There's a difference between showing why something is "never neutral" vs merely "not always neutral".
One example would be sufficient to establish that it is "not always neutral", but I think no example can establish that data visualisation is never neutral.
It's not even sufficient to show that maps are never neutral.
As far as neutrality is concerned, I'd like to see someone argue that a graph of sin(x) with x between 0 and 2pi and y between say -1.5 and +1.5 is not neutral, provided it is presented as a graphical approximation of the function and domain.
For other numerical graphs, such as stock prices, or population development, there's always the possibility that it isn't represented in sufficient detail, but that would depend on the user's knowledge and expectation, I think. How to lie with statistics is a good starting point for that. The article suggests the same idea, but makes it a social issue.
By limiting the graph to [0, 2pi] and presenting it as a graphical approximation of the function and domain, you've obscured the fact that the function is periodic. Visualizing the interval [-3pi, 3pi] would make it more obvious that the function is periodic.
Data visualisation can never be neutral for the same reason photography can never be neutral - you cannot do it without making endless decisions about framing even if you try and capture your subject ‘neutrally’. What you include, what you don’t, whether your axies focus on the charge range or full numeric ranges and so on. See Susan Sontag’s On Phototography for a deeply considered read on this.
> We too often assume that visualization is transparent, a method that lets us see through to the significance of the data underneath. But the reality is that the choices made when visualizing data are nearly as significant as the data itself.
This idea seems inconsistent with the idea that no map can be objective. The examples given have to do with an unfamiliar audience (the Spanish) misinterpreting the map. There is an explicit acknowledgement that a correct interpretation does exist! There is objective info in there if you know how to read it.
I think there is a hidden assumption that objective means "every single person who sees this will understand it." This is of course impossible but it's important to emphasize that the majority of people, in almost all cases, will mess something up. So I dislike the framing of data visualization is not neutral, the analyst is imposing their view on the world and exercising lots of power, etc and prefer "it's just stupidly hard and you gotta pick a few people you are actually talking too."
For a scientist this is a somewhat obvious point. The purpose of figures in the paper is to make certain specific points. You don't make a figure just to have it (if it is a good paper). In the same time, adjusting the plots to make specific points doesn't mean making them misleading (which by done by some, by playing with axis ranges, or coloring of points or smoothing).
I ran into this building a site that shows where the money in a litre of petrol goes in Pakistan. Every number comes straight from the regulator's published price notices, so I assumed the chart would be neutral. It wasn't, because the choices were all in the grouping.
I could have split the import price into "crude" and "premium", but the documents print cost and freight as one line. Any split would have been my estimate presented as fact, so it stays one line. A row the document doesn't carry shows as empty, not 0.00, because a zero tells the reader something the source never said. I also renamed a bucket from "The state" to "Government". The figures didn't change, but people read "the state" as something abstract and "government" as someone who takes a cut.
Same data and same sources, but each of those calls changes what a reader walks away believing.
12 comments:
There's a difference between showing why something is "never neutral" vs merely "not always neutral".
One example would be sufficient to establish that it is "not always neutral", but I think no example can establish that data visualisation is never neutral.
It's not even sufficient to show that maps are never neutral.
As far as neutrality is concerned, I'd like to see someone argue that a graph of sin(x) with x between 0 and 2pi and y between say -1.5 and +1.5 is not neutral, provided it is presented as a graphical approximation of the function and domain.
For other numerical graphs, such as stock prices, or population development, there's always the possibility that it isn't represented in sufficient detail, but that would depend on the user's knowledge and expectation, I think. How to lie with statistics is a good starting point for that. The article suggests the same idea, but makes it a social issue.
By limiting the graph to [0, 2pi] and presenting it as a graphical approximation of the function and domain, you've obscured the fact that the function is periodic. Visualizing the interval [-3pi, 3pi] would make it more obvious that the function is periodic.
Depending on the color choices, it may be more difficult for colorblind folks. Choosing to print or display it is a choice that affects the blind.
Data visualisation can never be neutral for the same reason photography can never be neutral - you cannot do it without making endless decisions about framing even if you try and capture your subject ‘neutrally’. What you include, what you don’t, whether your axies focus on the charge range or full numeric ranges and so on. See Susan Sontag’s On Phototography for a deeply considered read on this.
> We too often assume that visualization is transparent, a method that lets us see through to the significance of the data underneath. But the reality is that the choices made when visualizing data are nearly as significant as the data itself.
This idea seems inconsistent with the idea that no map can be objective. The examples given have to do with an unfamiliar audience (the Spanish) misinterpreting the map. There is an explicit acknowledgement that a correct interpretation does exist! There is objective info in there if you know how to read it.
I think there is a hidden assumption that objective means "every single person who sees this will understand it." This is of course impossible but it's important to emphasize that the majority of people, in almost all cases, will mess something up. So I dislike the framing of data visualization is not neutral, the analyst is imposing their view on the world and exercising lots of power, etc and prefer "it's just stupidly hard and you gotta pick a few people you are actually talking too."
For a scientist this is a somewhat obvious point. The purpose of figures in the paper is to make certain specific points. You don't make a figure just to have it (if it is a good paper). In the same time, adjusting the plots to make specific points doesn't mean making them misleading (which by done by some, by playing with axis ranges, or coloring of points or smoothing).
I ran into this building a site that shows where the money in a litre of petrol goes in Pakistan. Every number comes straight from the regulator's published price notices, so I assumed the chart would be neutral. It wasn't, because the choices were all in the grouping.
I could have split the import price into "crude" and "premium", but the documents print cost and freight as one line. Any split would have been my estimate presented as fact, so it stays one line. A row the document doesn't carry shows as empty, not 0.00, because a zero tells the reader something the source never said. I also renamed a bucket from "The state" to "Government". The figures didn't change, but people read "the state" as something abstract and "government" as someone who takes a cut.
Same data and same sources, but each of those calls changes what a reader walks away believing.
If you had access to all the underlying data could you then achieve a neutral visualization?
I don’t get why this was downvoted: it conveys a personal experience on the subject, and I for one enjoyed reading it; perhaps I’m missing something?
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