Growing Data
data visualization research project


2009
Growing Data is a research project that examines how real processes and structures can be used to create an alternative form of data visualization to traditional statistical diagrams. Formal aspects of the most diverse natural phenomena are translated into visual systems. Generative strategies in particular lend themselves to creating visual patterns and structures, while the human brain is a master at quickly interpreting such structures and assembling these into an overall picture. Both of these characteristics are used to depict data in a different way. Rather than using the same abstract forms of data visualization over and over again, the main objective hereby is to allow new images to emerge that are not committed to the precision of the data but that tell a story and provide a quick overview.
The main objective is to allow new images to emerge that are not committed to the precision of the data but that tell a story and provide a quick overview.
The project Growing Data is a part of this series and, using virtual plant growth, examines the possibilities of visualizing the air quality in various large cities. If one considers using plants or other growing life forms for this, the most obvious thing is to use the growth itself as the indicator for the changing data. Just as properties of the plants’ growth are determined by external influences, various data can control different aspects of digital growth. This data is assigned to different variables, which, for example, are responsible for life span, density and speed of growth. In order to relay information more directly and to reinforce its message, an additional information level is added in which names, words and symbols are gradually created from the growing structures.
Connected to various data interface and data bases, both the current data of various large cities and the reference values from other years can be visualized. The program is based primarily on a complex version of the “agent model” in which various agents are controlled by Brownian motion and are influenced in their movement by various variables.
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