Open Access

ARTICLE

A Survey of Time Series Data Visualization Methods

Wangdong Jiang¹, Jie Wu^1,*, Guang Sun^1,2, Yuxin Ouyang³, Jing Li³, Shuang Zhou²

1 School of Information Management and Technology, Hunan University of Finance and Economics, Changsha, 410000, China
2 The University of Alabama, Tuscaloosa, Alabama, USA
3 Housheng School of International Education, Hunan University of Finance and Economics, Changsha, 410000, China

* Corresponding Author: Jie Wu. Email:

Journal of Quantum Computing 2020, 2(2), 105-117. https://doi.org/10.32604/jqc.2020.07242

Received 01 April 2020; Accepted 06 July 2020; Issue published 19 October 2020

Abstract

In the era of big data, the general public is more likely to access big data, but they wouldn’t like to analyze the data. Therefore, the traditional data visualization with certain professionalism is not easy to be accepted by the general public living in the fast pace. Under this background, a new general visualization method for dynamic time series data emerges as the times require. Time series data visualization organizes abstract and hard-to-understand data into a form that is easily understood by the public. This method integrates data visualization into short videos, which is more in line with the way people get information in modern fast-paced lifestyles. The modular approach also facilitates public participation in production. This paper summarizes the dynamic visualization methods of time series data ranking, studies the relevant literature, shows its value and existing problems, and gives corresponding suggestions and future research prospects.

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Keywords

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