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Automated Generation of Personal Data Reports from Relational Databases (2011)
| Citations: | 3 - 3 self |
BibTeX
@MISC{Fakas11automatedgeneration,
author = {Georgios John Fakas and Ben Cawley and Zhi Cai},
title = { Automated Generation of Personal Data Reports from Relational Databases},
year = {2011}
}
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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) the GDS-Based 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.
Keyphrases
personal data report relational database query language hash table standard benchmark database database schema microsoft northwind optimisation algorithm different usability characteristic prior knowledge gds-based method novel approach personal data data protection act subject access request schema browsing method performance result proposed methdologies several query
