An UML profile and SOLAP datacubes multidimensional schemas transformation process for datacubes risk-aware design
Un profile UML et un processus de transformation des schémas multidimensionnels SOLAP pour la conception des cubes SOLAP avec la prise en compte du risque
Résumé
Spatial Data Warehouses (SDWs) and Spatial On-Line Analytical Processing (SOLAP) systems are new technologies for the integration and the analysis of huge volume of data with spatial reference. Spatial vagueness is often neglected in these types of systems and the data and analysis results are considered reliable. In a previous work, we provided a new design method for SOLAP datacubes that allows the handling of vague spatial data analysis issues. The method consists of tailoring SOLAP datacubes schemas to end-users tolerance levels to identified potential risks of misinterpretation they encounter when exploiting datacubes containing vague spatial data. It this paper, we further our previous proposal by presenting different formal tools to support our method: It is an UML profile providing stereotypes needed to add vague, risks and tolerance levels information on datacubes schemas plus the formal definition of SOLAP datacubes schemas transformation process and functions.