Auditory Representation of Scientific Data

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The long-term goal of this work is to develop and evaluate auditory representations of multidimensional data. For some forms of data (e.g., time series) auditory displays may be especially well suited to human perceptual analysis and possibly much more effective than current visual displays. Auditory data representation is fundamentally a mapping from a data variable to a property of a sonic event. Where the variable is multidimensional, the measure on each dimension of the data sample determines the value of the corresponding sound property of the event, and the values of all the measures together determine the overall character of the event. For example, if the event is a simple tone, one data dimension could be mapped to pitch, another to loudness, and a third to duration. A variety of auditory displays can be created depending on the kind of data and the kind of analysis to be conducted. Research in auditory data representation has been severely hampered by the lack of an appropriate computing environment. The Principal Investigators are building a prototype computing environment for research in auditory data representation and, using this environment, to develop several different auditory data representations and to conduct preliminary evaluations of these auditory data representations with both real and synthetic data.