Purpose of Design
~5 minute read
The primary goals of design are:
- Enable a user to accomplish a desired task easily.
- Make the task feel natural.
- Produce beautiful objects
This wiki contains pages that break down overall design of data visualization into components and concepts. Page by page, we will examine these components and concepts in turn. However, in this first page, I try to give a more holistic picture: what do we mean by ‘good design?’ What are we trying to accomplish through design? What is our overall goal when designing something?
Good design facilitates a task
While many overall goals of design could be identified, I think we will stick with the idea that a well-designed object:
- Allows its user to accomplish a task as easily as possible
- Allows its user to interact with it in a way that feels as natural as possible
- Is aesthetically pleasing.
In other words, the primary reason we are creating an object is enable someone to do something. Thus, we should strive to ensure this task is easy and the user enjoys performing it as much as possible. Let us look at each of the above points in turn.
1. Making tasks as easy as possible
Bad design can render objects hard to use or confusing. From forks to signs, even simple objects are not immune to bad design.
The fork on the left (designed by Katerina Kamprani) does not allow the user to interact with it as they wish. The design on the right is confusing. Both fail to accomplish the basic goals of design.
In the above examples, the quality of the designs is judged against the task they are trying to enable: the fork is supposed to allow someone to stab food with the tines, while the sign is supposed to convey information with clarity. Thus, when you designing an object, keeps its purpose in mind; always remember what you are trying to enable the user to do.
Let’s assume that you are making a data visualization for a publication or presentation. Presumably you are doing so because you have found something in your data that you wish to communicate. Therefore, good design in a data visualizations seeks to enable the reader to gain this same understanding in as simple a manner as possible.
Above, we saw that even simple objects can be ruined by bad design. The same is true in the world of data visualizations: one can make something as simple as a line chart nearly unusable. Below is a figure that I created some time ago. The intent behind the figure was to allow comparison between the infra spectrum of an inorganic compound in different solvents. However, this plot attempts to show too much data at once and does not make good use of contrast, rendering the desired task more difficult than it should be (for example, try comparing bands in ethanol and acetonitrile). The deign could be improved, for instance using the technique of small multiples, each with high contrast. This change makes it simpler to accomplish the desired task, and so makes the design better overall.
Above: An image from one of my publications. An improved design would simply stack 5 similar plots and not have so many different colors, as show below.
2. Making tasks seem natural
Good design does not exist in a vacuum. You are making data visualizations for people who are used to seeing things presented in a certain way. If you deviate from that expectation, you make the object feel less familiar, and make the reader work harder to understand it.
In the real world, we might find a green stop sign confusing, while in the world of data visualization we might find an ordered bar chart of stock market returns confusing. Both of the underlying objects are familiar, but their implementation is not.
There is nothing inherently wrong with a green stop sign. However, we find it confusing, because it does not meet our expectations. Similarly, there is no reason not to represent stock market performance using a ranked bar chart (which highlights what returns are most likely); however, since we are more used to seeing this represented as a histogram, we find this visualization confusing.
This is not to say that you shouldn’t try new things. Indeed every current ‘standard’ was once a new idea. However, when you are trying something new, you need to acknowledge that you are increasing the burden on the user, and ask yourself if the perceived gains you get from the new approach outweigh this drawback.
3. Making objects pleasing
People like beautiful things. We enjoy interacting with them and looking at them. Thus, if you make a beautifully designed object, you will create something that people will choose to interact with. That is powerful.
Some time ago, dedicated portable digital music players were extremely popular. Apple created the iPod. Archos created the Jukebox. While the Jukebox was arguably a technically better device by nearly every metric, only one of them is recognizable by most people today, and it is the one with the simpler, more natural, and better looking design.
The music player on the left eventually became synonymous with portable music devices, while the one on the right is largely forgotten. The one on the right was much more capable. The one on the left, however, was much more beautiful.
A common complaint of scientists is that it can be hard to get people to pay attention to your work. However, if you can make the iPod equivalent of a data visualization, you will have people sharing your work for you. Consider the two maps of election results shown below.
The plot on the left (taken from www.fivethirtyeight.com) contains less information than the one on the right. However, it is also more attractive, simpler to read, and follows our expectations for such maps. This is the style we always see on election night in the USA. Thus, the one on the left is more likely to be widely shared and appreciated.
**Apologies to friends outside the USA. I will update with a more global example as time permits.*
The one on the left is simple to read, reflects how many of us view the politics of the United States, and is attractive. The one on the right, while containing more information, is harder to immediately understand, represents things by colors we do not usually use in US politics, and is less attractive. Is there any wonder that maps like the one on the left are the most shared on election night?
Your goal is to create objects like the map on the left; objects that allow a reader to understand a complex topic as easily as possible, to frame the data in a context they understand, and to create an object that they enjoy looking at and wish to share with others.
As for how to accomplish all of this? Well, that is what the rest of the wiki is all about!