The term multidimensional aggregate data (MAD; see Rafanelli, 2003) generally refers to data in which a given fact is quantified by a set of measures obtained applying one more or less complex aggregative function (count, sum, average, percent, etc.) to row data, measures that are characterized by a set of variables, called dimensions. MAD can be modeled by different representations, depending on the application field which uses them. For example, some years ago this term referred essentially to statistical data, that is, data whose use is essentially of socio-economic analysis. Recently, the metaphor of the data cube was taken up again and used for new applications, such as On-Line Analytical Processing (OLAP), which refer to aggregate and non aggregate data for business analysis.