Data are constantly flowing around us. By capturing signals, we can weave data into sceneries. In the digital era, massive data are continuously analyzed and sorted out. Then, they are computed and used to create an order from certain perspectives to become readable information, just like what the protagonist in Matrix sees—everything comprises data flows. Even though we can never be the savior, artists can now use algorithms to tease out data and propose their own viewpoints, converting information into fuels that drive their works and visualizing data into sceneries of light and sound.
In the era of electronic community today, corporations have been gathering massive information as the digital footprints of user experience, such as user data and visitor behaviors, to formulate marketing strategies or design custom interfaces. Such gold-mining approaches enabled by big data have become ubiquitous nowadays. Nevertheless, in the field of artistic creation, viewing data analyses and algorithmic results as artistic works already emerged in the 90s ensuing the invention of the Internet. For instance, in 1993, ART+COM developed a work called Terravision, which used the global positioning system and data of satellite imagery for computation that allowed the work to move above planet Earth and visualize specific locations. Users only needed to type in their addresses, and the work would be able to endlessly enlarge aerial images taken from space, and show seamlessly images all the way from space to their houses. In addition, this work “inspired” the later invention of Google Earth. However, the differences between Terravision and modern satellite GPS system can be found in their dissimilar purposes, processes, and ways of presentation after data are induced into information by the artists—that is, the pursuit of aesthetic computing. The objective of aesthetic computing is to apply theories and practices of tech art and visual design to the field of computer science and computing, and vice versa. The aesthetic scope in art is much wider than that in mathematics and computing, in the latter of which aesthetics is usually equivalent to optimality criteria (e.g., elegant proof, crossing point of minimal line). Therefore, these new areas encourage to expand the categories of aesthetic appreciation based on art in application, and further include fundamental elements of computing, such as programs, models, and data.
