With the emergence of the notion of “open innovation”, public organisations are currently undergoing a transformation process. Particularly driven by the idea of open government, the release of data that has been produced and financed by public funds has increased and with it, the risk associated to the publication of sensitive or personal information about citizens. Although the diffusion of open government data (OGD) might be beneficial for the private sector, the disclosure of such data might engender several risks, which could affect an individual’s privacy. In order to avoid this issue, governments worldwide have started to protect the privacy of individuals by applying de-identification rules. However, de-identification is not risk-free. If the de-identified data does not provide sufficient robustness, re-identification (or re-construction) of personal information is possible. In this paper, we describe a practical approach to examine OGD de-identification rules.