Taxonomy of Personal Data for Public Organizations in Mexico

In Mexico, government organizations process different subsets of personal data, according to their scope or main activity. Although the types of personal data are usually the same, each institution treats them with different names, sizes, or formats. The main contribution of this work is to propose a taxonomy of personal data that is a guide for their identification and classification and for the design of standardized elements that represent them. The proposed taxonomy is dynamic, flexible, and facilitates security from the design of the data in the applications, systems, and computer models of Mexican public organizations, and allows the secure exchange of information. This taxonomy focuses on compliance with transparency and access to public information of the government organizations. The personal data sensitivity and confidentiality criteria were analyzed and defined with a computational implementation perspective not seen in the state of the art.