The National Science Foundation recently awarded Jerry Reiter, Department of Statistical Science, John de Figueiredo, Duke Law School, and Ashwin Machanavajjhala, Department of Computer Science, nearly $1.5 million for their research project, “An Integrated System for Public/Private Access to Large-scale, Confidential Social Science Data”. The goal: to change the way researchers access and use data.
When dealing with highly sensitive data, such as information on health, income or even history of (or lack thereof) infidelity, researchers must be extremely cautious as to how much data to release with their findings. The ability to replicate findings is one of the hallmarks of a sound study, yet it is hardly ethical to release the names of individuals who have been involved with affairs. The problem: how much information is too much information?
Reiter and his fellow researchers believe they have the solution: a three-part system of data delivery, which not only protects the identities of participants, but also offers accessible and reliable mock data.
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