2014•Unpublished venueRequires access

Big Data Analysis with Interactive Visualization using R packages

Wonhee Cho, Yoojin Lim, Hwangro Lee, N. Mohan Krishna Varma, Moon‐Soo Lee, Eunmi Choi

Open publisher page 12 citations

Abstract

Compared to the traditional data storing, processing, analyzing and visualization which have been performed, Big data requires evolutionary technologies of massive data processing on distributed and parallel systems, such as Hadoop system. Big data analytic systems, thus, have been popular to derive important decision making in various areas. However, visualization on analytic system faces various limitation due to the huge amount of data. This brings the necessity of interactive visualization techniques beyond the traditional static visualization. R has been used and improved for a big data analysis and mining tool. Also, R is supported with various and abundant packages for different targets with visualization. However interactive visualization packages are not easily found in the market. This paper compares and analyzes interactive web packages with visualization packages for R. This paper also proposes interactive web visualized analysis environment for big data with a combination of interactive web packages and visualization packages. In particular, Big data analysis techniques with sensed data are presented as the result by reflecting the decision view on sensing field.

About this research paper

What this paper is about

Compared to the traditional data storing, processing, analyzing and visualization which have been performed, Big data requires evolutionary technologies of massive data processing on distributed and parallel systems, such as Hadoop system. Big data analytic systems, thus, have been popular to derive important decision making in various areas. However, visualization on analytic system faces various limitation due to the huge amount of data. This brings the necessity of interactive visualization techniques beyond the traditional static visualization. R has been used and improved for a big data analysis and mining tool. Also, R is supported with various and abundant packages for different targets with visualization. However interactive visualization packages are not easily found in the market. This paper compares and analyzes interactive web packages with visualization packages for R. This paper also proposes interactive web visualized analysis environment for big data with a combination of interactive web packages and visualization packages. In particular, Big data analysis techniques with sensed data are presented as the result by reflecting the decision view on sensing field.

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OpenAlex reports 12 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Compared to the traditional data storing, processing, analyzing and visualization which have been performed, Big data requires evolutionary technologies of massive data processing on distributed and parallel systems, such as Hadoop system. Big data analytic systems, thus, have been popular to derive important decision making in various areas. However, visualization on analytic system faces various limitation due to the huge amount of data. This brings the necessity of interactive visualization techniques beyond the traditional static visualization. R has been used and improved for a big data analysis and mining tool. Also, R is supported with various and abundant packages for different targets with visualization. However interactive visualization packages are not easily found in the market. This paper compares and analyzes interactive web packages with visualization packages for R. This paper also proposes interactive web visualized analysis environment for big data with a combination of interactive web packages and visualization packages. In particular, Big data analysis techniques with sensed data are presented as the result by reflecting the decision view on sensing field.

Key concepts: Visualization, Big data, Computer science, Interactive visualization, Data visualization, Interactive visual analysis, Data science, Information visualization

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