Fall 2021
Information Visualization Approaches

“Information Visualization” is a term first coined by computer scientists working with networks and big scale data tables, but the practice of representing data visually with the goal of offering new insights, perspectives, and knowledge predates interaction with modern computers, having deep roots in the histories of graphic methods depending fundamentally on parallel advances in sciences, technology, humanities, art, design, data collection and statistical theory (Friendly, 2008). It is interdisciplinary in its foundation and practice

I would like to define (metaphorically) Information Visualization as a lens. Information Visualization is a process driven by the goal to put things in perspective just like a telescope or a microscope that magnify information and reveal the unseen. The information designer creates lenses to filter, reflect, refract light (curating and rearranging information) to put things in relative perspective.

The process starts when information is curated and classified as data, the data is then represented in an organized matter with visual marks in a system of encoding, to create a final product inviting exploration and offering “discoveries of both insights and knowledge” (Chen, 2017) in most cases. Other times, Information Visualization (just like a lens) is used to mislead, blur, and distort information but I will not dwell on this approach.

Either way this abstraction of information into a schematic form is to offer “the opportunity to act upon the understanding it offers” (Chen, 2017).

When talking about Information Visualization, there has been various needs for its application and different approaches:

Principles:

As a popular example, Tufte’s Principles for Information Visualization have been referenced in many and traditions of Information Visualization. Like a recipe to achieve what he calls graphical excellence, through “the well-designed presentation of interesting data” according to clarity, precision, and efficiency (Chen, 2017).

Some opposition to Tufte’s principles argues that visual embellishments can be an advantage, with the purpose of persuasion or presentation when what Tufte calls chart junk is designed “with the specific objective of aiding the memorability of the presented data” (Chen, 2017).

According to different principles, depending on the need and context of each Information visualization, a wide range of techniques are used, “these range from simple charts, such as bar and line graphs, to more advanced techniques, such as heat maps and scatter plot matrixes. Some of the techniques are created for a specific purpose” (Chen, 2017).

Perceptual aspects:

“Visual perception is relative, constantly scanning, constantly adjusting focus and constantly adapting” (Chen, 2017).

Chen explains that the information designer should take advantage of our understanding of human visual perception. Pre-attentive processing and the Gestalt Laws are great aspects of human perception that can be considered.

When a viewer perceives a visualization, what takes place in the sensory memory almost instantaneously and unconsciously is the detection of the pre-attentive visual properties by the “lower-level” visual system. These properties can be used for information to “pop out” (Chen, 2017).

Gestalt laws study the arrangement of visual symbols and how people interpret the world in relation to perceptual organization and its meaning. Such pattern perception can be applied by information designer to convey knowledge immediately and through nested levels, “visualization aids cognition due to the ways that it increases memory and the processing of resources available through pre-attentive properties” (Chen, 2017).

Sources:

Hsuanwei Chen’s report on information visualization (In Library Technology Reports, American Library Association, 2017).

A Brief History of Data Visualization - Handbook of Data Visualization - Michael Friendly - 2008.