Title:
AUDIFICATION AS A DIAGNOSTIC TOOL FOR EXPLORATORY HELIOSPHERIC DATA ANALYSIS
AUDIFICATION AS A DIAGNOSTIC TOOL FOR EXPLORATORY HELIOSPHERIC DATA ANALYSIS
Authors
Alexander, Robert L
Gilbert, Jason A
Landi, Enrico
Simoni, Mary
Zurbuchen, Thomas H
Roberts, D Aaron
Gilbert, Jason A
Landi, Enrico
Simoni, Mary
Zurbuchen, Thomas H
Roberts, D Aaron
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Abstract
To date, scientific data analysis is almost exclusively
conducted through the visual modality, though the perceptual
benefits of multi-modal stimulation are well known [1].
Visualization tools utilize parameters such as color, size, and
shape to render data sets of moderate complexity. However, a
growing number of NASA instruments produce extremely large
and complex data sets that must be visually rendered in groups
of sub-dimensions [2]. One such instrument, the Solar Wind Ion
Composition Spectrometer (SWICS) on the Advanced
Composition Explorer (ACE) satellite, has measured a large
number of solar wind parameters for the last 13 years. The
effective navigation and analysis of these massive data sets is a
persistent challenge. New data mining tools are necessary in
order to fully engage the large number of variables involved
with these extremely complex systems. New multi-modal
interfaces will have far reaching applications for exploratory
heliophysics research. This work will demonstrate that
audification is a powerful diagnostic tool for mining and
analyzing solar wind data.
Through audification, this research has revealed new
insight into data parameters used for differentiating solar wind
types. For example, an ion charge state ratio previously
considered to be unimportant is proving to be a leading indicator
of the boundaries between coronal hole and non-coronal hole
wind, as discussed below. A deep understanding of space
weather, to which the solar wind is a decisive component, will
be increasingly important as we continue to explore the space
environment.
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2011-06
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