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With it, data becomes accessible by its content and context instead of its name and location only.
Economic and long-term follow-up will be reported as data become accessible.
When the data become accessible to others, it becomes clear that scientific authorship is provisional rather than authoritative.
Both focus group discussions and in-depth individual interviews were suspended once data became saturated.
We have to recognise that in the era of digital robots that can cross-match large amounts of data, absolutely reliable protection of individual digital biometric data in general, and imaging data in particular, is almost impossible once the data have become accessible.
The intrinsic hierarchical cluster structure of the data becomes visually accessible at once in the computed cluster tree.
Privacy could still be an issue, however, as more user data becomes easily accessible.
As data becomes more accessible through open university repositories and other freely-available resources, the drivers for learning and communicating on a global level become more powerful.
The broad point here is that useful government data becomes more accessible to the mainstream web user.
>> You're saying that the value of this data is, becomes greater once the data becomes public.
Further validation of these data will only be possible when primary and further secondary data sources become accessible in the course of the ongoing evaluation.
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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