Benjamin Bach and colleagues wrote in IEEE Computer Graphics about “The Emerging Genre of Data Comics” . I like data and I like comics, so I’ll love data comics, right?
Data comics is a combination of data + story + visualization. They say that it is “a new genre, inspired by how comics function” (, p.7)
The “how comics function” is largely about flow and multiple panels. As Scott McCloud says, the action happens in the gutter (, p. 66) (i.e., between the panels).
(By the way, Sensei McCloud teaches that this happens though the active engagement of the reader, who closes the gap with his or her imagination. If you haven’t read Understanding Comics , stop reading this blog right now and go read McCloud. I’ll wait here.)
The authors assert that data always has context, and “Context creates story, which wants to be narrated” (, p. 10). Well, maybe, though I think it is a mistake to read this as “you can tell whatever story you want” (the Hollywood approach). Part of the context is what kinds of stories it is OK to tell.
The authors give four advantages of the medium,
- Combines text and pictures
- Delivers one message at a time in a guided tour
- Data visualization gives evidence for facts
- Other types of visualization can tell the story clearly
This article itself is delivered in the form of a comic (though not a data comic), which highlights both the advantages and the limitations of this approach.
One really good thing about storyboards and comix is that they force you to boil down your story to a handful of panels, with only so much on each. This isn’t always easy, but it surely helps organize the story.
Compare this to written or spoken word, which can flow any way you want and can go on as long as you have strength, with no guarantee that any organized narrative is told.
I note that any good visualization (or demo) probably had a storyboard in the beginning, which is essentially a comic strip of the overall story to be told.
The medium isn’t without drawbacks.
Fro example, this article was very difficult for my ancient eyes to read. The text was rather too small and blurry for me to read and white on black lettering is hard for me to make out. Many of the pictures were below my visual threshold. E.g., One panel is about “Early examples led the way” has tiny versions of other comics, which are illegible and may as well not be there.
Also, it was difficult to quote (i.e., remix) ideas from this article. E.g., I couldn’t easily quote the “Early examples” panel to make my point about it. I could probably have extracted the picture, fiddled with it in a drawing package, and saved a (blurry) image to include here. But how would that make my point about the illegibility of the original?
As a general rule, comix need to be pretty simple or they are impossible to read. This means that they can only deliver a very concise story. As Back, et al. suggest, this is a feature, not a bug.
On the other hand, telling “only one message at a time” is not just “concise” it is a Procrustean bed. For complicated data there isn’t one message, there are many. A data comic runs the risk of trivializing or misleading by omission. This is a bug, not a feature.
The challenge is to make “concise” be deep rather than shallow.
This is why trying to express the story in a storyboard (comic) is an extremely good design practice, even if the story isn’t ultimately published in the form of a comic.
- Benjamin Bach, Nathalie Henry Riche, Sheelagh Carpendale, and Hanspeter Pfister, The Emerging Genre of Data Comics. IEEE Computer Graphics and Applications, 38 (3):6-13, 2017. http://ieeexplore.ieee.org/document/7912272/
- Scott McCloud,, Understanding Comics, HarperCollins, 1994.