Classification and Analysis of Techniques and Tools for Data Visualization Teaching

Data Visualization addresses the use of graphics with the purpose to obtain or transmit the knowledge in a easier and faster way, this is it main, and in many cases unique purpose. Since their invention Data graphics has evolved and many techniques has been developed, and in the last decades, with the definition and evolution of the Data Science, Data Visualization has become to be used profusely, in that manner that, by one side, the Data Science Body of Knowledge, DS-BoK, define five knowledge area groups that should be taught when learning Data Science, in all of them Data Visualization is taken a main role for different reasons applying each knowledge area; and by other side all the Data Science development environments, open source or proprietary, include tools for performing Data Visualizations. This paper presents the results of a research carried out with the main objective of improving the teaching of data visualization using two ways: propose a new system to classify the large amount of different graphical techniques for presenting data that can be found in the literature; and analyze using different attributes quite all the most important different tools, open source and private, that are available to develop data graphics mainly form a data visualization teaching point of view.