Exhibiting Hierarchical Data Using Data Visualization Techniques
In the realm of data analysis, understanding hierarchical relationships is crucial. This article explores various information visualization techniques designed to illuminate parent-child relationships, nested groups, and levels of data structure within hierarchies.
One of the most common methods is the **Tree Diagram** or **Decision Tree**, coined by Noam Chomsky in 1965. These branching structures are effective in representing hierarchical relationships, making it easy to trace pathways from a root node down to leaves. They are commonly used in file systems and decision-making processes.
Another valuable tool is the **Flow Chart**, which visualizes processes or workflows with hierarchical steps and decision points. These diagrams are often employed to represent organizational or procedural hierarchies.
**Sunburst Diagrams**, circular, multi-level diagrams, show hierarchical data as concentric rings, effectively visualizing proportions and nested structures.
**Treemaps** use nested rectangles to represent hierarchical data, where the size and colour of each rectangle encode quantitative variables associated with the hierarchy’s nodes. Treemaps are space-efficient and ideal for showing proportions at multiple levels.
**Hierarchical Graph Layouts** are specifically designed for complex networks, arranging nodes at different levels to minimize edge crossings and improve readability of relationships in hierarchical planar graphs.
Some of these techniques, such as Treemaps and Decision Trees, also come in interactive forms, enhancing exploration and clarity in complex hierarchical datasets.
The **Treemap Diagram**, invented by Ben Shneiderman of the University of Maryland in 1990, is particularly useful for comparing nodes and seeing patterns within them. For instance, a Treemap Diagram of market share for different soft drinks was provided as an example.
The **Cone Tree Diagram**, developed at Xerox PARC in the 1990s, is a 3-D hierarchy model that works by arranging all child nodes of a root equidistant from the parent, forming a cone with some transparency. The process is repeated for each set of child nodes, with the diameter of the cone reduced at each level of the hierarchy.
A more recent addition to the family of tree diagrams is the **Botanical Tree Diagram**, invented by researchers at Eindhoven University of Technology in the Netherlands. This diagram extends the concept of tree diagrams by adding leaves and branches.
It's essential to remember that hierarchical data is a specialized form of network data, characterized by the principle of containment rather than connection between entities. A hierarchy begins with a root entity, which has at least one child node, and each child node can have zero or more children.
In summary, the most prominent hierarchical data visualization techniques include **Tree Diagrams**, **Flow Charts**, **Sunburst Diagrams**, **Treemaps**, and **Hierarchical Graph Layouts**, each suited for different contexts where hierarchy and nested relationships need to be clearly understood. Resources are available to learn more about these techniques, including Botanical Visualization of Huge Hierarchies and the work of Ben Shneiderman.
Technology plays a significant role in data-and-cloud computing, as it provides numerous tools for visualizing hierarchical relationships in data, such as Tree Diagrams, Flow Charts, Sunburst Diagrams, Treemaps, and Hierarchical Graph Layouts. Each of these techniques offers distinct advantages, making them suitable for various contexts where understanding hierarchy and nested relationships is crucial.
