2. Giving Shape to Data

A key challenge for designers is to be able to present large amounts of data in very clear and simple ways. By this, it involves bypassing, if not eliminating entirely, sophisticated forms and convoluted graphics, as well as countless textual metadata (legends or notes). High-dimensional data space, requiring the use of advanced user tools to navigate inside, is also to avoid. What it boils down to is nothing other than data assimilated into straightforward and captivating forms. The aim is to design primitive or minimal shapes stripped down to their very essence for the purposes of delivering both a sensitive and meaningful experience of datasets—this kind of experience leads us to the fundamental principles of Gestalt perception. In this chapter, we shall attempt to prove that visual and graphic representation of “Big Data” needs to shift toward a new formalized approach using pure shapes to enhance the qualities of its aesthetic perception (and improve interaction with data representation and visualization)—note that the possibility to infer phenomena from data depends mainly on the aesthetic experience of the data itself. To do so, we will refer to some cutting-edge data design projects. It will also be an opportunity to introduce a new series of large-scale data representations currently underway, entitled Data Shapes, in which the simplicity of forms is addressed.