Crystallization sonification of high-dimensional datasets

ABSTRACT

This paper introduces Crystallization Sonification, a sonification model for exploratory analysis of high-dimensional datasets. The model is designed to provide information about the intrinsic data dimensionality (which is a local feature) and the global data dimensionality, as well as the transitions between a local and global view on a dataset. Furthermore the sound allows to display the clustering in high-dimensional datasets. The model defines a crystal growth process in the high-dimensional data-space which starts at a user selected “condensation nucleus” and incrementally includes neighboring data according to some growth criterion. The sound summarizes the temporal evolution of this crystal growth process. For introducing the model, a simple growth law is used. Other growth laws which are used in the context of hierarchical clustering are also suited and their application in crystallization sonification offers new ways to inspect the results of data clustering as an alternative to dendrogram plots. In this paper, the sonification model is described and example sonifications are presented for some synthetic high-dimensional datasets.

REFERENCES

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.5 Sound and Music Computing

Additional Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.2 User Interfaces (D.2.2, H.1.2, I.3.6)
          Subjects: Auditory (non-speech) feedback

  I. Computing Methodologies
  I.6 SIMULATION AND MODELING
      I.6.5 Model Development

General Terms:
Algorithms, Design

Keywords:
Data Mining, Sonification, exploratory data analysis, interactive sonification