There's a recent paper by McIntosh et al. (2013), titled "Listen to Your Data: Econometric Model Specification Through Sonification" that I really enjoyed. It's thought-provoking and innovative, and it takes things a lot further than what I mentioned in a previous post on data sonification.
Here's the abstract:
"Ever since 1927, when Al Jolson spoke in the first “talkie” film The Jazz Singer, there had been little doubt that sound added a valuable perceptual dimension to visual media. However, despite the advances of over 80 years, and the complete integration of sound and vision that has occurred in entertainment applications, the use of sound to channel data occurring in everyday life has remained rather primitive, limited to such things as computer beeps and jingles for certain mouse and key actions, low battery alarms on a mobile devices, and other sounds that simply indicate when some trigger state has been reached – the information content of such sounds is not high.
Non-binary, but still technically rather simple data applications include the familiar rattling sound of a Geiger counter, talking clocks and thermometers, or the sound output of a hospital EKG machine. What if deletion of larger and/or more recently accessed computer files resulted in a more complex sound than for deleting smaller or rarely accessed files, increasing the user’s awareness of the loss of larger or more recent work efforts? All of these are examples of data sonification.
While sonification seems to be pursued mostly by those wishing to generate tuneful results, many are undertaking the process to simply provide another method of presenting data. Many examples are available at https://soundcloud.com/tags/sonification including some very tuneful arrangements of the Higgs Boson. Indeed, with complex data series one can often hear patterns or persistent pitches that would be difficult to show visually. Musical pitches are periodic components of sound and repetition over time can be readily discerned by the listener. Sonification techniques have been applied to a variety of topics (Pauletto and Hunt, 2009; Scaletti and Craig 1991; Sturm, 2005; Dunn and Clark, 1999). To the authors’ knowledge, Sonification has yet to be applied in any substantive way to economic data.
Our goal is not to produce tuneful results. Rather, the purpose of this paper is to explore the potential application of Sonification techniques for informing and assessing the specification of econometric models for representing economic data outcomes. The purpose of this seminal and exploratory analysis is to investigate whether there appears to be significant promise in adding the data sonification approach to the empirical economists’ toolkit for interpreting economic data and specifying econometric models. In particular, is there an advantage to using both the empirical analyst’s eyes and ears when investigating empirical economic problems?"In case you're wondering what the a rejection of the null hypothesis of homoskedasticity sounds like, here's the answer:
Read the paper and you can actually listen to the results!
Now, once more, from the top - with feeling!
© 2013, David E. Giles