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Data anonymization has been defined as a "process by which personal data is altered in such a way that a data subject can no longer be identified directly or indirectly, either by the data controller alone or in collaboration with any other party."
k-anonymity is an attempt to solve the problem "Given person-specific field-structured data, produce a release of the data with scientific guarantees that the individuals who are the subjects of the data cannot be re-identified while the data remain practically useful."
Research into de-identification is driven mostly for protecting health information. [15] Some libraries have adopted methods used in the healthcare industry to preserve their readers' privacy. [15] In big data, de-identification is widely adopted by individuals and organizations. [8]
[1] [4] In particular, it can be difficult for researchers to ensure participant anonymity. [5] One study of 112 published educational technology research papers was able to identify participant identities in 10 of those papers; the majority of these studies had gathered this data under conditions of anonymity. [5]
The sharing of research outputs is covered by three standards of the TOPs guidelines: on Data transparency (2), Analytic/code methods transparency (3) and Research materials transparency (4). All the relevant data, code and research materials are to be stored on a "trusted repository" and all analysis being already reproduced independently ...
Anonymity is seen as a technique, or a way of realizing, a certain other values, such as privacy, or liberty. Over the past few years, anonymity tools used on the dark web by criminals and malicious users have drastically altered the ability of law enforcement to use conventional surveillance techniques. [2] [3]
If you’re stuck on today’s Wordle answer, we’re here to help—but beware of spoilers for Wordle 1325 ahead. Let's start with a few hints.
Researchers publish data that they get from participants. To preserve participants' privacy, the data goes through a process to de-identify it. The goal of such a process would be to remove protected health information which could be used to connect a study participant to their contribution to a research project so that the participants will not suffer from data re-identification.