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Proceedings Paper

Conceptual model for adaptable and extensible visual data exploration
Author(s): Maria Cristina Ferreira de Oliveira; Milton Hirokazu Shimabukuro
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Paper Abstract

Interactive visual representations complement traditional statistical and machine learning techniques for data analysis, allowing users to play a more active role in a knowledge discovery process and making the whole process more understandable. Though visual representations are applicable to several stages of the knowledge discovery process, a common use of visualization is in the initial stages to explore and organize a sometimes unknown and complex data set. In this context, the integrated and coordinated-that is, user actions should be capable of affecting multiple visualizations when desired-use of multiple graphical representations allows data to be observed from several perspectives and offers richer information than isolated representations. In this paper we propose an underlying model for an extensible and adaptable environment that allows independently developed visualization components to be gradually integrated into a user configured knowledge discovery application. Because a major requirement when using multiple visual techniques is the ability to link amongst them, so that user actions executed on a representation propagate to others if desired, the model also allows runtime configuration of coordinated user actions over different visual representations. We illustrate how this environment is being used to assist data exploration and organization in a climate classification problem.

Paper Details

Date Published: 4 June 2004
PDF: 11 pages
Proc. SPIE 5295, Visualization and Data Analysis 2004, (4 June 2004); doi: 10.1117/12.539247
Show Author Affiliations
Maria Cristina Ferreira de Oliveira, Univ. de Sao Paulo (Brazil)
Milton Hirokazu Shimabukuro, Univ. de Sao Paulo (Brazil)
Univ. Estadual Paulista (Brazil)

Published in SPIE Proceedings Vol. 5295:
Visualization and Data Analysis 2004
Robert F. Erbacher; Philip C. Chen; Jonathan C. Roberts; Matti T. Gröhn; Katy Börner, Editor(s)

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