Publication Type : Conference Proceedings
Thematic Areas : Amrita Center for Cybersecurity Systems and Networks
Publisher : Procedia Computer Science
Source : Procedia Computer Science, Volume 58, p.371 - 379 (2015)
Url : http://www.sciencedirect.com/science/article/pii/S187705091502147X
Keywords : Apriori chart, Bar chart, Configuration, Data visualization, Line chart, Scatter chart
Campus : Amritapuri
School : Centre for Cybersecurity Systems and Networks, Department of Computer Science and Engineering, School of Engineering
Center : Cyber Security
Department : Computer Science, cyber Security
Year : 2015
Abstract : Data Visualization is the representation of data in a graphical or pictorial format. For the effective communication of data for a user proper visualization is necessary. Visualization is essential in order for the user to understand the data in an easy way. Visualization of data is done through various charts that represent the attributes of the data. For web applications, there are many open source JavaScript libraries that work on HTML5 (using SVG or CANVAS). But the drawback of these libraries is that they don’t provide for much flexibility with respect to configuration. They also don’t provide generalization of charts. Also many data mining algorithms are not supported by these libraries for data visualization. This paper has illustrated in building JavaScript charting libraries that would ensure proper visualization of data which is flexible for user customization. The charting library supports different types of charts varying from scatter chart to line chart to bar chart that are used for various algorithms. The libraries are built based on Object-Oriented JavaScript concept to support web applications that run either on the internet or intranet, so that extending the same in the future is also possible.
Cite this Research Publication : R. Meenakshi, Jayalekshmi, G., Hariram, S., Shiju Sathyadevan, and Thushara M. G., “Visualization with Charting Library Based on SVG for Amrita Dynamic Dashboard”, Procedia Computer Science, vol. 58. pp. 371 - 379, 2015.