Chart taxonomies help analysts and designers make informed decisions about what charts to use when. However, data visualization instructors hold contradictory views on the usefulness of these taxonomies. While some regard it as a starting place for people new to data visualization, others believe these taxonomies oversimplify chart selection and limit innovation in design.
There are many points for and against chart taxonomies. To begin with, we will examine the points against them. Chart taxonomies can give the impression that charts are by themselves irreducible units of visualization. Hence, learning the chart types themselves does not allow practitioners to understand the concepts behind and beyond the chart taxonomies. Additionally, chart taxonomies ignore the larger ecosystem of information and can oversimplify the process of chart selection. This may cause data visualization designers to ignore the principles of visual encodings.
Moreover, limiting design decisions to a list of charts for a given function would eliminate innovation in the data visualization space. Furthermore, many different names for the same kind of chart make chart selection unreliable and confusing. Above all, the effort invested in researching and discussing chart types, if focused on the fundamentals of visualization would be more rewarding.
Those who support chart taxonomies begin by putting forth the point that chart taxonomies can help beginners organize options on how to visualize a given dataset or analysis result. Moreover, finding ways to group like charts can help create a shared language and organize ideas in the relatively new data visualization field. Additionally, the data visualization field will benefit when even the most infrequent visualizers have tools and resources that help make better chart selections. Furthermore, taxonomies can be designed as compelling visual displays to prompt conversation and discussion. This will help young data visualization enthusiasts to display their love for data visualization to colleagues.
What is given above is a summary of a discussion between a group of semantics and data enthusiasts on the Data Visualization Society’s (DVS) Terminology channel.
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