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Modeling Global-scale Data Marts Based on Federated Data Warehousing Application Framework

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 9978)

Abstract

Data warehouses become large in size, dynamic, and physically distributed. In this context, federated data warehousing approach is a promising solution for specifying, designing, deploying as well as managing data marts and their data cubes. In this paper, the Federated Data warehousing Application (FDWA) framework has been used to specify global-scale data marts. To proof of our concepts, a global-scale analytical tool, namely GAINS-IAM (integrated assess model) will be presented as a case study to analyze recent trends and future world emission scenarios.

Keywords

  • FDWA (Federated Data Warehousing Application)
  • GAINS (Greenhouse Gas - Air Pollution Interactions and Synergies)
  • Global-scale data mart
  • Greenhouse Gases (GHGs)
  • IAM (Integrated Assess Model)

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Correspondence to Ngoc Sy Ngo .

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Ngo, N.S., Nguyen, B.T. (2016). Modeling Global-scale Data Marts Based on Federated Data Warehousing Application Framework. In: Huynh, VN., Inuiguchi, M., Le, B., Le, B., Denoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2016. Lecture Notes in Computer Science(), vol 9978. Springer, Cham. https://doi.org/10.1007/978-3-319-49046-5_38

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  • DOI: https://doi.org/10.1007/978-3-319-49046-5_38

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  • Print ISBN: 978-3-319-49045-8

  • Online ISBN: 978-3-319-49046-5

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