 38 - Article 10

Visualizing compositional data on the Lexis surface
Volume 36 - Article 21

Software for multistate analysis
Volume 31 - Article 14

Chronological objects in demographic research
Volume 28 - Article 23

Cited References: 28

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