Created with : Python, MAX-MSP, arduino, servo motor, directional speaker
Data Landscape is an attempt to shape data space entirely distinct from machine side structure, focusing instead on observations of user side phenomena, starting with the question of where digital data exists. An answer to the question can be various, but generally, digital data is considered to be bound to physical devices, and our relationship with data has been established by design and technology largely based on this common idea. However, in a specific dataset such as geographic coordinate system, the existence of data can be defined differently. Any dataset associated with geographical coordinate system can have geographical presence in the same way buildings, trees, or mountains with high degree of internal dynamics, and becomes to form an alternative environment, or Data Landscape. Thus, we sense the presence of data as environmental elements. Data Landscape’s series of design experiments explore the meaning of ‘feeling’ the presence of data instead of ‘reading’ it, and the impacts of it, by creating a specific acoustic environment consists of sonified data. Furthermore, Data Landscape will suggest an alternative norm that can redefine the human-data relationship as well as provide a new context for creative process.
Twitter Noise Machine #1
Every Twitter entry has its own GPS value, depending on a location an entry was created. Twitter Noise Machine translates local Tweets to various sound form such as pseudo-speech and ambient noise, according to content, length, frequency, and location of Tweet entries. By the sonification process, Twitter Noise Machine allows audience to feel and hear dynamics of Twitter system in current location intuitively. In this specific version of the machine, it demonstrate various field recordings from different locations.
Twitter Noise Machine #2 is designed to focus on an individual experience.A directional speaker mounted on a base turns toward the closest audience, plays Twitter Noise of the specific direction. As a result, the audience becomes to hear Twitter activity of the position where he or she is standing. Unlike Machine #1, #2 was created to allow audience to actively move and explore Twitter Noise.