Before we launch in to the first stages of the methodology in Chapter 2, Setting the Purpose and Identifying Key Factors, it is important to acknowledge a handful of key, overriding design objectives that should provide you with a framework to test your progress and the suitability of your design decisions.
Whereas the methodology will introduce a number of key thoughts and decisions at each stage of the process, these objectives transcend any individual step and highlight the intricate issues you have to handle throughout your process.
The key objectives are as follows:
The following is a quote from Frank Lloyd Wright:
"Form follows function—that has been misunderstood. Form and function should be one, joined in a spiritual union."
The first objective brings us immediately face-to-face with the age-old debate of form versus function or style over substance. As Frank Lloyd Wright proposed, all the way back in 1908, these are aspects of design that should be combined and brought together in harmony, not at the sacrifice of one or the other. There's room and a need for both.
It is a very difficult balancing act to achieve, as I've already alluded to in the discussion about art and science, but our aim should be to hit that sweet-spot where something is aesthetically inviting and functionally effective.
The designer and author Don Norman (http://www.jnd.org/dn.mss/emotion_design.html) talks about how we're more tolerant about things that are attractive and more likely to want them to perform well. Indeed, there is a school of thought that suggests how we think cannot be separated from how we feel.
Norman goes on to describe how well-executed aesthetics can naturally create favorable emotional and mental responses, but emotional affection can also come from the experience of good usability and the accomplishment of insight. Fundamentally, attractive form enhances function and the function portrays beauty through its effect.
Throughout this book, we will see examples of designs that have succeeded in creating elegance in form and in function. The following image is taken from an animated wind map developed by Fernanda Viégas and Martin Wattenberg. It is a beautiful piece of work, exceptionally well designed and executed but it also serves its purpose as a way of informing users about the wind patterns, strength, and directions occurring across the United States. This is form and function in spiritual union:
Image from "Wind Map" (http://hint.fm/wind/) created by Fernanda Viégas and Martin Wattenberg
The general advice, especially for beginners, is to initially focus on securing the functional aspects of your visualization. First, try to achieve the foundation of something that informs—that functions—before exploring the ways of enhancing its form. The simplest analogy would be build the house before decorating it, but I wouldn't want to create too much separation between the two as they are often intrinsically linked. Over time, you will be much more confident and capable of synthesizing the two demands in harmony. We shall discuss this in more depth in Chapter 4, Conceiving and Reasoning Visualization Design Options.
The following is a quote from Amanda Cox (http://vimeo.com/29391942), who works as a graphics editor at the New York Times:
"We're so busy thinking about if we can do things, we forget to consider whether we should."
In many ways, the central idea behind the methodology is encouraging you to determine that everything you do is thoroughly planned, understood, and reasoned.
This particular objective is about recognizing and responding to the scoping information that you will gather at the start of the methodology, to ensure that everything undertaken thereafter serves the purpose of our work and the needs of the audience.
Here, we should consider the idea of deliberate design, which means that the inclusion, exclusion, and execution of every single mark, characteristic, and design feature is done for a reason.
When we reach the stage of designing, concepting, and construction, you should be prepared to challenge everything; the use of a shape, the selection of a color pallet, the position of a label, or the use of an interaction.
In this next example, when displaying a section of a tree-hierarchy work by data illustrator, Stefanie Posavec, every visible property presented is used to communicate data, whether it be the use of color, the arc lengths of the petals, the position and sequence of stems; nothing is redundant and everything is deliberate.
Image from "Literary Organism" (http://itsbeenreal.co.uk/index.php?/wwwords/literary-organism/), created by Stefanie Posavec
It is also important to make sure that any visual property that is included, but does not represent data, such as shading, labels, colors, and axes among other properties, should only be included to aid the process of visual perception, not hinder it.
Furthermore, for interactive and animated visualizations, remember Amanda Cox's quote—"just because you can, doesn't mean you should." Don't succumb to the belief (like I did for many years) of thinking a visualization is a platform solely to showcase your technical competence.
Cluttering visualizations with fancy interactive features is a trap that is easy to fall into and leads to projects that look nice or are impressive technically but fail to serve their intended purpose. Instead, they interfere with the efficiency and effectiveness of the information exchange thus demonstrating a failure to synthesize form and function.
The following is a quote from Edward Tufte (http://adage.com/article/adagestat/edward-tufte-adagestat-q-a/230884/):
"Overload, clutter, and confusion are not attributes of information, they are failures of design."
When you next happen to be in a town or city center, take a look around you and observe how often people are confused by and struggle with the basic operation of correctly opening and entering doors into a store. Notice how the accessibility and function of a door—the simple act of opening and walking through it—is often impaired through a lack of intuitive design.
The method of opening a door should be straightforward, but often the aesthetics of features such as stylish door handles means we pull when we should push and we push when we should pull. This is a flaw in the intuitiveness and logic of the design, a failure in perceived affordance—it doesn't do what it looks like it should do.
