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The article addresses the “Guidelines for the Protection of Privacy and Transborder Flows of Personal Data” by the OECD, proposing a model that incorporates its recommendations to assess and enhance compliance with data protection regulations. Using the Object-Role Modeling (ORM) methodology, the study aims to develop a detailed representation of the relationships and constraints between entities such as Data Controller and Personal Data, emphasizing the importance of transparency, accountability, and interoperability. It concludes by suggesting the transformation of the ORM model into first-order logic to enhance formal analysis and automate reasoning, highlighting the benefits in terms of clarity, accuracy, and identification of inconsistencies, with the aim of strengthening the privacy and security of personal data

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The OECD-Inspired ORM Blueprint for Personal Data Security

  • 会议论文

  • 发表日期：

    2026年

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  • Antonio Goncalves,
  • Anacleto Correia

摘要

The article addresses the “Guidelines for the Protection of Privacy and Transborder Flows of Personal Data” by the OECD, proposing a model that incorporates its recommendations to assess and enhance compliance with data protection regulations. Using the Object-Role Modeling (ORM) methodology, the study aims to develop a detailed representation of the relationships and constraints between entities such as Data Controller and Personal Data, emphasizing the importance of transparency, accountability, and interoperability. It concludes by suggesting the transformation of the ORM model into first-order logic to enhance formal analysis and automate reasoning, highlighting the benefits in terms of clarity, accuracy, and identification of inconsistencies, with the aim of strengthening the privacy and security of personal data