Nathan Yau recently wrote a posting about the different words used for visualization and infographics. His definitions are interesting because they reveal quite a bit about his background and main focus, and his blind spots give some insights into the community he’s working in.
Here are Nathan’s definitions with my comments. Since I have something to say about almost all of them, I decided to quote his entire list. I don’t claim that my view is better or more correct, I simply want to provide a second opinion.
data visualization — Graph-like image or interactive, usually tied with data exploration and analysis.
First definition, first major difference: a lot of people in the visualization field would consider data visualization to denote scientific visualization (i.e., volume or flow visualization of data with spatial dimensions), for whatever reason. There may be simple historical reasons for this, or the assumption that scientific visualization deals with more data.
In any case, data visualization has a particular slant, and is not the same as visualization in general, and certainly does not refer to charts or ‘interactives.’
visualization — Similar to data visualization and often is, but can also be the later described information visualization.
It’s the generic term for all of visualization, though historically it has denoted scientific visualization. Traces of that are still there, like the Vis track at VisWeek, that would be much better served by the term SciVis (as the counterpart to InfoVis). That would also eventually make it possible to use “Vis” again as a shortcut for the entire conference, not just one track.
viz — A shorter version of visualization in both length of word and thoughtfulness in design and data.
Nathan nailed that one. I have no idea where the z comes from, it makes absolutely no sense. I wish people stopped using that spelling.
vizzes — Plural of viz and evokes an image of urinals.
A horrible term, and I also agree with Nathan on that one.
information visualization — Usually encapsulates what data visualization is about, but usually makes an effort to provide “actionable insights.”
Apart from the data visualization part (see above), I would also argue with the insights. Visual analytics has played those up a lot more, while infovis is a lot more about the basic representation and interaction issues. It’s not an easy line to draw, and there are many counterexamples, but I don’t think that “actionable” is the first thing that comes to mind when most people think of information visualization.
InfoVis — An annual conference that most visualization researchers go to.
Agreed, except it’s information visualization researchers.
infovis — Research of information visualization that people talk about at InfoVis
infoviz — Often a crappier version of infovis and closer to what will follow shortly. However, it could just be an indicator of the person using the word, and the work might be good.
Vis with a z is simply wrong. I don’t think there’s much you can deduct about either the work or the person using it, but they should stop doing it nonetheless.
information graphic — Serious work from journalist-type folks who provide a narrative with data.
Agreed. Though just like with visualization, different people have different ideas about the word, and they all think their use is correct.
infographic — A toss-up between information graphic and [INFOGRAPHIC], but usually the latter and often unnecessarily big.
Short for information graphic, just like infovis is short of information visualization. I don’t think it’s helpful to draw lines between the full and contracted versions of words, that just leads to confusion.
[INFOGRAPHIC] — A gigantic graphic with lots of graphs, numbers, icons, and fancy-ish typefaces. Often used in blog post title. Always useless.
Speaking of confusion, it took me some time to figure this one out: it’s the tag that’s often used in a title to tell people to click on it to see the wonderful infographic “after the jump.” They’re often a sign to stay away, true, but sometimes they can be good.
infograph — No idea who started using this term, but it’s dumb. Stop it.
I had never seen that one before, but let’s stop it before it even starts. It’s bad.
chart — Typically looks very statistical and close to a table.
This mostly sounds like it’s static, and it does have a statistical ring to it. I imagine crisp, black lines, printed on paper, with only a handful or data points. I don’t think it’s really that clearly defined though, and I’ve seen a lot of interactive and colorful charts. And they don’t even all have to be made with lots of care, the term chart junk isn’t just an accident.
It’s also a generic term for something that depicts data, like a bar chart or a pie chart. These can be part of some fancy, animated, 3D extravaganza, and still have chart in their names.
data chart — Even closer to a table of numbers. And kind of redundant.
Quite redundant, yes.
graph — It’s like a chart, but it sounds more visual, because it’s the root of “graphic.”
In the visualization community, graph is typically used in the mathematical sense, where it refers to a network. There is a whole subfield of graph visualization and a mostly unrelated field of graph drawing, both of which exclusively deal with network graphs. In fact, seeing the term graph refer to some kind of chart or visualization is rather rare (and confusing) in the visualization community.
data graphic — It’s an ambiguous term I like to use that doesn’t upset people who like to argue what visualization is and what it’s for, but clear enough that most people know what it is. Also implies that data comes first and is the driving force behind the graphic.
It’s not a bad term, especially because it conveys the importance of the data. To me, it sounds more infographic-y than a pure visualization, i.e., I’d expect it to have some kind of story and be designed by a designer rather than straight out of a program.
It’s interesting to see Nathan completely ignore scientific visualization, though it’s also not surprising: he is not a product of the academic visualization community. His focus is on statistical graphics and more information graphics-style things than visualization in general.
He also doesn’t seem to be aware of visual analytics and its focus on insight, sense-making, and decision support. This distinction is of course still up for debate, but I think it would help to clarify at least that one particular line, since all others are so fuzzy and ill-defined.
Nathan’s list is a good reminder that people outside the academic community have very different ideas about visualization, even – or perhaps especially – if they’re working in closely related fields.