News
Seminar
A Conceptual Perspective for Spatio-Temporal Data Warehouses
by Mr Esteban Zimanyi, Professor at the University Libre de Bruxelles
April 14th 2010, 14:00 pm
Seminar room, LIRMM
Abstract
Data warehouses and OLAP are related technologies that underpin nowadays’ decision-support systems. They are based on a multidimensional model composed of dimensions, fact relationships, measures, and hierarchies allowing users to view data at different levels of detail. As all business-related data involve information about location and time, extending data warehouses with spatial and temporal data has becoming the focus of many research works. At the same time, organizations are including spatial decision support systems into their overall management strategy. However, there are still many issues to be solved in this area, in particular in the area of conceptual modeling for multidimensional data.
In the talk we first present the MultiDim model, a conceptual model for multidimensional data based on the classical ER model. Then, we present the spatial and temporal extensions of the MultiDim model. The presented concepts aim at improving the analysis and design of spatio-temporal data warehouses. In this way decision-making users can represent in an abstract manner their analysis needs without considering complex implementation issues and tool developers can have a common vision for representing spatial/temporal data in a multidimensional model.
by Mr Esteban Zimanyi, Professor at the University Libre de Bruxelles
April 14th 2010, 14:00 pm
Seminar room, LIRMM
Abstract
Data warehouses and OLAP are related technologies that underpin nowadays’ decision-support systems. They are based on a multidimensional model composed of dimensions, fact relationships, measures, and hierarchies allowing users to view data at different levels of detail. As all business-related data involve information about location and time, extending data warehouses with spatial and temporal data has becoming the focus of many research works. At the same time, organizations are including spatial decision support systems into their overall management strategy. However, there are still many issues to be solved in this area, in particular in the area of conceptual modeling for multidimensional data.
In the talk we first present the MultiDim model, a conceptual model for multidimensional data based on the classical ER model. Then, we present the spatial and temporal extensions of the MultiDim model. The presented concepts aim at improving the analysis and design of spatio-temporal data warehouses. In this way decision-making users can represent in an abstract manner their analysis needs without considering complex implementation issues and tool developers can have a common vision for representing spatial/temporal data in a multidimensional model.
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Caroline Imbert
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