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soyiuz comments on “Banning exploration in my infovis class”

Whoa, I cannot disagree more with the premise and the conclusions of the author.

Exploration is absolutely one of the key goals of data visualization. Tukey’s insight was two-fold: First, that statistics puts too much emphasis on confirmation but not enough on systematic exploration of a data set. Too often researchers do not understand their data. They bring their own biases and preconceived notions, where they should be listening to the data.

Second, too often is visualization mistaken for confirmation. A curious pattern or an outlier may just be an artifact of the layout algorithm. The “find” part of visualization should happen through mathematical insight. The graphic illustrates the underlying mathematical reality but no more. One cannot strictly speaking “find” anything, only form intuitions or illustrate already proven insights.

Perhaps the author’s difficulty in evaluating his students work lies not in the exploration part of their assignments, but in his own pedagogic emphasis on “tools,” “frameworks,” and “users.” None of those things are relevant to data visualization as such. They might be goals for a business built around data visualization (to produce tools, or to identify user needs). A university should offer more than job training. Those interested in users and in “what one gets paid for” would do better in an internship or at a more narrowly technical trade school.

I don’t know how “finding” is any more of a goal for data visualization than “exploring.” Data visualizations tell stories. They often support the first and the last step in data analysis: the exploratory phase and the presentation of findings. They are inherently subjective, evocative, concise, artful.


link

soyiuz

Source:
https://news.ycombinator.com/item?id=14242982

soyiuz comments on “Banning exploration in my infovis class”

Whoa, I cannot disagree more with the premise and the conclusions of the author.

Exploration is absolutely one of the key goals of data visualization. Tukey’s insight was two-fold: First, that statistics puts too much emphasis on confirmation but not enough on systematic exploration of a data set. Too often researchers do not understand their data. They bring their own biases and preconceived notions, where they should be listening to the data.

Second, too often is visualization mistaken for confirmation. A curious pattern or an outlier may just be an artifact of the layout algorithm. The “find” part of visualization should happen through mathematical insight. The graphic illustrates the underlying mathematical reality but no more. One cannot strictly speaking “find” anything, only form intuitions or illustrate already proven insights.

Perhaps the author’s difficulty in evaluating his students work lies not in the exploration part of their assignments, but in his own pedagogic emphasis on “tools,” “frameworks,” and “users.” None of those things are relevant to data visualization as such. They might be goals for a business built around data visualization (to produce tools, or to identify user needs). A university should offer more than job training. Those interested in users and in “what one gets paid for” would do better in an internship or at a more narrowly technical trade school.

I don’t know how “finding” is any more of a goal for data visualization than “exploring.” Data visualizations tell stories. They often support the first and the last step in data analysis: the exploratory phase and the presentation of findings. They are inherently subjective, evocative, concise, artful.


link

soyiuz

Source:
https://news.ycombinator.com/item?id=14242982

soyiuz comments on “Banning exploration in my infovis class”

Whoa, I cannot disagree more with the premise and the conclusions of the author.

Exploration is absolutely one of the key goals of data visualization. Tukey’s insight was two-fold: First, that statistics puts too much emphasis on confirmation but not enough on systematic exploration of a data set. Too often researchers do not understand their data. They bring their own biases and preconceived notions, where they should be listening to the data.

Second, too often is visualization mistaken for confirmation. A curious pattern or an outlier may just be an artifact of the layout algorithm. The “find” part of visualization should happen through mathematical insight. The graphic illustrates the underlying mathematical reality but no more. One cannot strictly speaking “find” anything, only form intuitions or illustrate already proven insights.

Perhaps the author’s difficulty in evaluating his students work lies not in the exploration part of their assignments, but in his own pedagogic emphasis on “tools,” “frameworks,” and “users.” None of those things are relevant to data visualization as such. They might be goals for a business built around data visualization (to produce tools, or to identify user needs). A university should offer more than job training. Those interested in users and in “what one gets paid for” would do better in an internship or at a more narrowly technical trade school.

I don’t know how “finding” is any more of a goal for data visualization than “exploring.” Data visualizations tell stories. They often support the first and the last step in data analysis: the exploratory phase and the presentation of findings. They are inherently subjective, evocative, concise, artful.


link

soyiuz

Source:
https://news.ycombinator.com/item?id=14242982

soyiuz comments on “Banning exploration in my infovis class”

Whoa, I cannot disagree more with the premise and the conclusions of the author.

Exploration is absolutely one of the key goals of data visualization. Tukey’s insight was two-fold: First, that statistics puts too much emphasis on confirmation but not enough on systematic exploration of a data set. Too often researchers do not understand their data. They bring their own biases and preconceived notions, where they should be listening to the data.

Second, too often is visualization mistaken for confirmation. A curious pattern or an outlier may just be an artifact of the layout algorithm. The “find” part of visualization should happen through mathematical insight. The graphic illustrates the underlying mathematical reality but no more. One cannot strictly speaking “find” anything, only form intuitions or illustrate already proven insights.

Perhaps the author’s difficulty in evaluating his students work lies not in the exploration part of their assignments, but in his own pedagogic emphasis on “tools,” “frameworks,” and “users.” None of those things are relevant to data visualization as such. They might be goals for a business built around data visualization (to produce tools, or to identify user needs). A university should offer more than job training. Those interested in users and in “what one gets paid for” would do better in an internship or at a more narrowly technical trade school.

I don’t know how “finding” is any more of a goal for data visualization than “exploring.” Data visualizations tell stories. They often support the first and the last step in data analysis: the exploratory phase and the presentation of findings. They are inherently subjective, evocative, concise, artful.


link

soyiuz

Source:
https://news.ycombinator.com/item?id=14242982