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It's a computational tool that enables you to manipulate, analyse and visualise data: its capabilities range from solving equations to creating real-time 3D graphics.
Numerical dating methods in Quaternary science are faced with the need to adequately visualise data consisting of estimates that have differing standard errors.
We had initially been focusing on monitoring (a system to alert us when something was wrong), but we later started to focus on metrics (a system to gather and visualise data allowing us to better understand the systems).
Data scientists are typically attached to technology firms, and are therefore disproportionately likely to analyse and visualise data that is not in the public domain, rendering it unavailable for interested parties to attempt to reproduce results or carry out analyses of their own.
There are lots of ways to visualise data.
The original use was primarily to visualise data.
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Last.fm, whose data scientists are also pretty good at visualising data, have the answer.
David McCandless, who specialises in visualising data, decided to apply this technique to the sun-sign horoscopes that appear on Yahoo!
But my experience is that visualising data is often far more powerful than yet another set of numbers.
Maybe there's a feeling out there that more should have resulted from the explosion of interest in visualising data.
But the practice of visualising data is a little less well understood, perhaps because it's one of those disciplines that mixes art and science.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com