This idea is an important concept to translate into visualization. As we have already outlined, we are trying to exploit the inherent spatial reasoning and pattern recognition functions of visual perception. We don't want people to have to spend unnecessary time thinking about how to use or how to read and interpret something.
When you are creating a visualization, you are integrating visual design with a subject matter's data. The former is the window into the latter, and it is the design and execution of this window that creates the accessibility.
But it is important to create a distinction between accessibility and immediacy. The speed with which you are able to read or interpret a visualization should be determined by the complexity of the subject and the purpose of the project, not by the ineffectiveness of design.
Sometimes subjects are fundamentally simple and the portrayal of the data is straightforward and intuitive. This in turn means the reader's task of interpreting the data should be relatively easy.
On other occasions, a data framework might be more complex. Your challenge will be to respect the complexity and avoid simplifying, diluting, or reducing the essence of this subject. This might mean something is not immediately easy to interpret. Some visualizations will require effort to be put in, forcing the reader to undertake a certain amount of experiential practice in order for the eye and mind to essentially become trained in reading the display.
Think of it being like muscle memory, but for the eye and the brain. We are so used to reading bar charts and line charts that they have become entrenched and programmed into our interpretative toolkit. But when we are faced with something new, something different or seemingly complex, its not always immediately clear how we are supposed to handle it.
In the following example, we see a demonstration of what is quite a complex data framework. This is an image of a legend that was used to explain how to read an innovative visualization to portray three separate indicators of a movie's success. On the left-hand side of the image is the aggregate reviews (the higher the value, the better) and on the right-hand side of the image are both the budget and gross takings (the bigger the gap, the better):
Image from "Spotlight on Profitability" (http://www.szucskrisztina.hu), created by KrisztinaSzucs
It is an unusual representation of data, not something as preprogrammed as the bar or line chart, and so it takes a short while to learn how to read and interpret the resulting shapes formed by the movie data shown across piece. This is absolutely legitimate as an effective approach to visualizing this data so long as the efforts that go into learning how to read it eventually leads the user to understand it.
Take another example, which portrays the key events in a couple of soccer matches showing completed passes (green lines), shots (blue triangles), and goals (red dots) as shown in the following image:
Image from "Umbro World Cup Poster" (http://www.mikemake.com/Umbro-s-World-Cup-Poster), created by Michael Deal
Once the reader has mastered the understanding of what each shape and its position means, these displays provide a powerful and rewarding insight in to the key incidents and the general ebb and flow of each game.
In simple terms, so long as you can avoid all the negative characteristics that Edward Tufte mentions at the top of this section, you should succeed in giving people an accessible route in to the data. Make sure that the efforts needed from the reader or user to understand how to use and interpret a visualization are ultimately rewarded with a worthy amount of insight gained.
Visualization ethics relates to the potential deception that can be created, intentionally or otherwise, from an ineffective and inappropriate representation of data. Sometimes it can be through a simple lack of understanding of visual perception.
In the following diagram, we see a 2D pie chart and a 3D version. When the eye interprets a graphic like this, what it is actually doing is perceiving the proportion of visible pixels:
Image from "The Curious Incident of Kevins in Zurich…and other stories" (http://www.researchobservatories.org.uk/EasysiteWeb/getresource.axd?AssetID=38334) by Alan Smith.
On the left-hand side of the diagram, we see a blue segment representing 82 percent and an orange segment representing 18 percent. These are the actual values. However, when we introduce a third dimension on the right—incidentally, a dimension which is purely decorative and has no relationship with data values—our eyes are deceived because we are not capable of easily adjusting our interpretation of the values across this isometric projection. With the introduction of the extra dimension and the visible height of the pie itself, we now perceive 91 percent of the visible area as blue and only 9 percent orange. This is clearly a hugely distorted reading of the values.
Another similar example comes from a Wikipedia fundraising campaign from a few years ago and a progress bar depicting the status of their efforts; as shown in the following screenshot:
Image published under the terms of "Creative Commons Attribution-Share Alike", source: https://donate.wikimedia.org/
As with the pie chart, for a bar chart we perceive the visible pixels as being representative of the values. The label indicates a total of $0.8M USD had been raised (10.7 percent towards target) but if you calculate the actual length of the bar displayed, this occupies 24.6 percent of the overall bar length. Once again, a significant distortion of the truth.
This next example is a demonstration of where aesthetics and style completely hijack a visualization. Here, we have a still showing a 3D bar chart that swooshes impressively onto the screens of those watching soccer on TV in the UK:
But what have we here? There is a yellow Drawn bar representing the value 1 and this appears to be more than half the length of a red Aston Villa bar representing 4. How can that be?
The designers of this visual have chosen to include the category labels within the bar's length, thus completely distorting the values being represented. Now, this is possibly one of the least interesting statistics you'll come across, and I'm assured the world will not stop turning as a result of this graphical misdemeanor, but it should demonstrate the pitfalls of decoration and overly stylized design.
Obeying visualization ethics is clearly an objective for any project, but really it is just about basic, good practice, respect for your readers, and attention to detail.