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

Ngo, N.S. & Nguyen, B.T. ORCID: https://orcid.org/0000-0002-2260-8186 (2016). Modeling Global-scale Data Marts Based on Federated Data Warehousing Application Framework. In: Integrated Uncertainty in Knowledge Modelling and Decision Making. Eds. Huyn, V.M., Inuiguchi, M., Le, B., Le, B.N., & Denoeux, T., pp. 447-456 Cham, Switzerland: Springer International Publishing. ISBN 978-3-319-49046-5 10.1007/978-3-319-49046-5_38.

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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.

Item Type:	Book Section
Additional Information:	5th International Symposium, IUKM 2016, Da Nang, Vietnam, November 30- December 2, 2016, Proceedings
Uncontrolled 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)
Research Programs:	Air Quality & Greenhouse Gases (AIR)
Depositing User:	Romeo Molina
Date Deposited:	25 Jan 2017 15:27
Last Modified:	27 Aug 2021 17:28
URI:	https://pure.iiasa.ac.at/14337

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