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Visualization Criticism – The Missing Link Between Information Visualization and Art Robert Kosara The University of North Carolina at Charlotte [email protected] Abstract of what constitutes visualization and a foundational theory are still missing. Even for the practical work that is be- Classifications of visualization are often based on tech- ing done, there is very little discussion of approaches, with nical criteria, and leave out artistic ways of visualizing in- many techniques being developed ad hoc or as incremental formation. Understanding the differences between informa- improvements of previous work. tion visualization and other forms of visual communication Since this is not a technical problem, a purely techni- provides important insights into the way the field works, cal approach cannot solve it. We therefore propose a third though, and also shows the path to new approaches. way of doing information visualization that not only takes We propose a classification of several types of informa- ideas from both artistic and pragmatic visualization, but uni- tion visualization based on aesthetic criteria. The notions fies them through the common concepts of critical thinking of artistic and pragmatic visualization are introduced, and and criticism. Visualization criticism can be applied to both their properties discussed. Finally, the idea of visualiza- artistic and pragmatic visualization, and will help to develop tion criticism is proposed, and its rules are laid out. Visu- the tools to build a bridge between them. alization criticism bridges the gap between design, art, and technical/pragmatic information visualization. It guides the view away from implementation details and single mouse 2 Related Work clicks to the meaning of a visualization. Several models of information visualization have been proposed. Most of them are very technical and describe ei- 1 Introduction ther the process of the visualization [4] or the data [17]. An interesting recent paper [20] uses two criteria to differenti- Two cultures exist in visualization: very technical, ate between information and scientific information: discrete analysis-oriented work on the one, and artistic pieces on the vs. continuous data, and whether the spatial layout of the vi- other hand. The type that shall be called pragmatic visu- sualization is given or chosen. alization below is mostly practiced by people in computer Sack [16] compares InfoVis to conceptual art, and ar- science with no background in art or design. A student once gues for the adoption of an aesthetics of administration: put it aptly: Computer graphics is mostly computers, but rather than looking at the surface, evaluate the type of gover- little graphics. At the same time, artists and designers of- nance a particular visualization enables. Sack’s article will ten work on visualizations without much knowledge of the be mentioned again below. technical work being done in computer science. Goodman’s theories on art and language [7, 14] provide Information visualization (InfoVis) is such an inherently an interesting approach to a classification of representation interdisciplinary field that it requires a much more inte- and the visual. His ideas about visual languages resonate grated approach. Since this is not the case right now, it well with information visualization, even though most vi- needs to be created from the two extremes that exist. In sualizations do not fulfill his requirements for a language. analogy to a concept in the natural sciences [2], this could Studying them is still useful to learn more about visualiza- be called the third culture of visualization. Such a third cul- tion and its relations to other fields. Cox [5] suggests a gen- ture would consist not only of people working in the respec- eralized view on visualization metaphors than it is usually tive fields, but a strong interchange of ideas between them. understood, thus linking the elusive (and often misunder- The techniques developed in both scientific and informa- stood) concept of the metaphor to concrete technical imple- tion visualization are certainly useful, but an clear picture mentations of visualization systems. 3 What is Information Visualization? Visualizations also have other properties like interaction, visual efficiency, etc. And while these are certainly impor- A good part of the confusion about visualization comes tant, the above criteria appear to be sufficient to precisely from the fact that there is no clear or generally accepted def- define information visualization the way it is generally used inition of visualization. Such a definition would clearly vary in its technical sense. between fields, but at least within one field (like computer While the first two criteria are quite obvious, the last science, design, illustration, etc.), it needs to be consistent. one is important for the rest of the discussion in this paper. Also, by understanding the differences between definitions Manovich [26] defines visualization as “situations when in different fields, we can identify elements that help in quantified data which by itself is not visual [...] is trans- building the bridge between them. These are not just the formed into a visual representation.” Of course, any pro- similarities though, but also the differences that require in- gram that produces a visual output translates some kind vestigation. of non-visual information into a visual representation. But Examples for visualization are: architectural visualiza- Manovich’s definition requires the program to get data from tion, terrain visualization, 3D medical/volume visualiza- outside, and not just produce it inside itself. Still, the crite- tion, 2D or 3D flow visualization, flow topology visualiza- rion is only necessary, but not sufficient: a transformation of tion, presentation graphics, abstract data visualization, in- data into a visual shape does not imply readability. An ex- formation dashboards, music visualization, photomontage ample for a visual mappings from data for use as icons are or collage, traffic signs, traffic signals, sign language, icons, VisualIDs [15]: unique visual forms that are based on data, visualizing oneself in a different job/situation, visualization but do not provide any information about it. One particular of concepts, drawing fractals, etc. class of visualizations that are data-based but not readable These are clearly very different types of visual commu- are music visualizations like MilkDrop [23] (Figure 1c), but nication, and many of them are not generally considered most artistic visualizations also fall into this group. visualization; others are, but only by specific groups. Why In addition to readability, a visualization has to be made is that? And how can we differentiate between them in a with the intent to communicate data. This can be illus- way that is not ad hoc? trated with an example of informative art [18]: a display We consider the following criteria to be a minimal set that looks like a Mondrian painting to show a bus schedule of requirements for any visualization. The remainder of (Figure 1b). The visualization is easily readable for those this discussion will concentrate on information visualiza- who know how, but not recognizable as one. Consequently, tion, but these criteria apply equally to scientific visualiza- one of the authors of that work later developed a model of tion. the comprehension of ambient displays [8], which consists It is based on (non-visual) data. The data to be visualized of three steps: realizing that data is being visualized by the must come from outside the program, and the program image, understanding what is being visualized, and how the must be able (at least in principle) to work on different display is to be read. Only when the user has reached that data sets. Also, visualization is not image processing last level can s/he make use of the display. or photography; if the source data is an image and is It can therefore be argued that the utilitarian appearance used as an image in the result, it is not being visualized. of many visualizations actually serves a purpose, in helping the user take at least the first step. The question remains, It produces an image. Clearly, each visualization has the though, if an aesthetically pleasing visualization has to ap- goal of producing one or more images from the data, pear like a work of art, or can be easily recognizable at the and the visual must be the primary means of commu- same time. nicating the data. Other media can be part of a visual- ization, but the visualization must be able to stand on its own. 4 Artistic and Pragmatic Visualization The result is readable and recognizable. There are many ways to transform data into images, most of which do Kelly [10] defines aesthetics as “critical reflection on art, not allow the viewer to understand the underlying data. culture, and nature”. Critical thinking is the basis of all sci- A visualization must produce images that are readable ence, and also connects the technical approaches to prag- by a viewer, even if that requires training and prac- matic visualization with philosophy and artistic visualiza- tice. Visualization images must also be recognizable tion. A particular type of critical thinking is an important as such, and not appear to be something else. The use part of the process in design and the arts: criticism (see of additional elements (or even “eye candy”) is cer- Section 5). Aesthetic approaches are also being applied to tainly possible, but must not take precedence over the computer science in an approach called aesthetic comput- communication goals of the visualization. ing [6]. a) b) c) Figure 1. The gamut of data-based visualization. a) Parallel Sets [12] show data about the people on the Titanic, and are readable and recognizable as a visualization; b) Ambient visualization [18] visualizing a bus schedule are readable but require more effort and are not readily recognizable as a visualization; c) Music visualization like MilkDrop [23] is also based on data, but not readable.

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