Open Access

ARTICLE

Design of a Web Crawler for Water Quality Monitoring Data and Data Visualization

Ziwen Yu¹, Jianjun Zhang^1,*, Wenwu Tan¹, Ziyi Xiong¹, Peilun Li¹, Liangqing Meng², Haijun Lin¹, Guang Sun³, Peng Guo⁴

1 College of Engineering and Design, Hunan Normal University, Changsha, 410081, China
2 LIHERO Technology (Hunan) Co., Ltd., Changsha, 410205, China
3 Big Data Institute, Hunan University of Finance and Economics, Changsha, 410205, China
4 University Malaysia Sabah, Sabah, 88400, Malaysia

* Corresponding Author: Jianjun Zhang. Email:

Journal on Big Data 2022, 4(2), 135-143. https://doi.org/10.32604/jbd.2022.031024

Received 08 April 2022; Accepted 14 June 2022; Issue published 31 October 2022

Abstract

Many countries are paying more and more attention to the protection of water resources at present, and how to protect water resources has received extensive attention from society. Water quality monitoring is the key work to water resources protection. How to efficiently collect and analyze water quality monitoring data is an important aspect of water resources protection. In this paper, python programming tools and regular expressions were used to design a web crawler for the acquisition of water quality monitoring data from Global Freshwater Quality Database (GEMStat) sites, and the multi-thread parallelism was added to improve the efficiency in the process of downloading and parsing. In order to analyze and process the crawled water quality data, Pandas and Pyecharts are used to visualize the water quality data to show the intrinsic correlation and spatiotemporal relationship of the data.

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Keywords

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