Official organisations that maintain databases containing personal information need to devise better ways to protect individuals' privacy while preserving the value of the information to researchers, academics argue.

A report by Carnegie Mellon University statistics professor George Duncan in the journal Science claimed that traditional methods of 'de-identifying' records, such as stripping away Social Security numbers or birthdates, are inadequate to safeguard privacy.

Professor Duncan warned that a person who knows enough about the data pool could use other characteristics to identify individuals.

The academic pointed out that he is the only person who holds a Ph.D. in statistics and teaches in Carnegie Mellon's H. John Heinz III School of Public Policy and Management, so any data set that included that information, even with Duncan's name removed, could be used to determine his identity.

This could have serious consequences when it comes to data that includes information about a person's medical history or sexual behaviour, such as that collected by the National Center for Health Statistics.

Unfortunately, the characteristics that can be used to 're-identify' records are often the very information that makes the data useful to legitimate researchers.

"The question is how data can be made useful for research purposes without compromising the confidentiality of those who provided the data," said Professor Duncan.

Possible solutions to this dilemma include administrative procedures that limit data access to approved users who must abide by restrictions on the use of information, and statistical methods that 'de-identify' records in such a way that the user cannot readily reconstruct personal identities.

In order to be effective, these statistical transformations must be tailored to how the data will be used so that researchers can see the information that interests them while other characteristics remain veiled.

"Achieving 'adequate' privacy will require engineering innovation, managerial commitment, information cooperation of data subjects and social controls (legislation, regulation, codes of conduct by professional associations and response to reactions of the public)," Professor Duncan concluded.