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Removing identifiable information from research data is important to maintain the privacy of research participants. Unfortunately, this is often not enough to prevent deanonymization when the dataset is combined with other data. This recommendation shows some countermeasures against deanonymization and how to apply them.
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2017
Academic writers have the ethical responsibility to protect their sources of data, to inform participants of how personal information will be secured, and to inform participants when anonymity cannot be safeguarded. The informed consent document, reviewed prior to data collection, conveys the appropriate information to potential participants.
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Academic writers have the ethical responsibility to protect their sources of data, to inform participants of how personal information will be secured, and to inform participants when anonymity cannot be safeguarded. The informed consent document, reviewed prior to data collection, conveys the appropriate information to potential participants.
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The BY-COVID project works towards enabling and improving the accessibility of COVID-19 and other infectious disease data to researchers, policy-makers, and the public. The BY-COVID Fest took place on 23-25 January 2024 in Athens, Greece, as the final event in a series of training events on Research Data Management (RDM) and the General Data Protection
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Movement data anonymity through generalization
2010Wireless networks and mobile devices, such as mobile phones and GPS receivers, sense and track the movements of people and vehicles, producing society-wide mobility databases. This is a challenging scenario for data analysis and mining. On the one hand, exciting opportunities arise out of discovering new knowledge about human mobile behavior, and thus ...
Monreale A +6 more
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Implications of Data Anonymization on the Statistical Evidence of Disparity
Management Science, 2022Heng Xu, Nan Zhang
exaly
Anonymous sequences from trajectory data
2009The increasing availability of personal data of a sequential nature, such as time-stamped transaction or location data, enables increasingly sophisticated sequential pattern mining techniques. However, privacy is at risk if it is possible to reconstruct the identity of individuals from sequential data.
R. G. Pensa +3 more
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Classification utility aware data stream anonymization
Applied Soft Computing Journal, 2021Uğur Sopaoğlu, Osman Abul
exaly
Methods and tools for healthcare data anonymization: a literature review
International Journal of General Systems, 2023Olga Vovk, Gunnar Piho, Peeter Ross
exaly