In this video, we're going to use the Our World in Data website to analyse inequality between different countries. So global inequality. Now, Our World in Data is an organisation which takes data that's been gathered by reputable sources and creates charts, so graphs and digital maps, which help us understand the different aspects of the geography of the world. So in this, we're wanting to look at inequality between countries. So one way we could do this is if we come to the top of the page, we can click on where it says Browse by topic. And you can see there's lots of different topics here that I can choose. And if I click on Health, for example, if I choose any of these, like Life Expectancy or Smoking or Cause of Death, it will create some graphs or it will display, I should say, some graphs and some maps related to those things around the world. So these are incredible ways of being able to visualise inequality between different countries. So there can be a load of different social inequalities that I can investigate, and maybe if I come down to Poverty and Economic Development, I can find some economic inequalities that I can investigate. So that's one way I can find these graphs and charts. Another way is just typing what I want to find into here and seeing if it's got it. So for example, if I type in GDP per capita, then we can see that it's actually got some information on this. And we can see there's a map down here where it said GDP per capita, 2023. So I'm going to click on this and here we go. Here's the map in front of us now. Now, GDP per capita, remember, is all the goods and services produced in a country in a year divided by the population. So it's kind of a measure of how wealthy the country is, how much income there is in a country. It's quite a narrow measure, if we're remember, of development, but it is one measure. So we can see the key at the bottom of the map and we can see where it has a lower figure. So lower income countries are in the sort of lighter greens and the darker blues are the higher income countries. Now, a useful aspect of this map is if I hover over a colour, it actually just highlights those countries around the world. So we can see here which countries are in the highest income bracket. We can see that there's a concentration in North America, Western Europe, and then pockets in the Middle East, East Asia, and Oceania. And again, if I hover over some of the lower numbers, then we can see that they're concentrated in sort of Sub-Sahara, Central Africa, and there's Afghanistan there in Asia. Now, I was quite careful about where I said there in Africa, Sub-Sahara means South of the Sahara Desert. And you know, Central Africa is an important term. And the reason why I'm saying that is if I keep going up these, I actually have to come right the way up to between 10,000 and $20,000 GDP per capita to highlight countries in the Southern tip of Africa and North Africa. So there is a real difference between the wealth, the GDP per capita of different countries in Africa. It's important to understand that. So that can help us analyse patterns between different parts of the world. Another useful thing I can do is if I actually hover over the country, it gives us the actual GDP per capita specifically and how much it's grown. And that can be quite useful because if we've got two countries in the same category, they might be quite different. If, for example, United States, they're both in the top category. United States, they're nearly at $75,000. Canada at around 55,000, so that's 56,000 really. So, you know, almost a $20,000 difference there. So that is quite significant. Now we know that GDP per capita is actually a fairly narrow measure of development. It doesn't tell us how much income inequality there is within a country, for example. It doesn't really tell us how happy people are. So there's lots of different problems with GDP per capita. So we would need to look at other maps here to start analysing inequality across the world. So if I choose another map, this one's Healthy life expectancy. So if we look at this section here, it says the estimated average number of years live free from disability or disease burden, we can then analyse the map again and again, I can highlight over one of the highest categories and we can see again, there's a concentration in West Europe and North America. You can also see Chile there. You'll notice though that the United States is not highlighted. I have to actually come down to the next category. So if we highlight over the two, the United States, just over 66 years, this is in 2019, remember, and Canada's actually over five years higher than that. So it's a reversal from the GDP per capita figures. And this is why it's important to look at different maps. Again, I can come to the lower numbers, see Lesotho there in the lowest category. And then again, we're going into different parts of the world, Central African Republic, Somalia there, and we can start analysing these patterns about where people's healthy life expectancy is lower or higher. So Our World in Data is a really useful website for us to analyse global inequality, both economic inequality and social inequality, environmental inequality. As long as I use different maps, I'm able to do that. So the question is, is this a geographic information system? And I think the answer to that is actually a little bit grey in that can we visualise geographical data? Absolutely, we can visualise geographical data over space here, spatial data. Can we analyse it and interpret it? Yes, we can. So in some ways, that makes it a geographic information system. However, there are certain functionalities that other GIS applications have that this doesn't. So I can't upload data, for example, onto the system. I can't put two layers of data onto one map and maybe toggle between the two or use a swipe or a transparency tool to be able to analyse the data in a little bit more detail. So we sometimes have to just choose the GIS application or the way we're getting our digital maps, depending on exactly what we want to do with it. But Our World in Data is an incredibly useful tool that we can use to analyse global inequality.