Automated Generation of Personal Data Reports from Relational Databases

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 usab...

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Bibliographic Details
Published inJournal of information & knowledge management Vol. 10; no. 2; pp. 193 - 208
Main Authors Fakas, Georgios John, Cawley, Ben, Cai, Zhi
Format Journal Article
LanguageEnglish
Published World Scientific Publishing Co 01.06.2011
IKMS
Subjects
Algorithmus
Data extraction
Datenbank
Graphentheorie
Information retrieval
Online-Recherche
Personal information
Privacy
privacy protection
Relational data bases
relational databases
relational databases
privacy protection
Data extraction
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Summary: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) the GDSBased Method and (2) the By 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.
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ISSN:0219-6492
1793-6926
1793-6926
DOI:10.1142/S0219649211002936