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A Multidimensional Model for Data Warehouses of Simulation Results

A Multidimensional Model for Data Warehouses of Simulation Results

Hadj Mahboubi, Thierry Faure, Sandro Bimonte, Guillaume Deffuant, Jean-Pierre Chanet, François Pinet
Copyright: © 2010 |Volume: 1 |Issue: 2 |Pages: 19
ISSN: 1947-3192|EISSN: 1947-3206|EISBN13: 9781609609504|DOI: 10.4018/jaeis.2010070101
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MLA

Mahboubi, Hadj, et al. "A Multidimensional Model for Data Warehouses of Simulation Results." IJAEIS vol.1, no.2 2010: pp.1-19. http://doi.org/10.4018/jaeis.2010070101

APA

Mahboubi, H., Faure, T., Bimonte, S., Deffuant, G., Chanet, J., & Pinet, F. (2010). A Multidimensional Model for Data Warehouses of Simulation Results. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 1(2), 1-19. http://doi.org/10.4018/jaeis.2010070101

Chicago

Mahboubi, Hadj, et al. "A Multidimensional Model for Data Warehouses of Simulation Results," International Journal of Agricultural and Environmental Information Systems (IJAEIS) 1, no.2: 1-19. http://doi.org/10.4018/jaeis.2010070101

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Abstract

This paper examines the multidimensional modeling of a data warehouse for simulation results. Environmental dynamics modeling is used to study complex scenarios like urbanization, climate change and deforestation while allowing decision makers to understand and predict the evolution of the environment in response to potential value changes in a large number of influence variables. In this context, exploring simulation models produces a huge volume of data, which must often be studied extensively at different levels of aggregation due to there being a great need to define tools and methodologies specifically adapted for the storage and analysis of such complex data. Data warehousing systems provide technologies for managing simulation results from different sources. Moreover, OLAP technologies allow one to analyze and compare these results and their corresponding models. In this paper, the authors propose a generic multidimensional schema to analyze the results of a simulation model, which can guide modelers in designing specific data warehouses, and an adaptation of an OLAP client tool to provide an adequate visualization of data. As an example, a data warehouse for the analysis of results produced from a savanna simulation model is implemented using a Relational OLAP architecture.

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