From Transactional Spatial Databases Integrity Constraints to Spatial Datacubes Integrity Constraints

Spatial multidimensional databases (also called "spatial datacubes") are the cornerstone of the emerging Spatial On-Line Analytical Processing technology (SOLAP). They are aimed at supporting Geographic Knowledge Discovery (GKD) as well as certain types of spatial decision-making. Although these technologies seem promising at first glance, they may provide unreliable results if one does not consider the quality of spatio-temporal data. In traditional spatial databases, spatial integrity constraints have been employed to improve internal quality of spatial data. However, spatial datacubes require additional integrity constraints in comparison to the traditional databases found into transactional GIS systems. These extra constraints concern the supplementary information included in these datacubes, such as spatial dimensions and hierarchies, aggregated data, multidimensional cross-tabulation of data, and the existence of a temporal dimension with several levels of granularity. This paper presents the characteristics of spatial datacubes that differentiate them from transactional spatial databases from a spatial integrity constraint perspective. Based on these characteristics, we propose fundamental considerations for the classification of these integrity constraints and for the use of integrity constraint specification languages tailored for geospatial datacubes. Finally, the paper concludes and addresses some questions that contribute to a research agenda for the definition of spatial integrity constraints in spatial datacubes. * Corresponding author.