Adding semantic modules to improve goal-oriented analysis of data warehouses using I-star |
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| Affiliation: | 1. Lucentia Research Group, Department of Software and Computing Systems, University of Alicante, Carretera San Vicente del Raspeig s/n, 03690 San Vicente del Raspeig, Alicante, Spain;2. BarcelonaTech, Universitat Politècnica de Catalunya, Calle Jordi Girona, 31, 08034 Barcelona, Spain;1. Department of Mechanical and Industrial Engineering and the Iowa Informatics Initiative, The University of Iowa, Iowa City, USA;2. Bell Labs, Nokia, Espoo, Finland;3. Department of Information and Computer Science, Aalto University School of Science, FI-00076, Finland;4. Department of Business Management and Analytics, Arcada University of Applied Sciences, Helsinki, Finland;5. Risklab at Arcada University of Applied Sciences, Helsinki, Finland;6. School of Information Science and Engineering, Ocean University of China, Qingdao, China;7. School of Engineering and Computer Science, Oakland University, Rochester, USA;1. Department of Computer Science, University of Taipei, No. 1, Aiguo W. Rd., Taipei 100, Taiwan;2. Department of Information and Finance Management, Institute of Information Management and Institute of Finance, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu 300, Taiwan;3. Department of Finance and Department of Computer Science & Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 106, Taiwan |
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| Abstract: | The success rate of data warehouse (DW) development is improved by performing a requirements elicitation stage in which the users’ needs are modeled. Currently, among the different proposals for modeling requirements, there is a special focus on goal-oriented models, and in particular on the i* framework. In order to adapt this framework for DW development, we previously developed a UML profile for DWs. However, as the general i* framework, the proposal lacks modularity. This has a specially negative impact for DW development, since DW requirement models tend to include a huge number of elements with crossed relationships between them. In turn, the readability of the models is decreased, harming their utility and increasing the error rate and development time. In this paper, we propose an extension of our i* profile for DWs considering the modularization of goals. We provide a set of guidelines in order to correctly apply our proposal. Furthermore, we have performed an experiment in order to assess the validity our proposal. The benefits of our proposal are an increase in the modularity and scalability of the models which, in turn, increases the error correction capability, and makes complex models easier to understand by DW developers and non expert users. |
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| Keywords: | Data warehouses User requirements I-star |
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