Meta-model of information visualization based on Treemap

The interpretation and understanding of large quantities of data is a challenge for current information visualization methods. The visualization of information is important as it makes the appropriate acquisition of the information through the visualization possible. The choice of the most appropriate information visualization method before commencing with the resolution of a given visual problem is primordial to obtaining an efficient solution. The objective of this paper is to describe an information visualization classification approach based on Treemap, which is able to identify the best information visualization model for a given problem. This is understood through the construction of an adequate information visualization meta-model. Firstly, the actual state of the visualization field is described, and then the rules and criteria used in this research are shown, with the aim of presenting a meta-model proposal based on Treemap visualization methods. Besides this, the authors present a case study with the information contained in the Periodic Table visualization meta-model along with an analysis of the information search time complexity in each of the two meta-models. Finally, an evaluation of the results is presented through the experiments conducted with users and a comparative analysis of the methods based on Treemap and the Periodic Table.