The big data visualization technology based ecosystem cycle on high speed network

2019 ◽  
Vol 78 (20) ◽  
pp. 28903-28916
Author(s):  
Hye-Sun Kim ◽  
Hwa-Young Jeong ◽  
Hae-Jong Joo
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
High Speed ◽  
High Speed Network ◽  
Big Data Visualization ◽  
Visualization Technology

Research and Application of Responsive Big Data Visualization Based on HTML5

2014 ◽  
Vol 631-632 ◽  
pp. 1075-1079
Author(s):  
Pei Yang ◽  
Hai Yun Han
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Mobile Platform ◽  
Technology Research ◽  
Mass Data ◽  
Volume Velocity ◽  
Big Data Visualization ◽  
Visualization Technology ◽  
Special Points ◽  
Meaningful Data

Research the responsive visualization technology of big data based on HTML5. Big data has 4 special points: volume, velocity, variety and value. Our purpose is to mine the value of big data with the visualization technology. There are many platforms such as desktop and mobile platform, and each kind of device may have different resolution, based on HTML5, CSS3 and JavaScript technology, research the responsive visualization technology to fit all platforms, then we can mine meaningful data of the mass data, guide the development of related forecasting and strategy.

scholarly journals Research and implementation of big data visualization based on WebGIS

2019 ◽  
Vol 2 ◽  
pp. 1-6
Author(s):  
Wenjuan Lu ◽  
Aiguo Liu ◽  
Chengcheng Zhang
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Visual Analysis ◽  
Distributed Database ◽  
Research Problem ◽  
Research Area ◽  
Geographical Information ◽  
Data Set ◽  
Visualization Technology ◽  
Thematic Data

<p><strong>Abstract.</strong> With the development of geographic information technology, the way to get geographical information is constantly, and the data of space-time is exploding, and more and more scholars have started to develop a field of data processing and space and time analysis. In this, the traditional data visualization technology is high in popularity and simple and easy to understand, through simple pie chart and histogram, which can reveal and analyze the characteristics of the data itself, but still cannot combine with the map better to display the hidden time and space information to exert its application value. How to fully explore the spatiotemporal information contained in massive data and accurately explore the spatial distribution and variation rules of geographical things and phenomena is a key research problem at present. Based on this, this paper designed and constructed a universal thematic data visual analysis system that supports the full functions of data warehousing, data management, data analysis and data visualization. In this paper, Weifang city is taken as the research area, starting from the aspects of rainfall interpolation analysis and population comprehensive analysis of Weifang, etc., the author realizes the fast and efficient display under the big data set, and fully displays the characteristics of spatial and temporal data through the visualization effect of thematic data. At the same time, Cassandra distributed database is adopted in this research, which can also store, manage and analyze big data. To a certain extent, it reduces the pressure of front-end map drawing, and has good query analysis efficiency and fast processing ability.</p>

An Innovative Methodology for Big Data Visualization for Telemedicine

2019 ◽  
Vol 15 (1) ◽  
pp. 490-497 ◽  
Author(s):  
Antonino Galletta ◽  
Lorenzo Carnevale ◽  
Alessia Bramanti ◽  
Maria Fazio
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Big Data Visualization ◽  
Innovative Methodology

A Visual Insight Into Tweeting Activity Before and During Natural Disasters

2021 ◽  
Vol 12 (3) ◽  
pp. 19-33
Author(s):  
Shadi Maleki ◽  
Milad Mohammadalizadehkorde
Keyword(s):  
Social Media ◽  
Big Data ◽  
Spatial Distribution ◽  
Emergency Management ◽  
Data Visualization ◽  
High Dimensionality ◽  
High Complexity ◽  
Big Data Visualization ◽  
Disaster Studies ◽  
Insight Into

Big data provided by social media has been increasingly used in various fields of research including disaster studies and emergency management. Effective data visualization plays a central role in generating meaningful insight from big data. However, big data visualization has been a challenge due to the high complexity and high dimensionality of it. The purpose of this study is to examine how the number and spatial distribution of tweets changed on the day Hurricane Harvey made landfall near Houston, Texas. For this purpose, this study analyzed the change in tweeting activity between the Friday of Hurricane Harvey and a typical Friday before the event.

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