Visualization Genres: Presentation
In the last entries, I introduced three genres of visualizations.
Exploration: I want to discover new insights about my data.
Presentation: I know the answer and I want to share it with others.
Monitoring: I know the questions I want to ask, and check them from time to time.
We’ve talked about Exploration. Data presentation – sometimes, “data storytelling” – is the next genre to discuss. In a presentation, the visualization designer already knows the answer, and is trying to present it to an audience. Visualizations for presentation are perhaps the ones that we most often are thinking of when we think about the field – we find them in newspaper articles, in corporate powerpoint decks, and in memes.
Because the designer already knows the outcome, they have more latitude than in other genres. They typically choose a fixed set of data. They can set axes to perfectly fit their data, choose colors that are descriptive, and can choose a visual representation that might not scale to other data. They can also add parts to the image that would not work well in another context: whether that’s memorable flags or decorations, or a surprising data mapping.
Data presentations leave a lot of room for creativity, and so designers are most often deeply involved in data presentations. They often can be carried out in drawing tools like Illustrator as well as technical tools like Tableau. Coding tools like D3 can let the designer create an interactive visualization or explore a new representation.
"HBO Recycling Program, Hanpuku version" (Detail, adapted from Craig Robinson's original.) This visualization shows the complex connections between stars who appear in multiple HBO shows. We applied a circular layout to show how Illustrator and D3 complement each other.
Data presentations might be animated – as in Hans Rosling’s famous “200 countries, 200 years” talk, where Rosling gesticulates as the data animates through time. They might be interactive, allowing the user to control information progressively, or even to filter and slice the data, as many New York Times ones do. (I rather like this example on the Bond Yield Curve). Even here, the questions are largely predetermined, and the goal of the presentation is to communicate the results to another.
Next up: let’s talk about dashboards.
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Edward Segal & Jeff Heer wrote an excellent paper on Narrative Visualizations, which tries to pick apart
A quick visit to reddit’s r/dataisbeautiful gives a great selection of data presentations, as does Tableau’s “Iron Viz” contest.