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At the local level in San Francisco, former mayor and current California Lt. Governor Gavin Newsom ordered departments to release all non-confidential data to the public.
This paper develops a spatial econometric model of fishing location choice using non-confidential data from the Great Barrier Reef coral trout commercial fishery.
In face of this scenario, many systems aim to provide information confidentiality by protecting only the secret data itself, without any care of the correlated non-confidential data.
The project encourages developers, researchers, universities and businesses to upload large (non-confidential) data sets to Amazon – things like census data, genomes, etc. – and then let others integrated that data into their own AWS applications.
Publicly available datasets from any of these surveys contain only non-confidential data.
The general discussion after the presentations focused mainly on non-confidential data that can be made publicly available without coping with privacy issues.
The mortality data used provided non-confidential information on decedents including state of death, county of death, age, sex, date of death and primary cause of death.
Typically, the researcher must guarantee that collected data are stored without non-researchers having access to confidential data.
Personal confidential data.
Google has since removed the confidential data.
In both ways, we can reliably identify confidential data, ranging from FDE keys to vast amounts of confidential user data.
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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