Data is the main character behind visualization, and reverse visualization is the same as the first step in building a visualization from scratch: start with the raw data. The difference is that in reverse we see the final result of the data after graphical mapping, processing, and modification, while the raw data is hidden in the complexity of the visualization. Putting aside the flashy visualizations, finding the data and analyzing it is our first priority.

Step 2: Analyze the Graphics

Graphics is the key element in visualization, and it's also the part we pay most attention to. Analyzing graphics in a visualization can be done from many angles, and we can start with the whole thing

Step 3: Digging deeper into the technology behind it

Through the above analysis, we can actually create similar visualizations with some tools. But as a hardcore visualization player you can't stop there, you should dig deeper to understand the underlying implementation methods. We can view the source code of open source tools,

Step 4: Implementation

When you get to this point, don't you want to visualize it yourself? With the data, analyzed structure, and a deep understanding of the principles behind, the implementation will become very simple, and you can choose the right tool for your needs.

Step 5: Optimize for readability

In the analysis above we may have missed some details: optimizing for readability. Readability has a direct impact on the quality of visualization content; confusing colors and overlapping labels can greatly reduce readability. When reversing visualization cases, we should pay attention to discovering and accumulating methods to optimize for readability, so that we can better apply them to our own cases.