Annually, international wildlife trade is estimated to be worth billions of dollars and to include hundreds of millions of plant and animal. The trade is diverse, ranging from live animals and plants to a vast array of wildlife products. I found an interesting dataset on CITES website. It has a database of wildlife trade from 1975 to 2021, which contains records on every international import or export conducted with legal species from the CITES lists. I used this dataset to visualize 4 questions that I'm interested in. I also conducted usability testings for refinment.
3 Questions I want to figure out about wildlife trade
1. International Wildlife Trade (2020)
Since the dataset is about international trade, I thought I could make a Sankey diagram to show the flow of these wildlife among different countries. However, I found it is complicated to make a Sankey diagram by Tableau. There are some tutorials of Sankey diagram made with Power BI which is a data visualization and analysis software by Microsoft. Power BI is similar to Tableau. Both of them are friendly to beginners. I decided to use Power BI to do the Sankey diagram of international wildlife trade. However, since there are nearly 200 countries/regions in my dataset, the diagram looks so messy. [Figure 1] My idea of Sankey diagram failed.
As I was thinking of giving up this new attempt, the chord diagram suddenly came in my mind. Because each trade is between two countries/regions, a circle of all countries/regions is suitable for visualizing the flow among them. It is even better than Sankey diagram! However, I met the problem again. Although Power BI is also able to make the chord diagram, it cannot process all data and looks strange. [Figure 2]
Figure 1
Figure 2
I did not want to waste this idea of chord diagram, so I searched which software could be used to make it. Some people wrote the tutorial of using R to make chord diagrams. I refused to open it in the beginning, because R is too hard to learn quickly. However, after trying several online software, and finding that they had the same problem with Power BI which cannot process so much data, I finally turned to R. I have seen its capability to process thousands of data in my previous project.
Data clean & visulization
The chord diagram needs a data structure that is different from the original one. There are more than 30,000 pieces of data, and I really did not know how to transform the data structure to what I need. Luckily, I finally got the right data structure with the help of Prof James using R. [Figure 3]
Figure 3
There is no doubt that using R to make visualization is very challenging to me. I looked at so many tutorials and tried over and over again during the whole process. I was thrilled when I saw the final chord diagram. It was awesome! The outside circle shows the code of each country/region. However, they are too small to be seen clearly. In order to improve the user experience, I added the flag and name of some main countries/regions beside the code using Sketch. [Figure 4]
Code in R to make a chord diagram
Result
From the diagram, it surprised me that Netherlands (NL) is the largest exporter of wildlife all over the world in 2020, and Germany (DE) is the largest importer of wildlife.
Figure 4
2. Top 10 Wildlife Export In Netherlands
From the chord diagram, we got to know that Netherlands (NL) is the largest exporter of wildlife in 2020. It made me want to explore what kind of wildlife that Netherlands exports.
Data clean & visulization
I used OpenRefine to sort all the exporters and only kept Netherlands (NL). [Figure 5] Then I used Tableau to make a bar chart. It ranks all the wildlife exported from Netherlands by the numbers of records. [Figure 6]
Figure 5
Figure 6
Result
From the bar chart, I found the number of records of Phalaenopsis hybrid is more than twice that of other species. Then I selected the Top 10 to figure out what are they exactly. After some searches, I found all of the Top 10 wildlife exported by Netherlands are plants. Since Taxon is the formal name of the wildlife, I do not know what they are. I decided to use Sketch to add the images of that plants beside their names. [Figure 7]
Figure 7
3. Top 10 Wildlife Import In Germany
From the chord diagram, we also got to know that Germany (DE) is the largest importer of wildlife. So what kind of wildlife does Germany import?
Data clean & visulization
The same with last data cleaning method, I used OpenRefine to sort all the importers and only kept Germany (DE). Then I used Tableau to make a bar chart. It ranks all the wildlife Imported to Germany by the numbers of records. I also selected the Top 10 wildlife imported to Germany and added their images beside their names in Sketch.
In the last bar chart of Netherlands, the terms of all the plants are “live”, so it is not necessary to show the terms. However, there are many kinds of terms in the chart of Germany including skins, leather products, trophies, etc. In addition, I would like to know the purpose of these imports. I used Tableau to make a stacked bar chart to show what I want to know above.
Result
The result in Germany is totally different from Netherlands. All of the imports are related to animals. From the stacked bar chart [Figure 8], most of the terms we found are skins and leather products. The colors of bars represent the purpose of imports. Macaca fascicularis is mostly imported for medical reasons. Apart from the purpose of importing Macaca fascicularis, the purposes of other imports mostly are “Commercial” and “Hunting trophy”. I guess most of them are used to make clothes, shoes, handbags, etc.
Figure 8
Usability Testing
Methods
Moderated usability testing is a qualitative study where the researcher’s goal was to discover the problems users face with looking at the visualizations. The participants were asked to look at the visualizations one by one. For each image, they were encouraged to speak out their thoughts at first glance. Then they were asked to complete the following tasks for each visualization.
Tasks
1. International Wildlife Trade (2020)
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Tell me what this visualization is talking about.
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Find out which country/region is the largest importer.
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Find out which country/region is the largest exporter.
2. Top 10 Wildlife Export In Netherlands (2020)
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Tell me what this visualization is talking about.
3. Top 10 Wildlife Import In Germany (2020)
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Tell me what this visualization is talking about.
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“Term” refers to the form or the parts of these wildlife. Find out what the term of crocodylus porosus is.
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Find out the purpose of importing alligator mississippiensis.
Findings & Improvements
Overall, both of the participants found the visualizations easy to understand. In particular, although neither of them heard of chord diagram before, they can understand it easily. Having said that, my usability testing showed that there are some problems that could be improved. The findings and the corresponding improvements are listed below.
1. International Wildlife Trade (2020)
Findings: Both of the participants feel confused about how to differentiate importer and exporter.
Improvements: I changed the end of the chord from flat to the arrow so that the viewers can see the direction of the chord. [Figure 9]
Figure 9
2. Top 10 Wildlife Export In Netherlands
Findings: Both of the participants thought this chart is easy to understand.
Improvements: Since this chart and the chart about Germany below follow the same design style, I swapped the row and the column to make them look consistent. I also got some good feedback from my viewer. He suggests adding the color palette to differentiate the different species being traded. [Figure 10]
Figure 10
3. Top 10 Wildlife Import In Germany
Findings: 1. Some words in the color blocks are not displayed. 2. If some terms (skin, leather products…) are concentrated in one color block, they did not know the number of each term.
Improvements: Firstly, I swapped the row and the column of this stacked bar chart so that leaving more space for the long words. Then I added the border to divide the blocks more clearly. [Figure 11]
Figure 11
Final Work
Since the last 3 visualizations tell one story on International Wildlife Trade, I combined them together.
Reflection
For the future direction, I have an idea that making a world map showing the paths between the importer and exporter. I tried several times, but I was stuck at the data structure. I would find a way to solve it if I had more time. What’s more, this idea could even be made on a 3D earth, which would be really cool!
Overall, although there were a couple of setbacks in the process, I really enjoy the time that solving problems over and over again, which gives me a sense of achievement!
References