For the next two weeks the 19 Million Project will meet in Rome to wrestle with how data, design and journalism can best tell the heartbreaking stories produced by the refugee crisis which has sprung out of Syria, Iraq and Afghanistan. The project brings a pretty brilliant cross-functional team together to see what they can make of the data that’s out there.
You can find a pretty comprehensive list of data sources here, in this blog post produced after an open call for data on the issue. I thought it would be interesting to go more in-depth on one of those links, the UNHCR official database.
This is the world’s audit of refugees, produced annually and covering everywhere the United Nations’ refugee agency operates (which does not include Palestinian refugees monitored by the UNRWA). I used it to create this map for Mother Jones.
So what can you learn from that data? Here are three datasets, cleaned up and ready to download, as Google spreadsheets:
What it shows: Origin of refugees by country in 2014 — the latest year’s worth of data.
What you could do with it: This shows the state of the world’s refugees in 2014 — a representation of the world’s war zones and trouble spots. This could be mashed up with other data to show correlations with other data, such as poverty, civil unrest, war and so on.
What it shows: Location of refugees by country in 2014 — the latest year’s worth of data. Plus: internally displaced population for each country where it’s recorded; number of refugees as a proportion of the total population in each place.
What you could do with it: I’ve added the population ratios for each country, so you can get a sense of the true scale of the refugee population in each country. It shows that most refugees stay nearby their home country, or remain in it if they can. In the UK, for instance, there was a refugee population of around 116 per million people of concern to the UNHCR. In Syria, for every million population, over 400,000 are refugees.
What it shows: The UNHCR ‘population of concern’ by location in each country by year.
What you could do with it: This is the dataset to show flows from one country to another over time. You could use it to show how the world’s refugee population have been forced from one location to another.