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To collect the meteorological data dispersed in various industries, fields and disciplines in a comprehensive and real-time way, and meet the needs of scientific research departments for data, an efficient directional crawler was developed based on Google’s full-Stack technology called MEAN (MongoDB + Express +AngularJS + Node.js) Stack and an fast flex Javascript Document Object Model module called CheerIO, the functions such as fast-gathering weather information, information analysis and processing by data storage, query, automatic mapping, statistical analysis, forecasting of GIS were realized. An application system deployed on Alicloud server which can real-timely update and forecast meteorological data was created, and it can also provide practical functions of massive data storage, convenient search and query. An efficient and practical web application system was built, which not only provided effective solutions for scattered online data collection but show people date intuitively by using HTML5 data visualizing technology. In actual project, it offered a great number of data support and example to the weather-related fields, such as forestry and preventive medicine. GIS data visualization is a constantly evolving concept, whose borders are expanding fast. At the age of the internet, especially in the globalization of information, the long-term value of data has been gained more and more recognition and affirmation from small companies to national political decision-making. It should be recognized what really it is and how it can help us.