Sankey charts, a type of diagram known for their use in creating visual representations of network structures, have historically been used within the fields of anthropology, sociology, and many other disciplines. However, their potential for revealing hidden relationships is starting to gain more attention from researchers and practitioners alike, particularly as they relate to complex systems. In this article, we’ll explore some of the ways these charts can be used to unlock hidden relationships within a system, and how they can help us gain a more nuanced understanding of the world.
First and foremost, the creation of a Sankey chart is a visual exploration of a network structure. A network structure is a layout of elements (such as nodes and links) where the order and arrangement of the elements create a meaningful pattern or pattern. Within a network structure, nodes often represent different types or attributes of the elements on which it is being based on, while links represent a relationship between those nodes. For example, in the infographic below, we have a network structure representing a company, where the nodes are departments and the links represent the way they are related to each other.
To create a Sankey chart, one takes a graph of the elements in the network and repositions elements to ensure that the nodes represent their underlying characteristics (labels), while the links represent their relationship to each other. For example, in the graph above, the red node represents sales, while the green node represents product development. The links connecting the two nodes represent the way the sales and product development teams work together.
However, as we delve deeper into the connections within a network structure, we often find that these connections are not fully or fully represented within the graph. This is where Sankey charts can be incredibly powerful. By using color and color gradient techniques within the chart, we can help reveal these hidden relationships. The following infographic offers a great example of this, visualizing the relationships between different departments within a company based on the information in the graph above.
By overlaying the graph with information about the departments, we can see that there are some interesting relationships that we might not have noticed before. For example, in the top row of the graph, Sales is connected to two different departments, Human Resources and Marketing. This suggests that the sales department has a strong connection to the marketing and HR departments, while the other department, Development, doesn’t seem to be as interconnected.
The use of Sankey charts for visualization of hidden relationships is just one way these charts can be applied. There’s a wide variety of applications for Sankey charts, and below are some examples:
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Economic modeling – Sankey charts can be used to visualize the relationships between different industries, regions, or nations, to gain insight into complex systems.
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Biomedical – Sankey charts can be used to visualize the relationships between different organs and systems within the human body, in order to build a better understanding of biological processes.
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Environmental science – Sankey charts can be used to visualize the relationships between different pollutants and environmental resources, to understand the dynamics of complex environmental systems.
Overall, the use of Sankey charts for visualization of hidden relationships within complex systems is a powerful tool for gaining a deeper understanding of the world around us. By using these diagrams, we can explore networks, visualize relationships, and uncover patterns that may be hidden from plain sight. So the next time you have a complex system to understand, don’t just focus on the surface relationships – use a Sankey chart to uncover the hidden relationships that can reveal a deeper, more nuanced understanding.
SankeyMaster
SankeyMaster is your go-to tool for creating complex Sankey charts . Easily enter data and create Sankey charts that accurately reveal intricate data relationships.
