IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/kms9n.html
   My bibliography  Save this paper

How to Manage My Data? With Machine--Interpretable GDPR Rights!

Author

Listed:
  • Pandit, Harshvardhan J.
  • Esteves, Beatriz
  • Krog, Georg P
  • Ryan, Paul

Abstract

The EU GDPR is a landmark regulation that introduced several rights for individuals to obtain information and control how their personal data is being processed, as well as receive a copy of it. However, there are gaps in the effective use of rights due to each organisation developing custom methods for rights declaration and management. Simultaneously, there is a technological gap as there is no single consistent standards-based mechanism that can automate the handling of rights for both organisations and individuals. In this article, we present a specification for exercising and managing rights in a machine-interpretable format based on semantic web standards. Our approach uses the comprehensive Data Privacy Vocabulary to create a streamlined workflow for individuals to understand what rights exist, how and where to exercise them, and for organisations to effectively manage them. This work pushes the state of the art in GDPR rights management and is crucial for data reuse and rights management under technologically intensive developments, such as Data Spaces.

Suggested Citation

  • Pandit, Harshvardhan J. & Esteves, Beatriz & Krog, Georg P & Ryan, Paul, 2024. "How to Manage My Data? With Machine--Interpretable GDPR Rights!," OSF Preprints kms9n, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:kms9n
    DOI: 10.31219/osf.io/kms9n
    as

    Download full text from publisher

    File URL: https://osf.io/download/676358bf5d23ca2047a33bcf/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/kms9n?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:osfxxx:kms9n. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.