IDEAS home Printed from https://ideas.repec.org/a/wsi/jikmxx/v10y2011i02ns0219649211002936.html
   My bibliography  Save this article

Automated Generation of Personal Data Reports from Relational Databases

Author

Listed:
  • Georgios John Fakas

    (Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, M1 5GD, UK)

  • Ben Cawley

    (Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, M1 5GD, UK)

  • Zhi Cai

    (Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, M1 5GD, UK)

Abstract

This paper presents a novel approach for extracting personal data and automatically generating Personal Data Reports (PDRs) from relational databases. Such PDRs can be used among other purposes for compliance with Subject Access Requests of Data Protection Acts. Two methodologies with different usability characteristics are introduced: (1) theGDSBased Methodand (2) theBy Schema Browsing Method. The proposed methdologies combine the use of graphs and query languages for the construction of PDRs. The novelty of these methodologies is that they do not require any prior knowledge of either the database schema or of any query language by the users. An optimisation algorithm is proposed that employs Hash Tables and reuses already found data. We conducted several queries on two standard benchmark databases (i.e. TPC-H and Microsoft Northwind) and we present the performance results.

Suggested Citation

  • Georgios John Fakas & Ben Cawley & Zhi Cai, 2011. "Automated Generation of Personal Data Reports from Relational Databases," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 193-208.
    • Handle: RePEc:wsi:jikmxx:v:10:y:2011:i:02:n:s0219649211002936
    DOI: 10.1142/S0219649211002936
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219649211002936
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219649211002936?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:wsi:jikmxx:v:10:y:2011:i:02:n:s0219649211002936. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/jikm/jikm.shtml .

    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.