Sonification of Quarknet Data

1 Introduction

In this presentation, I discuss ways of “sonifying” data collected from the Quarknet CR detectors–that is, creating sound files from the raw data collected in experiments. The focus of this document is on the sonification process, rather than on how to use or interpret the resulting sound and sound datafiles (although I will touch on that somewhat).
Although I will describe multiple ways to sonify the data, I will provide the greatest detail for methods that involve using only free tools (open-source, in most cases), in recognition of the fact that cost is a major consideration for most schools.

2 Background

There is a growing interest in the utility of experimental data as sound, alongside the traditional graphical presentation. An article in the May 2012 Physics Today describes several researchers who are experimenting on how the human auditory system can pick out data features that may be missed by the visual system (looking at plots of data). From the Physics Today article:
Donald Gurnett of the University of Iowa has sonified data from spacecraft for decades. “When Voyager 1 flew by [Jupiter’s moon] Io in 1979,” he says, “we detected whistlers”—low-frequency radio waves. “That was first detected by hearing. Your ears are amazing at picking out fine signals. In frequency–time spectra, you can choose the resolution when you process the data. If you choose the wrong resolution, you may not detect anything. You have to match what you are processing to the time resolution. Your ear does that automatically.”

3 Sonification of data

3.1 Workflow (with Free/Open-Source Tools)

  1. Create plot in e-Lab
  2. Open analysis directory
  3. Open “plot_param”; determine which datafile is actually being plotted
    1. e.g., in a lifetime plot, the plotted file is 'frequencyOut':
    2. Note the command in plot_param file: “plot 'frequencyOut' using 1:2 with points...”
  4. Save the datafile (will save as a .txt file)
  5. Optionally save the plot image (for reference and comparison)
  6. Remove extraneous columns:
    1. Open a LibreOffice spreadsheet
    2. Open datafile; import as a tab-delimited file
    3. In the resulting spreadsheet, delete unwanted columns
  7. Time-Series Plot
  8. Amplitude-Only Plot
  9. Save As a .csv (comma-separated values) file
  10. Create binary datafile by importing text file into wxMaxima, exporting as binary:
  11. Import into Audacity
    1. File | Import | Raw Data...
    2. <choose file>...Unsigned 8-bit PCM, big-endian, 1-channel (mono), Sample Rate 2048
      1. (Feel free to experiment with these values!)
    3. You have your sound file! Mess about!
    4. Also look at Spectrogram (click on down-arrow at left of plot; brings up pop-up menu), and Analyze | Plot Spectrum
image: flux_waveform_view.png

3.1.1 Alternative Method: Sonification Sandbox

  1. Import csv file (two columns, independent variable in first column)
  2. Press “Play”
Produces a sequence of piano notes

3.2 Mathematica

Import csv file, one column (amplitudes)
image: ListPlay_image.png

4 Lifetime Plots

It is interesting to compare the sounds obtained from lifetime plots to one type of sound created from so-called Jovian whistlers.
(a) image:
(b) image:
Figure 1: (a) A typical lifetime plot from Quarknet data. (b) A spectrogram of “Jovian whistlers”

From the Space audio site at the University of Iowa:
Jovian whistler waves propagate at audio frequencies along closed field lines in Jupiter's magnetosphere. The higher frequency components of the Jovian whistler propagate faster than the lower frequency components, resulting in a descending whistling tone. Jovian whistlers are generated by lightning discharges in the atmosphere. It was the detection of these signals by the Voyager 1 spacecraft that provided the first indirect evidence of lightning on the giant planet.

5 Supplemental Links

The Sonification Handbook
Sonification Sandbox
Space Audio