Statistical graphics history is recent, about 250 years old. Much older are cartography, the musical notation or the Cartesian axes on which graphics are based [1].The evolution that has taken place since the first line, bar or pie charts were invented by William Playfair is remarkable, particularly after the computer advent. The rise of statistical graphics cant be dissociated from the historical period theyre in: Industrial Revolution, development of sciences, the 1920’s, the growing role of literacy or socialization of information that was followed by the obscurantist phase called of ”Modern Dark Ages” [2]. The re-birth of data visualization with the invention of new exploratory information graphics [3] to handle huge amount of data was only possible with the increase of computer process- ing. The availability of big data coming from Internet and the Internet of Things (IoT) associated with computation power has created the need for new techniques for visualiz- ing/understanding data. One could think that the end of the story was near, but were far from it: data visualization is constantly reinventing itself. This paper aims to contribute to the study of theoretical and historical approach of data visualization. It proposes a quadrant model of analysis based on two perpendicular axes that translate the lesser or greater complexity of the graphical design options and the lesser or greater complexity of the concepts represented. These axes allows us to model four profiles that range from complex graphic design that describe elaborated concepts (1st quadrant) to simple graphic design that show plain ideas (3rd quadrant). The po- sition in the quadrant is related to the technology development process, meaning the more away from the center the more technology is used. Data visualization uses a similar framework as 100 years ago: simplicity in graphic design to describe different ideas. This cyclical process can be described through an upward spiral shape along the four quadrants pushed towards periphery due to technology and computer development.

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Data visualization,information graphics,history milestones

• Computer and Information Sciences - Natural Sciences
• Media and Communications - Social Sciences
• History and Archeology - Humanities
• Arts (arts, history of arts, performing arts, music) - Humanities