RT Book, Section
SR 00
ID 10.1007/978-3-319-49046-5_38
A1 Ngo, N.S.
A1 Nguyen, B.T.
T1 Modeling Global-scale Data Marts Based on Federated Data Warehousing Application Framework
YR 2016
FD 2016-10-29
VO 9978
SP 447
OP 456
K1 FDWA (Federated Data Warehousing Application); GAINS (Greenhouse Gas - Air Pollution Interactions and Synergies); Global-scale data mart Greenhouse Gases (GHGs); IAM (Integrated Assess Model)
AB 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.
NO 5th International Symposium, IUKM 2016, Da Nang, Vietnam, November 30- December 2, 2016, Proceedings
A2 Huyn, V.M.
A2 Inuiguchi, M.
A2 Le, B.
A2 Le, B.N.
A2 Denoeux, T.
T2 Integrated Uncertainty in Knowledge Modelling and Decision Making
PB Springer International Publishing
PP Cham, Switzerland
T3 Lecture Notes in Computer Science
SN 978-3-319-49046-5
AV Published
LK https://pure.iiasa.ac.at/id/eprint/14337/