Premium
The bird's ear view of space physics: Audification as a tool for the spectral analysis of time series data
Author(s) -
Alexander Robert L.,
O'Modhrain Sile,
Roberts D. Aaron,
Gilbert Jason A.,
Zurbuchen Thomas H.
Publication year - 2014
Publication title -
journal of geophysical research: space physics
Language(s) - English
Resource type - Journals
eISSN - 2169-9402
pISSN - 2169-9380
DOI - 10.1002/2014ja020025
Subject(s) - identification (biology) , computer science , data set , process (computing) , set (abstract data type) , time series , noise (video) , data science , data mining , artificial intelligence , machine learning , biology , operating system , botany , image (mathematics) , programming language
The effective navigation, mining, and analysis of large time series data sets presents a recurring challenge throughout heliophysics. Audification, a specific form of auditory analysis commonly used in other fields of research (such as geoseismology), provides a promising technique for the evaluation of spectral features in long heliospheric time series data sets. Following a standard research methodology for the development of new analysis techniques, this paper presents a detailed case study in which audification was introduced into the working process of an experienced heliophysics research scientist and used for the identification and classification of features in high‐resolution magnetometer data during a structured analysis task. Auditory evaluation successfully led to the detection of artificial, instrument‐induced noise that was not previously observed by the scientist and also the identification of wave activity embedded within turbulent solar wind data. A follow‐up interview indicated that the scientist continued using these auditory analysis methods in the assessment of every large data set during the 2 months after the study was completed. These findings indicate that audification can be valuable and enabling for researchers in forming a deeper understanding of both microstructures and macrostructures within large time series. Additionally, as both a standalone methodology and a supplement to visual analysis methods, audification can expedite certain stages of the data survey, analysis, and mining process and provide new qualitative insight into the spectral content of time‐varying signals.