
Abstract Context Data warehouses are systems which integrate heterogeneous sources to support the decision making process. Data from the Web is becoming increasingly more important as sources for these systems, which has motivated the extensive use of XML to facilitate data and metadata interchange among heterogeneous data sources from the Web and the data warehouse. However, the business information that data warehouses manage is highly sensitive and must, therefore, be carefully protected. Security is thus a key issue in the design of data warehouses, regardless of the implementation technology. It is important to note that the idiosyncrasy of the unstructured and semi-structured data requires particular security rules that have been specifically tailored to these systems in order to permit their particularities to be captured correctly. Unfortunately, although security issues have been considered in the development of traditional data warehouses, current research lacks approaches with which to consider security when the target platform is based on XML technology. Objective We shall focus on defining transformations to obtain a secure XML Schema from the conceptual multidimensional model of a data warehouse. Method We have first defined the rationale behind the transformation rules and how they have been developed in natural language, and we have then established them clearly and formally by using the QVT language. Finally, in order to validate our proposal we have carried out a case study. Results We have proposed an approach for the model driven development of Secure XML Data Warehouses, defining a set of QVT transformation rules. Conclusion The main benefit of our proposal is that it is possible to model security requirements together with the conceptual model of the data warehouse during the early stages of a project, and automatically obtain the corresponding implementation for XML.
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
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