A personalization process for spatial data warehouse development

摘要

Spatial data warehouses (SDW) rely on extended multidimensional (MD) models in order to provide decision makers with appropriate structures to intuitively explore spatial data by using different analysis techniques such as OLAP (On-Line Analytical Processing) or data mining. Current development approaches are focused on defining a unique and static Spatial multidimensional (SMD) schema at the conceptual level over which all decision makers fulfill their current spatial information needs. However, considering the required spatiality for each decision maker is likely to derive in a potentially misleading SMD schema (even if a departmental DW or data mart is being defined). Furthermore, spatial needs of each decision maker could change over time or depending on the context, thus requiring the SMD schema to be continuously updated with changes that can hamper decision making. Therefore, if a unique and static SMD schema is designed, acquiring the required spatial information is more costly than expected for decision makers and they may get frustrated during the analysis. To overcome these drawbacks, we argue for considering spatiality as a personalization feature within a formal design process. In this way, each decision maker will be able to access its own personalized SMD schema with its required spatial structures and instances, suitable to be properly analyzed at a glance. Our approach considers several novel artifacts: (i) a UML profile for spatial multidimensional modeling at the conceptual level, (ii) a spatial-aware user model in order to define decision maker profile; and (iii) a spatial personalization language to define spatial needs of decision makers as personalization rules. The definition of personalized SMD schemas by using these artifacts is formally defined using the Software Process Engineering Metamodel Specification (SPEM) standard. Finally, the applicability of our approach is shown through a running example based on our Eclipse-based tool for SDW development.