Data for all: How professionals and non-professionals in design use and evaluate information visualizations

Graphic designers are increasingly involved in creating ‘popular’ data visualizations in mass media. We investigated graphic designers’ criteria for ‘good’ design for a general audience by interviewing professional designers and by reviewing information design handbooks. Two issues were central in the study: what is the relative importance of clarity and attractiveness, and what position do designers take in objective representation vs. subjective interpretation of data? Additionally, we investigated what might make an information visualization attractive in the view of designers. According to designers and design handbooks, clarity and attractiveness are the main criteria, with clarity having most emphasis. The designers’ aim is to objectively inform the public, rather than communicating personal opinions or concerns. Further, although aesthetics is considered important, design literature hardly addresses characteristics of aesthetics, and interviewees find it hard to define what makes a visualization attractive. Data for all. How professionals and non-professionals in design use and evaluate information visualizations 22 This chapter is based on: Quispel, A. , Maes, A. , and Schilperoord, J. (submitted). Information visualization for a general audience: the designer’s perspective. Data for all. How professionals and non-professionals in design use and evaluate information visualizations 22 23 Information visualization for a general audience: the designer’s perspective 2.1 Designing information visualizations for a general audience This explorative study takes the perspective of the producer of mass media information visualizations and addresses three issues that hitherto have only been amply discussed in theoretical and applied literature on information visualization1. What is the role and relative importance of clarity and attractiveness? Do designers aim to present objective information or convey subjective meaning? And what makes an information visualization attractive? The study is based on a collection of statements and opinions with respect to these issues which have been derived from two sources: interviews with professional designers and information design handbooks which are recommended and frequently consulted by information designers. Traditionally, information visualization techniques have been developed mainly for science and statistics, and were first and foremost meant to allow expert users to explore and analyze data quickly and accurately. In the past decades, however, many collections of data have become freely available, and so has software for data visualization. As a result, an increasing number of designers has started to apply visualization techniques to create data visualizations for popular purposes. At the same time, the intended audiences of those visualizations has expanded from expert users to include various groups of lay users as well (Vande Moere & Purchase, 2011). The increasing popularity of data visualizations is also testified by the growing number of books for non-expert users that provide guidelines for data visualization to be used by non-scientific readers and showcase a huge variety of popular data visualization techniques (e.g. Klanten, 2008; McCandless, 2009). Among the designers involved in creating popular data visualizations are many graphic designers and other types of designers such as interaction designers, who have been educated at art and design academies (e.g. http://www.catalogtree. net; http://lust.nl; http://tulpinteractive.com). Novel ways of visualizing data have been developed for business, government, newspapers, magazines, and internet platforms. These popular forms of data visualization are not only meant to allow an efficient and accurate reading of the data, as in science, but also to inform broad audiences about facts and developments in society. Consequently, designing such data visualizations may call for other design criteria than the ones applied to design graphs meant to serve scientific, analytical purposes. In this study, we are especially interested in those other criteria. Some researchers in the scientific field of information visualization assume that aesthetic criteria are a key factor in communicating quantitative 1 In the scientific field of information visualization, the term information visualization refers to the computer-aided interactive visualization of big data with the aim to amplify cognition (Card, MacKinlay, & Shneiderman. 1999). In graphic design, the term refers to a broader category of visualizations meant to inform or instruct people, including data visualization. In this article with the term information visualization we refer to the visualization of quantitative data, be it limited or big, static or interactive. Data for all. How professionals and non-professionals in design use and evaluate information visualizations 24 information to broad audiences (e.g. Judelman, 2004; Kosara, 2007; Lau & Vande Moere, 2007; Vande Moere & Purchase, 2011). Those researchers propose collaborations between scientists and designers to strike an adequate balance between information value on the one hand and aesthetics on the other, i.e. between clarity and attractiveness. They thus implicitly assume that aesthetics is part of the expertise of designers. Some also seem to suggest that designers of popular data visualizations tend to put more emphasis on attractiveness than on clarity. As Vande Moere and Purchase put it: ‘(.) complex and socially relevant issues might best be communicated to a large audience through popular media using an artistic and engaging visualization (even if its designer knows that such a method is not the most effective or efficient). ’ (p.361). According to Kosara (2007) ‘artistic’ and ‘pragmatic’ forms of visualizations even seem irreconcilable: ‘Visual efficiency does not play a role in artistic visualization, quite the contrary. The goal is not to enable the user to read the data, but to understand the basic concern. ’(p.634). Related to this latter quote, is the assumption made by several researchers that designers intend to convey subjective meaning underlying the data, rather than objectively presenting data and facilitating insight in the data (e.g. Kosara, 2007; Lau & Vande Moere, 2007). Designers would employ ‘ambiguous and interpretative methods’ in order to engage the user and provoke personal reflection (Gaver, Beaver, & Benford, 2003), and their designs are supposed to involve subjective decisions and stylistic influences, and to be highly interpretative (Lau & Vande Moere, 2007). The assumptions as described above reflect the way some scientists in the field of information visualization and human-computer interaction think about characteristics of popular information visualizations. But how do designers themselves think about these matters? In the present study, we take the perspective of the designers as the producers of popular data visualizations as a starting point. To shed light on these matters, we interviewed ten professional designers In addition, several handbooks on data visualization were reviewed in search for criteria for data visualization for a general audience. The selected handbooks can be assumed to reflect ‘best practices’ in information design because they are recommended by the International Institute for Information Design (IIID); an authoritative institution in the field of information design; and because they are frequently consulted by designers. In particular, we focused on the following questions: How do designers look upon the relative importance of clarity and attractiveness in information design? Any message, be it casted verbally or visually, is created with the objective to be understood by the intended audience. Therefore, the message should first and foremost be clear and understandable. At the same time, however, in order to be notified in the first place, the message must attract and hold attention; in other words the message has to be attractive for the intended audience. In this study, we consulted designers about what they consider to be the most Data for all. How professionals and non-professionals in design use and evaluate information visualizations 24 25 important criterion in designing visualizations. Do they consider clarity to be more important or attractiveness? Or do they consider clarity and attractiveness equally important? What position do designers take in objective representation of data vs. providing subjective interpretation in visualizing information? When people use language, they have many conventional signals at their disposal to differentiate between expressing objective vs. subjective content (modal verbs, different types of connectives, etc.). When designers communicate messages using the visual modality, they arguably also aim at expressing either objective knowledge or subjective interpretations of it. However, the visual modality may not have a conventionalized set of signals to mark the difference between facts and opinions. So, the question is whether designers differentiate between these two types of information in their designs, and, if so, how they mark this distinction. With the interviews and literature review, we wanted to investigate the opinions of designers with respect to this objectivesubjective issue. What do designers consider the defining characteristics of attractiveness in information design? Scientific studies in information visualization usually do not offer explicit hypotheses about what might make an information visualization attractive. Aesthetics is a very complex notion, and several theories and studies have been constructed and conducted about features of aesthetics (e.g. Hekkert, 2006; Reber, Schwarz, & Winkielman, 2004). Some studies start from the theoretical assumption that novelty (or related notions like originality, innovativeness, or uniqueness) is a factor causing attractiveness (e.g. Lavie & Tract