Project description

Sep 21, 2017 marked the start of a new era for China’s high-speed rail network. China’s newest bullet train, the Fuxing, traveled between Beijing and Shanghai at the speed of 350 kilometers per hour — the world’s highest operating speed.
Since 1949, the railway system in China has seen tremendous speed increases. Trains, as one of the most popular forms of transportation in China, has drawn Chinese cities closer ever since. The distribution of railway lines in different speed levels greatly affected the accessibility of cities and regions. If we use the travel time to measure the "distances" between cities, it would look quite differently from the real distance map.
The project was a collaboration between The Paper and its English-language sister publication Sixth Tone. We collected data from train timetables in years that major schedule changes happened. We tried to visualize the rapid change over years, and also show the unbalanced advances between different regions of the country.
We found out that, over 68 years, the speed increase of the railway system shrunk the travel time up to 1/10 of its original time in some areas. While the eastern and middle regions benefited the most from upgrades of railway systems, the northeastern part lagged behind. For example, In 1949, Shenyang, a city in northeastern region, which is about 600km away from Beijing, the fastest train from Shenyang to Beijing took 21 hours. And Zhengzhou, a middle region city, which is about same distance from Beijing, took 31 hours to get to Beijing. In 2017, the fastest train from Beijing to Zhengzhou only needs two and a half hours, while it would take four hours to travel to Shenyang in train.

What makes this project innovative?

1) The project collected non-structural data and transform it into structured data.
2) To make the changes more easy to understand, the project chose time as the key variable to look at, and also consider it as the emphasis of visualization.
3) To visualize the data, the team used Processing to code all the data in a short amount of time, and present the final product as GIF, which was found to be easy to share and look at.
4) The team shared the raw data in Github after publication, so that it spared efforts for other practitioners in the data community.

What was the impact of your project? How did you measure it?

The project was published in both English and Chinese within 24 hours. It got more than 100,000 views and hundreds of comments, and the visualization itself got mentioned in many comments.

Source and methodology

1) The data was collected by hand from “National Train Timetable of China” (1959-2016) and “Train Timetable, Vol. 4” (Nov. 15, 1949).
2) We chose railway lines between the capitol city Beijing, which is also the No. 1 traffic hub in the country. There are often multiple trains that travel between Beijing and these cities. We chose the fastest direct train if possible. If not, the fastest indirect way.
3) The time range is clear from the very beginning, 1949 when P.R.China was founded to now. Then we tried to find out the years when changes happened. The six large-scale speedups were included for sure, and these years are 1997, 1998, 2000, 2001, 2004 and 2007. Then it was 2012, the year after the speed limit 300km/h. 2016 was chosen as a comparison to what happened after this time's speedup. As for years before 1997, we used ten years as an interval and tried to get 1987, 1977, 1967, and 1957. And because we couldn't find the schedule book for 1957, we used 1959 as an alternative.
4) "raw data" contains the departing times and arriving times, as well as the exact sources. The "note" column is for cities that were not directly connected to Beijing, either unconnected completely, or for some cities, at least one transfer is needed.

Technologies Used

Processing, Illustrator, After Effects

Project members

Chang Liu/ Sixth Tone, Zhaoying Qin / The Paper


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