Build a Global Refugee Population Dashboard

Turn UNHCR population records into a revision-aware dashboard for refugee and displacement trends. The UNHCR Refugee Data Scraper provides a bounded connector to the authoritative publisher while preserving stable identifiers and source URLs on every row.

Start with a small, reviewable query

{"mode":"population","yearFrom":2020,"yearTo":2025,"maxResults":500}

Run a small sample before expanding the result limit. Inspect identifiers, dates, null values, units, qualifiers, and source fields in the Apify Dataset. Export as JSON for nested fields or CSV and Excel for review. For recurring ingestion, upsert on the publisher stable record dimensions instead of assuming every run is append-only.

Build a reliable data pipeline

The Actor uses direct HTTP requests, bounded inputs, transient-error retries, and explicit empty-result failures. It does not require a browser or paid proxy, so scheduled runs remain inexpensive. Keep the input in an Apify Task, send completion through a webhook, and load the dataset into a warehouse or dashboard. Store collection time downstream so source revisions can be distinguished from newly published records.

Interpret the source responsibly

Official publication does not remove the need for context. Preserve footnotes, status fields, dataset type, reporting period, and source attribution. A missing value is not zero, and a revised record is not necessarily a new event. For legal, medical, financial, safety, protection, or public-policy decisions, confirm material findings with the publisher and a qualified specialist.

This workflow is designed for humanitarian analysts, journalists, and policy researchers. It is an independent integration and is not affiliated with or endorsed by the source institution.

Design the dashboard around movements and stocks

A useful refugee dashboard separates the population observed at year end from movements recorded during the year. Put headline totals above a country-by-country table, then add origin-to-asylum flows as a second view. Use a consistent color for each population type and never imply that two categories are interchangeable. A year selector should expose whether a change is a new displacement, a return, resettlement, naturalization, or a source revision. Add the UNHCR source link beside the freshness date, and show an explicit “data unavailable” state instead of plotting missing values as zero. Those choices make the dashboard suitable for operational review rather than merely attractive.