Paper
4 March 2011 Metadata Mapper: a web service for mapping data between independent visual analysis components, guided by perceptual rules
Bernice E. Rogowitz, Naim Matasci
Author Affiliations +
Proceedings Volume 7865, Human Vision and Electronic Imaging XVI; 78650I (2011) https://doi.org/10.1117/12.881734
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States
Abstract
The explosion of online scientific data from experiments, simulations, and observations has given rise to an avalanche of algorithmic, visualization and imaging methods. There has also been enormous growth in the introduction of tools that provide interactive interfaces for exploring these data dynamically. Most systems, however, do not support the realtime exploration of patterns and relationships across tools and do not provide guidance on which colors, colormaps or visual metaphors will be most effective. In this paper, we introduce a general architecture for sharing metadata between applications and a "Metadata Mapper" component that allows the analyst to decide how metadata from one component should be represented in another, guided by perceptual rules. This system is designed to support "brushing [1]," in which highlighting a region of interest in one application automatically highlights corresponding values in another, allowing the scientist to develop insights from multiple sources. Our work builds on the component-based iPlant Cyberinfrastructure [2] and provides a general approach to supporting interactive, exploration across independent visualization and visual analysis components.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bernice E. Rogowitz and Naim Matasci "Metadata Mapper: a web service for mapping data between independent visual analysis components, guided by perceptual rules", Proc. SPIE 7865, Human Vision and Electronic Imaging XVI, 78650I (4 March 2011); https://doi.org/10.1117/12.881734
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Cited by 5 scholarly publications.
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KEYWORDS
Visualization

Visual analytics

3D modeling

Associative arrays

Biological research

Human-machine interfaces

Software development

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