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Engineers thought they could take data for granted.
But to think of data as simply a grant requirement is taking data for granted -- it can do so much more.
It is common to take the reliability of these data for granted and to draw from them resolute inferences about the properties or the behavior of the investigated organisms.
It takes away the "taken for granted".
This gives them impressive savings in efficiency, it will enable them to get a real-time view of their management data (something taken for granted in the first world, but until now, elusive in remote areas), and very importantly, because of the subscription model, it gives them the ability to grow without substantial capital investment.
Take nothing––and nobody––for granted.
Today every tweet is archived, every Facebook selfie stashed and cached, every arts/tech/culture blog mirrored, and the idea of the permanence of data is taken for granted.
No one ever takes it for granted".
He never takes anything for granted.
Endeavoring to get more useful data so as to better measure and use ideas like chemistry and leadership seems far-fetched now, but a generation ago pitch-tracking, fielding data and other information we take for granted today would have been hard to imagine.
Conceding that much more can be accomplished on computers than was ever the case in shoe-leather days of yore (we now take online data journalism for granted, for instance), it remains the case that journalism is undergoing severe retrenchment.
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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