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An ontology-based approach for automatic goal requirements engineering in data warehouse design

An ontology-based approach for automatic goal requirements engineering in data warehouse design Goal-oriented approaches in data warehouse development projects still face two main issues. First, analysts often lack domain knowledge required during goal decomposition. This may lead to identifying erroneous requirements that most likely propagate to the remaining project phases, potentially leading to the project failure. Second, the identification of the data warehouse content from requirements is done manually by the designers in an error-prone process. In this paper, we address these two issues. We propose an ontology that formalises and automates the reasoning about decision-making knowledge, which allows analysts to compensate their lack of domain knowledge during goal decomposition. In addition, to demonstrate the feasibility of our proposal we present a semi-automatic process that assists the construction of the ontology. Furthermore, the proposed ontology ensures the traceability between both decision-making and data warehouse knowledge. Thanks to this traceability, we propose a set of rules that automatically derive a data warehouse schema from requirements specification. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Information and Decision Sciences Inderscience Publishers

An ontology-based approach for automatic goal requirements engineering in data warehouse design

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1756-7017
eISSN
1756-7025
DOI
10.1504/IJIDS.2021.116494
Publisher site
See Article on Publisher Site

Abstract

Goal-oriented approaches in data warehouse development projects still face two main issues. First, analysts often lack domain knowledge required during goal decomposition. This may lead to identifying erroneous requirements that most likely propagate to the remaining project phases, potentially leading to the project failure. Second, the identification of the data warehouse content from requirements is done manually by the designers in an error-prone process. In this paper, we address these two issues. We propose an ontology that formalises and automates the reasoning about decision-making knowledge, which allows analysts to compensate their lack of domain knowledge during goal decomposition. In addition, to demonstrate the feasibility of our proposal we present a semi-automatic process that assists the construction of the ontology. Furthermore, the proposed ontology ensures the traceability between both decision-making and data warehouse knowledge. Thanks to this traceability, we propose a set of rules that automatically derive a data warehouse schema from requirements specification.

Journal

International Journal of Information and Decision SciencesInderscience Publishers

Published: Jan 1, 2021

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