Often microdata sets contain attributes which are neither numerical nor ordinal, but take nominal values from a taxonomy, ontology or classification (e.g. diagnosis in a medical data set about patients, economic activity in an economic data set, etc.). Such data sets must be anonymized if transferred outside the data collector's premises (e.g. hospital or national statistical office), say, for research purposes. The literature on microdata anonymization methods is relatively limited for nominal data. Multiple imputations are a usual choice for such data, but it has computational problems when nominal attributes can take many possible different values.