Handling multiple points of view in a multimedia data warehouse

Abstract

Data warehouses are dedicated to collecting heterogeneous and distributed data in order to perform decision analysis. Based on multidimensional model, OLAP commercial environments such as they are currently designed in traditional applications are used to provide means for the analysis of facts that are depicted by numeric data (e.g., sales depicted by amount or quantity sold). However, in numerous fields, like in medical or bioinformatics, multimedia data are used as valuable information in the decisional process. One of the problems when integrating multimedia data as facts in a multidimensional model is to deal with dimensions built on descriptors that can be obtained by various computation modes on raw multimedia data. Taking into account these computation modes makes possible the characterization of the data by various points of view depending on the user's profile, his best-practices, his level of expertise, and so on. We propose a new multidimensional model that integrates functional dimension versions allowing the descriptors of the multidimensional data to be computed by different functions. With this approach, the user is able to obtain and choose multiple points of view on the data he analyses. This model is used to develop an OLAP application for navigation into a hypercube integrating various functional dimension versions for the calculus of descriptors in a medical use case.