Data Warehouses and On-Line Analytical Processing systems rely on a multidimensional model that includes dimensions, hierarchies, and measures. Such model allows to express users' requirements for supporting the decision-making process and to facilitate its afterward implementation. Although Data Warehouses typically include a spatial or location dimension, this dimension is usually represented in an alphanumeric format. However, it is well-known that a visual representation of spatial data allows to reveal patterns that are difficult to discover otherwise. Further, a multidimensional model is seldom used for representing spatial data.In this work we propose an extension of a conceptual multidimensional model with spatial dimensions, spatial hierarchies, and spatial measures. We also consider the inclusion of topological relationships and topological operators in the model. We analyze different scenarios showing the significance and convenience of the proposed extension.
The MultiDimER model is a conceptual model used for representing a multidimensional view of data for Data Warehouse (DW) and On-Line Analytical Processing (OLAP) applications. This model includes a spatial extension allowing spatiality in levels, hierarchies, fact relationships, and measures. In this way decisionmaking users can represent in an abstract manner their analysis needs without considering complex implementation issues and spatial OLAP tools developers can have a common vision for representing spatial data in a multidimensional model. In this paper we propose the transformation of a conceptual schema based on the MultiDimER constructs to an object-relational schema. We based our mapping on the SQL:2003 and SQL/MM standards giving examples of commercial implementation using Oracle 10g with its spatial extension. Further we use spatial integrity constraints to ensure the semantic equivalence of the conceptual and logical schemas. We also show some examples of Oracle spatial functions, including aggregation functions required for the manipulation of spatial data. The described mappings to the object-relational model along with the examples using a commercial system show the feasibility of implementing spatial DWs in current commercial DBMSs. Further, using integrated architectures, where spatial and thematic data is defined within the same DBMS, facilitates the system management simplifying data definition and manipulation.The work of E. Malinowski was funded by a scholarship
OLAP (On-Line Analytical Processing) tools support the decisionmaking process by giving users the possibility to dynamically analyze high volumes of historical data using operations such as roll-up and drill-down. These operations need well-defined hierarchies in order to prepare automatic calculations. However, many kinds of complex hierarchies arising in real-world situations are not addressed by current OLAP implementations. Based on an analysis of real-world applications and scientific works related to multidimensional modeling, this paper presents a conceptual classification of hierarchies and proposes graphical notations for them based on the ER model. A conceptual representation of hierarchies allows the designer to properly represent users' requirements in multidimensional modeling and offers a common vision of these hierarchies for conceptual modeling and OLAP tools implementers. * This work was funded by a scholarship of the Cooperation Department of the Université Libre de Bruxelles. ** Currently on leave from the Universidad de Costa Rica. 1 Other names, such as dimension attributes [5] or category attributes [15] are also used. 2 They also are called non-dimension attributes [5].
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