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The bird’s ear view of space physics: Audification as a tool for the spectral analysis of time series data

机译:空间物理的鸟的耳朵视图:Audification作为时间的光谱分析的工具序列数据

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摘要

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.
机译:有效的导航,挖掘和分析大时间序列数据集提供了一个循环在太阳的挑战。一般听觉分析的一种具体形式用于其他领域的研究(如geoseismology),提供了一个很有前途的技术光谱特性评估长格林威治时间序列数据集。标准研究方法的发展新的分析技术,本文提出一种audification是详细的案例研究引入的工作过程经验丰富的科学家和从事研究用于识别和分类在高分辨率磁强计数据特性在一个结构化的分析任务。评价成功地检测了不是人工,instrument-induced噪音以前科学家也观察到波活动嵌入的识别太阳风湍流数据。表明,科学家继续使用这些听觉评估分析方法每一个大数据集在2个月后这项研究是完成。audification可以有价值和启用研究人员在形成一个更深层次的理解的微观结构和宏观结构在大的时间序列。独立的方法和视觉的补充分析方法,audification可以加快某些阶段数据的调查、分析和采矿过程和提供新的定性洞察时变的光谱内容信号。

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