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Another example is data compression when original data is transformed into a space of lower dimension.
The classic example is data collected about an infection by a physician seeing a patient, who then reports a specific case to his local public health agency - depending on the (sometimes legally outlined) reporting requirements of the infectious diseases at hand.
A critical example is data on the deep sea.
A second example is data coming from different healthcare providers that unaware of each other both have created EHRs for a patient.
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Typical examples are data collected with the Global Positioning System (GPS) or respondents describing chosen itineraries to interviewers.
Examples are data for eels from the Loire [7], from Scottish water bodies [23] and also for the American eel Anguilla rostrata from the Hudson River [46].
Examples are data on couple mental stress, or biological measures to differentiate between ovulatory and anovulatory cycles.
Typical examples are Data-Oriented Networking Architecture (DONA) [8], Publish-Subscribe Internet Routing Paradigm (PSIRP) [9], Network of Information (NetInf) [10], and content-centric networking (CCN) [11].
One example of this is data on cultural production.
One example is the data sold by the exchanges.
AT&T, for example, is mining data from Twitter (Using Twitter to Track Dropped Calls).
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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