Paper
4 June 2004 Conceptual model for adaptable and extensible visual data exploration
Maria Cristina Ferreira de Oliveira, Milton Hirokazu Shimabukuro
Author Affiliations +
Proceedings Volume 5295, Visualization and Data Analysis 2004; (2004) https://doi.org/10.1117/12.539247
Event: Electronic Imaging 2004, 2004, San Jose, California, United States
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.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Maria Cristina Ferreira de Oliveira and Milton Hirokazu Shimabukuro "Conceptual model for adaptable and extensible visual data exploration", Proc. SPIE 5295, Visualization and Data Analysis 2004, (4 June 2004); https://doi.org/10.1117/12.539247
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Cited by 1 scholarly publication.
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KEYWORDS
Visualization

Visual process modeling

Data modeling

Climatology

Knowledge discovery

Visual analytics

Data analysis

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