Site icon m. e. driscoll

the case for open source data visualization

When I was in graduate school, the most closely studied part of the scientific publications we read was not the results, but the methods sections. (It was also, incidentally, often the hardest section to write for one’s own publications.) Methods sections are wonderful because they allow you to verify that someone else’s work is correct — by reproducing it yourself. But more importantly, methods sections allow you to build upon the work of others. They are the open source code of science.

Unfortunately, for all but a small fraction of data visualizations on the web, there are no methods sections being published. This is a shame, because it slows the free flow of ideas and prevents the creative extension of other people’s work.

Three conditions must be met for a data visualization to be considered open and reproducible:

I grade some of the web’s existing data visualization sites using these criteria.

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