This work is written in both Chinese and English.
Taking the No. 5633 train passing through Xide County, Sichuan Province as the starting point, we independently excavated and sorted out the geographical coordinate data of poverty alleviation trains and the poverty alleviation counties in different years for visual processing.
It shows that as a means of public transport for the people in poverty-stricken areas, slow trains have the basic characteristics of “low-speed, multiple stations, long dwell time, cheap ticket and quality service”.
The shortened version of this work, titled “情系人民的“公益慢火车””, was first released on the Xinhuanet National Channel, with more than 1 million hits in a single day.
We are based on the self-created platform, combined with the open platforms called “dychart” and “Map-lab”.
The geographical location map, information map, rose map, jade map, water wave map and other charts in the work provide a targeted multi-visual presentation of geographical location data, classification data and continuous data.
What was the hardest part of this project?
The data types of this work include geographical location data, continuous data, discrete data and some unstructured data.
The team independently excavated and sorted out the geographical coordinate data of the poverty alleviation train and the personalized information of poverty alleviation counties in different years, and superimposed these data.
China’s high-speed railway technology is world-renowned, with the fastest speeds exceeding 600 kilometres per hour, impressing the world with the “China Speed”. While China is developing so “fast”, it is also willing to “slow down” and wait for those who are temporarily behind, and the “slow train” is a special token of China’s solicitude for the poor regions.We think it is necessary to let everyone know.
What can others learn from this project?
I think other people can see from this work how we can point to the surface and use data to materialize abstract things.