The Journal of the Society for Art and Science
Online ISSN : 1347-2267
ISSN-L : 1347-2267
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iSea: Visualization of Relationship by Combining Sea Condition and Catch Data
Kenta MaruyamaKatsutsugu Matsuyama
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2021 Volume 20 Issue 2 Pages 160-170

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Abstract
We propose a visualization technique for analyzing relationship between sea condition and catch data. In order for people to predict fish catches in the short term and at the local level, we believe that understanding the relationship between sea conditions and fish catches is essential. We develop an information visualization tool that allows users to investigate the relationship between the two. In this research, we design a coarse-to-fine user interface to grasp the overall trend and then see the details through interaction. Specifically, our tool start with overall visibility through time series graphs of fish catches, then identify representative sea conditions that satisfy the survey conditions, and investigate partial characteristics of the sea conditions. In order to realize the user interface, we have developed a new method for collecting sea condition data similar to the target condition, and a method for visualizing partial similarities and differences in sea condition. We implemented the proposed tool and confirmed the effectiveness of our user interface.
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© 2021 The Society for Art and Science
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