We present an interactive Shiny application designed to democratize access to data from the Comprehensive Household Survey, or GEIH, with special emphasis on Venezuelan migration patterns and labor market dynamics. Our application addresses the growing need for accessible and reproducible demographic research tools. Through a modular architecture encompassing demographics, education, labor markets, housing, and health indicators, we have created a platform that serves academics, policymakers, NGOs, and public officials. The application leverages advanced R packages including data. table for efficient large-scale data processing, plotly for interactive visualizations, and shinydashboard for intuitive user interfaces. Our implementation demonstrates how complex statistical analysis can be made accessible without requiring extensive programming knowledge from end users. We discuss the technical challenges encountered in processing multi-module GEIH data and performance optimization strategies for large datasets. The application facilitates reproducible research by enabling data export in multiple formats and providing public access to source code under the MIT license.

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Interactive Visualization and Analysis of Colombia’s GEIH Data: A Shiny Application for Reproducible Demographic and Labor Market Research

  • Iván Cruz,
  • Daniel Molina,
  • Alic Barandica

摘要

We present an interactive Shiny application designed to democratize access to data from the Comprehensive Household Survey, or GEIH, with special emphasis on Venezuelan migration patterns and labor market dynamics. Our application addresses the growing need for accessible and reproducible demographic research tools. Through a modular architecture encompassing demographics, education, labor markets, housing, and health indicators, we have created a platform that serves academics, policymakers, NGOs, and public officials. The application leverages advanced R packages including data. table for efficient large-scale data processing, plotly for interactive visualizations, and shinydashboard for intuitive user interfaces. Our implementation demonstrates how complex statistical analysis can be made accessible without requiring extensive programming knowledge from end users. We discuss the technical challenges encountered in processing multi-module GEIH data and performance optimization strategies for large datasets. The application facilitates reproducible research by enabling data export in multiple formats and providing public access to source code under the MIT license.