History of
Ben Shneiderman is considered to be the inventor of Treemaps. He created treemaps as a way to visualize a vast file directory on a computer, without taking up too much space on the screen. Treemap has subsequently become an essential method for displaying hierarchical data using nested figures and rectangles in information visualization and computing. A number of different algorithms can be used to determine how the rectangles in a treemap should be sized and ordered.
When to Use a Treemap?
1
When you need to make hierarchical data easy to read and analyze
Use treemaps to make hierarchies easier to understand, through rectangles ranging in size from the top left corner of the visualization to the bottom right corner, with the largest rectangle positioned in the top left corner and the smallest rectangle in the bottom right corner. Colour is also used to differentiate allowing one to show both the importance (usually shown by size) and urgency (usually shown by color) of a data point. For nested rectangles size, and thereby also position, of a rectangle that contains other rectangles, is decided by the sum of the areas of the contained rectangles.
An interactive treemap chart for visualizing proportions in hierarchical data, where nodes of a tree are represented as nested fully-packed rectangular tiles.
Advantages of Diagnosis
1. Problem formulation based on symptoms
One of the methods that help researchers trace the cause and effect relationship between product elements or features and user behavior.
2. Critical thinking
Diagnosis requires critical thinking and analysis to formulate the real problems that need to be addressed to deduce a solution.
3. Time effective
Diagnosis is quick and time effective when using online tools and can be used to analyze large chunks of data gathered from large sample groups.
4. Online tools for data analysis
Many online tools can be employed to gather data, carry out analysis on this data to spot patterns or symptoms which can the ultimate diagnosis of the problem much more streamlined for the researchers.
Disadvantages of Diagnosis
1. Experienced researcher
An experienced researcher who is familiar with critical or Bayesian thinking would be more effective at diagnosis than any researcher.
2. Incorrect symptom evaluation
If the symptoms are not evaluated correctly or the researcher fails to ask the right questions, the diagnosis of the problem and its optimum solution may be way off.