Improving Comparative Analysis for the Evaluation of AOSE Methodologies

AOSE methodologies, as they have been proposed so far, mainly try to suggest a clean and disciplined approach to analyze, design and develop MASs by using specific methods and techniques. Moreover, different studies have been proposed for the evaluation of agent-oriented methodologies adopting specific types of evaluation and criteria. However, little effort has been devoted to the comparison among such different evaluations. Comparison techniques may help in finding out new information from the existing studies, consolidating the results from the available evaluations, and consequently in obtaining greater reliability from the evaluation results and their acceptance. With the aim of improving the acceptability of agent-oriented methodologies evaluation in the agent community, among the existing comparative techniques, the paper proposes the Profile Analysis technique for comparing evaluations carried out by different authors (perhaps using different evaluation frameworks). To exemplify the proposal, we present the application of the Profile Analysis technique on a case study

An evaluation of the challenges of Multilingualism in Data Warehouse development

In this paper we discuss Business Intelligence and define what is meant by support for Multilingualism in a Business Intelligence reporting context. We identify support for Multilingualism as a challenging issue which has implications for data warehouse design and reporting performance. Data warehouses are a core component of most Business Intelligence systems and the star schema is the approach most widely used to develop data warehouses and dimensional Data Marts. We discuss the way in which Multilingualism can be supported in the Star Schema and identify that current approaches have serious limitations which include data redundancy and data manipulation, performance and maintenance issues. We propose a new approach to enable the optimal application of multilingualism in Business Intelligence. The proposed approach was found to produce satisfactory results when used in a proof-of-concept environment. Future work will include testing the approach in an enterprise environmen