Symbolic Data Analysis and the SODAS Project: Purpose, History, Perspective

In many domains of human activities it is now quite common to record huge sets of data in large data bases. It becomes a task of first importance to summarize these data in terms of their underlying concepts in order to extract new knowledge from them. These concepts can only be described by more complex type of data which we call symbolic data as they contain internal variation and they are structured. In this context, we have a rapidly increasing need to extend standard data analysis methods (exploratory, graphical representations, clustering, factorial analysis, discrimination,…) to these symbolic data.