My Favorite Visualizations - August
Nowadays, Data is a big part of science and technology advancements. Researchers use data to develop models, discover patterns, and predict the future behavior. However, mathematical knowledge and statistical methods are not enough to make sense out of the data. Data visualization techniques enable us to represent the meaning behind our findings.
In my daily browsing, I usually encounter with some amazing visualizations which motivate me to read the article and understand it in an easy way. So I decided to pull them up together and publish them monthly. So here is My Favorite Visualizations for August.
1. Mapping the Flow of International Trade
Max Galka, a NYC-based entrepreneur and adjunct instructor at UPenn has used the UN Comtrade database to map the flow of goods around the globe. Each dot - colored by the type of the good - represents the value of $1 billion. Max gives some examples of what we can see on the map. For instance, Germany is the largest economy in Europe and is the number one exporter to other EU countries. In another example, even though the new government in the United States indices the idea of having a one-way economic relation with Mexico, the US has roughly balanced its imports and exports with Mexico ($240 billion and 294$ billion). Learn more about it here.
2. The International Network of Weapon Trade
Tamer Khraisha is a PhD candidate at the Center for Network Science at the Central European University in Budapest. His visualization shows the weapon trade among countries from 1955 to 2005 with five-year intervals. It can be seen which country buys and which one sells weapon. For example the major customers of the United States are United Arab Emirates, Israel, and Saudi Arabia; however, European countries have a more diverse range of customers and buyers. You can find the interactive version of this visualization here.
3. Mapping the Human Diseasome
This is old but gold! Back in 2007, Kwang-II Goh and his colleagues developed the Human Diseasome Network in which disorders and disease genes are linked by known disorder-gene associations. Their work is supporting the existence of distinct disease-specific functional modules. The New York Times has a beautiful version of it that you can find it here.