As a starting point, you need to decide what you want to achieve with your visualization. We already introduced you to the main rules of thumb: clarify, explore, mind the dialogue with your audience. But each of these is also a goal per se : do you want your visualization to enable personal discovery of complex data or should it instead tell a story or rather support and enhance an editorial perspective? Using D3 does not oblige you to create interactive visualizations, thus, you also need to decide whether to go for a static or an interactive one. All those are critical decisions to make and will reflect the clarity of concept you want to get to your audience.
While thinking and narrowing down the above answers and specifications, you should always mind the audience. As Alberto Cairo explained in his book “The Functional Art,” you as a creator (journalist or otherwise) must respect your reader/viewer. A visualization transforms complicated matters into understandable subjects. Hence, my “clarify, but don't dumb down” from Chapter 1 : your audience is composed of diverse individuals but the common feature among them is that they are smart and curious. Thus, clarity differs from reductionism and simplicity. Your visualization should not have the immediacy of interpretation as its primary goal. If your visuals are appealing enough, the audience will engage with—and put the effort it needs to comprehend the complexity you have attempted to clarify.
Look at the big picture: is your visualization a stand-alone piece of work or is it a part of a larger production? If it the latter, you need to think the visualization within the whole production, not as a mere colourful after-thought or a technical show-off. Such an integration requires rigour throughout the entire process for the visual to be aligned to the context and the questions it is answering.
The Connected China website ( http://china.fathom.info/ ) helps illustrate the point we are trying to make (Figure 2-1 ). Connected China was built over a year and a half by a team of journalists and researchers at Hong Kong, and Ben Fry's Fathom Design and presents a visual exploration of China's social and
institutional power. The visualization is an extraordinary tool kit for anyone wishing to understand the social and institutional power of China’s elite: you can explore essential background on the country, compare careers for current and past leaders, read featured stories, and so on. Here, context is king and the driver behind such a unique effort to organise and transform with visuals Reuters' knowledge base of power in China. The production is radically different from news as we know it: the audience does not get either a story or a news item or a table, rather the entire visualization centers on narrating the structure of power in China.
CHAPTER 2 ■ STRUCTURING AND DESIGNING DATA VISUALIZATIONS
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Such a project is a huge one, indeed, but that is not its most important feature. Not much of the success of this visual exploration is technical. What’s impressive is the team’s commitment to maintain and update the database behind “Connected China.” Reg Chua, Thomson Reuters' editor of data and innovation, wrote on his blog: 3
[...] we updated the database (and hence the site) when the news was announced. That’s
not remarkable—right?
That may seem like a strange question. After all, shouldn’t data-driven apps offer the
most up-to-date information to users? Certainly many do, especially those that take in
regular feeds of government and publicly released data. But many data-driven projects—
and especially heavily editorially curated projects such as Connected China—often don’t;
they’re generally built to stand as a snapshot of a moment in time, not to be a constantly
updated resource. [...] Most big projects analyzing reams of data and providing stories and
analysis aren’t designed to be updated. But shouldn’t they be?
Of course, not every newsroom can allow to build and maintain such a gigantic project. The bottom line here is, though: you are not in a vacuum, so strategically planning for the structure and the life of your visualization is crucial. A critique you could address to “Connected China” for example is on usability: how do I know when it was last updated since every time I visit the home page, it displays the same? If the plan was to have the underlying database updated as long as the visualization lives, then users should be given a way to know that this has happened and when.
If by now you think that this whole process is taking time, then wait for the data collection and preparation bit; we will spend more time on that in Chapter 3 . For now, note that a compelling data visualization generally has a compelling data research and analysis behind. Whether it is on Doctor Who villains or casualties of drone strikes in Yemen, working with data and transforming it into visuals is time-consuming.
Figure 2-1. A screenshot of the home page of “Connected China.”
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Another reminder is to use visual restraint: you cannot show everything. If you want to use colours, do so, but ensure colour-blind could still see what you want to show. Furthermore, the diversity of forms needs to be carefully constructed to answer the primary question or enhance the main axes of a story. Your data visualization needs to amplify the impact of the content you are providing to the audience, not overwhelm it.
Finally, here comes a relatively overlooked element: the annotation. Going freehand with D3 is just that easy—but ensuring your audience follows you is a challenge. Thus, think of providing context and annotation for the key messages to be correctly interpreted. The New York Times is an outstanding example here, both regarding technical realisations and clarity of messages.