The Unlinkable Data Challenge was a NIST-sponsored event designed to engage diverse data professionals in addressing the problem of "quasi-identifiers;" items of personal data which are not individually identifying, but can be combined with other data to compromise anonnymity in a variety of contexts.

Our solution involved development of a multidimensional aggregation algorithm that is a robust solution to data privacy needs which is both flexible and intuitive, with a basic concept that is comprehensible even to a lay audience. Underlying this emphasis on intelligibility is the conviction that individuals are not only entitled to privacy, but also to an understanding of their privacy.