Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

January 27, 2014

The Sonification Handbook

Filed under: BigData,Data Mining,Music,Sonification,Sound — Patrick Durusau @ 5:26 pm

The Sonification Handbook. Edited by Thomas Hermann, Andy Hunt, John G. Neuhoff. (Logos Publishing House, Berlin 2011, 586 pages, 1. edition (11/2011) ISBN 978-3-8325-2819-5)

Summary:

This book is a comprehensive introductory presentation of the key research areas in the interdisciplinary fields of sonification and auditory display. Chapters are written by leading experts, providing a wide-range coverage of the central issues, and can be read from start to finish, or dipped into as required (like a smorgasbord menu).

Sonification conveys information by using non-speech sounds. To listen to data as sound and noise can be a surprising new experience with diverse applications ranging from novel interfaces for visually impaired people to data analysis problems in many scientific fields.

This book gives a solid introduction to the field of auditory display, the techniques for sonification, suitable technologies for developing sonification algorithms, and the most promising application areas. The book is accompanied by the online repository of sound examples.

The text has this advice for readers:

The Sonification Handbook is intended to be a resource for lectures, a textbook, a reference, and an inspiring book. One important objective was to enable a highly vivid experience for the reader, by interleaving as many sound examples and interaction videos as possible. We strongly recommend making use of these media. A text on auditory display without listening to the sounds would resemble a book on visualization without any pictures. When reading the pdf on screen, the sound example names link directly to the corresponding website at http://sonification.de/handbook. The margin symbol is also an active link to the chapter’s main page with supplementary material. Readers of the printed book are asked to check this website manually.

Did I mention the entire text, all 586 pages, can be downloaded for free?

Here’s an interesting idea: What if you had several dozen workers listening to sonofied versions of the same data stream, listening along different dimensions for changes in pitch or tone? When heard, each user signals the change. When some N of the dimensions all have a change at the same time, the data set is pulled at that point for further investigation.

I will regret suggesting that idea. Someone from a leading patent holder will boilerplate an application together tomorrow and file it with the patent office. 😉

NASA’s Voyager Data Is Now a Musical

Filed under: Music,Sonification,Sound — Patrick Durusau @ 5:01 pm

NASA’s Voyager Data Is Now a Musical by Victoria Turk.

From the post:

You might think that big data would sound like so many binary beeps, but a project manager at Géant in the UK has turned 320,000 measurements from NASA Voyager equipment into a classically-inspired track. The company describes it as “an up-tempo string and piano orchestral piece.”

Domenico Vicinanza, who is a trained musician as well as a physicist, took measurements from the cosmic ray detectors on Voyager 1 and Voyager 2 at hour intervals, and converted it into two melodies. The result is a duet: the data sets from the two spacecraft play off each other throughout to create a rather charming harmony. …

Data sonification, the technique of representing data points with sound, makes it easier to spot trends, peaks, patterns, and anomalies in a huge data set without having to pore over the numbers.

Some data sonification resources:

audiolyzR: Data sonification with R

Georgia Tech Sonification Lab

Sonification Sandbox

Sonification.de

I suspect that sonification is a much better way to review monotonous data for any unusual entries.

My noticing an OMB calculation that multiplied a budget item by zero (0) and produced a larger number, was just chance. Had math operations been set to music, I am sure that would have struck a discordant note!

Human eyesight is superior to computers for galaxy classification.

Human hearing as superior way to explore massive datasets is a promising avenue of research.

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