made available for error-correction processes. Second, data can be selectively made available only when they are needed to resolve ambiguities in any putative record-level match—an approach that minimizes privacy concerns because it obtains additional data on individuals only when they are needed.9

When using third-party data to enhance matching accuracy, additional logging and accountability requirements must be introduced. Each third-party record requested and received must be retained and retained in its original form until it is no longer needed (for example, until the point that the voter has confirmed any changes that may have resulted from the use of such data). Furthermore, any third-party record used to improve a match should be logged and accounted for similarly. In addition, government matching with third-party datasets raises privacy concerns (such as concerns if credit header data are merged with voter history data, for example).

COLLATERAL ISSUES IN IMPROVING DATA QUALITY

Application of the techniques discussed above is intended to improve the quality of the data in a VRD by making the data more accurate—that is, these techniques allow erroneous data to be changed into correct data. But their success in doing so is not guaranteed—use of the techniques may introduce additional error, or the original data may in fact have been correct. Thus, it may well be advisable to keep the old data as well as the new, but with a flag that indicates that the old data have been corrected. In addition, a policy must be established regarding notification of the voter if a field is changed. The cost of such notification must be weighed against the value of ensuring with high confidence that the updated data are correct.

9

This technique is explained in detail in Paul Rosenzweig and Jeff Jonas, “Correcting False Positives: Redress and the Watch List Conundrum,” Legal Memorandum 17, The Heritage Foundation, June 17, 2005, available at http://www.heritage.org/Research/HomelandSecurity/lm17.cfm.



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