Non-Linear Multi-Dimensional Scaling (MDS) is a set of methods designed to show relationships between items. The explored dataset is displayed as points on a low-dimensional output space. Most of the time, the output space is a Euclidean 2D space, which is proposed as a "map" of data. These techniques are particularly used to explore high dimensional data. Indeed, MDS techniques are expected to retrieve the spatial organisation of high dimensional dataset. To achieve this goal, linear, as well as non-linear Multi-Dimensional Scaling methods preserve the distances between data "as much as possible", according to criteria depending on the method. 18 Usually, small distances are emphasized.