Visualization techniques for large datasets

被引:0
|
作者
Michalos, M. [1 ]
Tselenti, P. [1 ]
Nalmpantis, S.L. [2 ]
机构
[1] School of Computing, Information Systems and Mathematics, Kingston University, London, United Kingdom
[2] Department of Electrical Engineering, Kavala Institute of Technology, Kavala, Greece
关键词
Information systems - Visualization - Extraction;
D O I
10.25103/jestr.051.13
中图分类号
学科分类号
摘要
In order to improve understanding and working with data, visualizing information is without a doubt the best method to implement. Data visualization as a term unites the established field of scientific visualization and the more recent field of information visualization. The goal of data visualization is to provide the viewer an aggregated representation of available data by taking into account human's visual system and its influence to comprehension. Spotting trends, seeing patterns and identifying outliers are some of the human's visual system processes that are being manipulated in order to make data more accessible and appealing. This procedure of graphical representations creation helps engaging data exploration and even more, data extraction. Along with computer and graphical engineering, visualizations have grown and reached a very satisfactory level of variations and techniques, indulging even the most exacting data facilitators whether they are researchers, computer scientists, statisticians etc. A variety of data visualization software has been developed the last decades but Stanford University's Protovis is by far the most distinguished tool to do the job. Below, a study is presented on data visualization's purpose and prospects and how these became a necessity through time. © 2012 Kavala Institute of Technology.
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收藏
页码:72 / 76
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