Fall 2021
What is Information Visualization?

300 years later, Lev Manovich point out the success of Playfair’s method and the cognitive power of information visualization. The symbiotic relation between human cognition and information visualization is now driven by the designer’s access to developing technologies adopting high-level programming languages and APIs 2.

Robertson, Card and Mackinlay name an application Information Visualization with which they

animated in 2D and 3D to explore information and its structure. Their research described the automatic generation of graphical presentations of relational information (e.g. bar charts, scatter plots, node and link diagrams)3. They used computer generated graphics to present information through 2D static visuals and explored the use of 3D and interactive animation. Their definition of information visualization is bonded with the use of computer-supported, interactive, visual representation of abstract data do amplify cognition4 .

This definition brings the focus on what is represented in the first place and the origin of the data. Despite the consistent concept of cognition amplification, their definition distinguishes empirical scientific from abstract information visualization.

In accordance with the Oxford Dictionary, visualization involves a mindful cognitive activity in which humans engage, whether technology is involved or not. Card explains that the goal of a visualization is insight, not pictures, while externalization of the cognitive visualization using tools (which can be as simple as a pen and paper) can extend the person’s working memory and result with a “more effective visualization” 5 .

Norman adds that It is things that make us smart6 since external aids can enhance cognitive abilities and graphics can be one of those “things” as they can be grasped through visual cognition deciphering visual quantitative relations.

Chen’s definition of information visualization is: “representations of the semantics or meaning of information7” without dealing with any quantitative data.

All these categories and definition of information visualization can cause blurry and confusing boundaries between data visualization, information visualization and scientific visualization. Overlap between the three can be found when certain conditions are met since information visualization is an interdisciplinary intersecting human-computer interaction, graphic design, and statistics.

Let’s investigate what has been claimed about the role of aesthetics in information visualization trough more contemporary definitions that cover the role of design.

Manuel Lima’s Information Visualization Manifesto contains a distinction between information art and information aesthetics leading to 10 directions to design information visualizations:

1. Form follows function – form follows revelation.

2. Start with a question

3. Interactivity is the key.

4. Cite your source.

5. The power of narrative – using narratives.

6. Do not glorify aesthetics.

7. Look for relevancy.

8. Embrace time – envisioning data through time.

9. Aspire for knowledge.

10. Avoid gratuitous visualizations. 8

These strict guidelines limit designers to only make meaningful choices as they execute visualizations, in accordance with Edward Tufte’s rule: “above all else show the data 9 . Tufte and Lima vilify additional visuals not relevant to any information or data being visualized. Otherwise, Tufte remedies a good design with narrative power, sometimes by immense detail, and sometimes by elegant presentation of simple but interesting data 10.

In opposition to these restrictions, Ellen Lupton brings up the fact that information visualization can be richly expressive, creating evocative pictures that reveal surprising relationships and impress the eye with the sublime density and grandeur of a body of data 11 , embracing graphic design and expressivity in the process.

Andrea Lau and Andrew Moere emphasize that information aesthetics are driven by: Representing data, providing an interactive interface, and using visual appeal to engage the user12. Lau defines information aesthetics as the link between visualization and visualization art in the attempt to appeal to specific fields and audiences.

Vande Moere and Purchase saw information visualization specific to experts and as objective as possible “portraying data in a scientific and neutral way”. However with Data and technology becoming more accessible Information visualization is well adopted by the mainstream user. Vande Moere and Purchase also clearly map information visualization on three axes13 : visualization studies related to empirical academic research driven by computer science, visualization practice as the design practice with the approach of problem solving and visualization exploration with innovative visionary approaches developing new techniques.

Visualization exploration can lead to a more artistic data visualization, a term coined by Viegas and Wattenberg describing mass communication that employs vigorous perspectives of their authors 14. This subjectivity is the opposite of a scientific visualization. Viegas and Wattenberg explain that perfect objectivity seeked by the scientific community is impossible just as it impossible to create a flat map of the Earth’s surface without distorting distances 15. Their solution is for the designer to minimize the intrusion of point of-view by working with a perspective that is right for a given analytic task.

On another hand, visualization exploration can drive casual information visualization, a term defined by Pousman et al., developing new traditions of information design focused on the characterization of the target audience, the objectives of the authors and the contexts of the visualization 15 to create usefulness, enjoyment, and reflection.

Heer et al. explains that information visualization users are utilizing visualization tools, from expert developers to savvy designers and novice consumers 16, emphasizing the effortless “communication-driven” goals.

I will conclude this evolution of perspectives on information visualization with Fallman’s reminder, that Design in visualization is not art since it still has a functional purpose that is the clear communication of a data-driven message17. It is its own pillar, between science and art, a tradition guiding action and thought, which spans across many disciplines 18.