Abstract
As we have repeatedly argued, DSOs fulfill their stewardship responsibilities by resolving the tension between ensuring confidentiality and providing access (Duncan et al., 1993; Kooiman et al., 1999; Marsh et al., 1991). Data stewardship, therefore, requires disseminating data products that both (1) protect confidentiality—so get disclosure risk R low by providing safe data and (2) keep data utility U high by providing data products that are analytically valid. In other words, the problem of protecting data is bi-criteria. This opens the question of how to balance the two criteria. Answering this requires that we know how R and U affect each other.
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Notes
- 1.
Another possibility is the Sample knowledge state where the data snooper is taken to know that τ is one of the values in X (i.e., is in the sample). The Sample knowledge state is appropriately assumed when the data snooper knows, for whatever reason, that the individual was surveyed in a sample survey. This would certainly be true if the data are a census or a near census. This state is called “response knowledge” by Keller and Bethlehem (1992). Or the data snooper might know that the record of the target is in the sampling frame, but not necessarily in the actual sample.
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Duncan, G.T., Elliot, M., Salazar-González, JJ. (2011). Disclosure Risk and Data Utility. In: Statistical Confidentiality. Statistics for Social and Behavioral Sciences. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7802-8_6
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