Visualisation of Multidimensional Objects and the Socio-Economical Impact to Activity in EC RTD Databases

Abstract. The paper deals with the analysis of Research and Technology Development (RTD) in the Central European countries and the relation of RTD with economic and social parameters of coun-tries in this region. A methodology has been developed for quantitative and qualitative ranking and estimates of relationship among multidimensional objects on the base of such analysis. The knowl-edge has been discovered in four databases: two databases of European Commission (EC) contain-ing data on the RTD activities, databases of USA CIA and The World bank containing economic and social data. Data mining has been performed by means of visual cluster analysis (using the non-linear Sammon’s mapping and Kohonen’s artificial neural network – the self-organising map), regression analysis and non-linear ranking (using graphs of domination). The results on clustering of the Central European countries and on the relations among RTD parameters with economic and social parameters are obtained. In addition, the data served for testing various features of realisation of the self-organising map. The integration of non-classical methods (the self-organising map and graphs of domination) with classical ones (regress analysis and Sammon ’ mapping) increases the capacity of visual analysis and allows making more complete conclusions. Key words: research and technology development, knowledge discovery, data mining, regression analysis, neural network, self-organising map, non-linear ranking, graphs of domination, visual analysis, cluster analysis