Data Visualization: Wind

At first I was a bit confused about what Data Visualization was (ie. I had to email Prof. Modey and ask). After a quick search on Google Images though, I think it was just that I didn’t know that this type of representation was called ‘Data Visualization’. I’ve definitely seen these images before; really, I see them all of the time. It’s cool to put a name to this type of image.

Anyway… in my short research time I stumbled upon this image-

Image Courtesy of


First, I was struck by how beautiful the image was. There is something classic about a black and white image, and I was immediately drawn to the subtle elegance of the sweeping lines across it (even before I realized what the lines were supposed to be representative of). I really found it to be an ascetically appealing image. Looking closer, I was able to deduce that the lines were wind patterns. They look a lot like the images of wind seen on the news, and because of that association I think I was able to make the right guess. And looking outside my window into the blustery snowpocalypse of Ann Arbor, the weather was certainly on my mind. That, and the beauty of the image itself, were what first caught my attention.

Technically speaking, this Data Visualization has a lot of interesting strengths. In terms of Tufte’s graphical integrity, this Data Visualization seems to do a decent job. Dimensionally, the number of dimensions do not exceed the number of data types being represented–two dimensions; two datas [wind speed and direction] (Tufte 77). Similarly, the labels for this image seem good (Tufte 77). Although sparse, I feel like they are sufficient considering the visual aid of the wind representations. It looks like the Data Visualization might have also initially been interactive (allowing you to focus in on specific locations and get wind speed and direction). However, this was no longer an option with the copy of the image I found on Google. This interactive aspect could explain the lack of labels on the image I found (more labels would appear as you scrolled). The labels might also be lacking because the image does have an independent movement that make sense for its claims (Miller). The wind on the page is frozen in a movement aligned with the real world.

And in light of our most recent readings, it is important that I personally found that data here interesting. It is relevant to my current environment, and in bridging the gap between Topic-Question-Significance (Ch.4 Booth).

These strengths stated, there are a few significant flaws with this Data Visualization. Again, looking at Tufte, there is an emphasis here on design variation, not data variation (Tufte 77). Although the two are closely connected in Data Visualization, the data variation can be a bit ambiguous, and resultantly a bit subjective (which I find a real problem in terms of evaluating data). There could be a bit of reader bias here, which is something that Miller would tell us to avoid. Similarly, this bias could lead to distortions and misrepresentations, again things Miller warns us against when creating visualizations from data.

It seems that this Data Visualization captures the imaginative beauty that a good image should, but falls a bit short in terms of tangible/usable data. It creates a thought provoking image, however, this image is somewhat unclear and could lead to severe reader bias and misinterpretation. It did catch my eye though, and in the onslaught that is Google Images, I think that is still worth noting.


3 thoughts on “Data Visualization: Wind

  1. I would have to agree this is definitely a beautiful example of data visualization, and it caught my eye as well. I feel that the interactiveness of this figure really prevents it from being so limited, but I can definitely see how interpretations can be hindered.

    • I think you bring up and interesting concern here that neither Miller, Tufte, nor Booth touched upon (as far as I can remember), and that is the effectiveness of interactive data. This Internet revolution that we’re living in allows us to do things digitally that, in the past, weren’t possible. Now I’m curious as to what any of those authors would have to say about interactive graphs or data visualizations– what they warrant us to do, but also what their drawbacks might be.

  2. I appreciate Brie’s comment about interactivity. I think that might be the key to addressing Jeff’s concern about data variation. Nevertheless, even with the still image, one can see wind patterns across the country and get a sense, impossible to observe independently, of how wind has different directions and speeds in different areas of the country. Really cool visualization!

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