The goal of this project was to sonify a data set. In particular, we were assigned to find an interesting time series and map the data to musical elements. I chose to use unemployment data for two sets of people: those under and those over 25 years of age. The time series consisted of monthly unemployment rates from the years 1983 to 2012. In order to map the data to sound, all data points were standardized to values between 0.0 and 1.0, and were used to adjust parameters of our oscillators and effects such as pitch, gain, and others. The goal with my data to sound mapping was to create distinct audio queues of times of unusually high unemployment. I achieved this by associating high unemployment with louder sound (gain), higher pitch (frequency). Because I chose to use the flute/clarinet unit generators, I was able to additionally map parameters such as the reed stiffness and noise gain to create a more distinct audio queue to signal high unemployment (reed stiffness and noise gain would be greater). Lastly, I mapped the reverb mix to the data to create an even more clear signal for data points.
The name of the data set was Harmonised unemployment rates (%) - monthly data, collected by Eurostat, and found via DataMarket (link directly below)
Thank you DataMarket.