Taxonomy of Data Visualization Methods - Data Visualization: A Successful Design Process - page 114

Data visualization methods
The common definition for taxonomy comes from the biological sciences and refers
to the organization into groups of members that share similar characteristics. In
this case, the members are chart types and the shared characteristic is based on the
primary data portrayal function.

Selecting the appropriate visualization method will be influenced by the definition
work you undertook earlier in the methodology to clarify the intention of your
visualization communication.

It is about starting the journey towards identifying the most suitable way to answer
your main data questions: how are you going to show, what it is you want to say.

Here is an outline of the primary communication purpose of each method
classification:

Method classification Communication purpose

Comparing categories To facilitate comparisons between the relative and

absolute sizes of categorical values. The classic example
would be the bar chart.

Assessing hierarchies and
part-to-whole relationships

To provide a breakdown of categorical values in their
relationship to a population of values or as constituent
elements of hierarchical structures. The example here
would be the pie chart.

Showing changes over time To exploit temporal data and show the changing trends

and patterns of values over a continuous timeframe. A
typical example is the line chart.

Plotting connections and
relationships

To assess the associations, distributions, and patterns
that exists between multivariate datasets. This collection
of solutions reflects some of the most complex visual
solutions and usually focuses on facilitating exploratory
analysis. A common example would be the scatter plot.

Mapping geo-spatial data To plot and present datasets with geo-spatial properties

via the many different mapping frameworks. A popular
approach would be the choropleth map.

Once we have selected the appropriate method, we then start to work through the
other key ingredients of the data representation selection process, as outlined in
Chapter 4 , Conceiving and Reasoning Visualization Design Options .