In groundwater quality research, researchers are often confronted with large, multidimensional datasets. An exploratory data analysis is often carried out, aiming at summarizing the available data, extracting useful information and formulating hypothesis for further research. The techniques traditionally used in this phase of research are basic statistics (i.e. mean, median, standard deviation) along with graphical techniques (i.e. scatter plots, his-tograms, time series plots). Also

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... e statistical techniques, like principal component analysis or discriminate analysis are used to explore mul-tidimensional datasets. Kohonen's Self-Organizing Map is an artificial neu-ral network technique, developed by Kohonen in the early '80s, especially designed for 2D visualizing and analyzing large, multidimensional datasets [3] .