Amidst Singapore’s transformation into a Smart Nation, we speak to data visualiser Yin Shanyang and data scientist Alvin Chua to learn how data can be meaningfully used to better different facets of life in the city. In part 1, Shanyang and Alvin shared more about their projects.
DREAMS OF A DATA-DRIVEN CITY
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| Alvin Chua, Data Scientist |
Yin Shanyang, Data Visualiser |
Another danger is seeing data as a neutral measure just because it is made up of numbers. Alvin points to the example of FixMyStreet, an online app in Brussels that allows residents to photograph and report defects in their neighbourhood for their municipal government to address. While this service helped bridge the gap between the people and the government, most of its users were actually the middle and upper-income residents. But the municipality used the app to replace a phone service they had, cutting off economically disadvantaged residents who do not have ready access to the Internet. As many residents are also immigrants who can speak but not read French, they do not understand how to file reports on the new online service too. “No data is perfect, data is always some abstraction of reality and from that you have bias towards something,” he says. “Simply making decisions from one source of data is not enough, especially when you’re not certain of the bias.”
Although FixMyStreet improved communication between people and government in Brussels, Alvin’s analysis of the geographic spread of reports by residents demonstrated how the service was actually underused by the city’s underprivileged districts.
By analysing a year’s worth of train schedules of the Belgian railway, Alvin was able to show how Flemish provinces and cities are connected. Brussels was clearly where most Belgians travelled to wherever they were, but there were also interconnections between Leuven, Gent and Antwerp.
That said, the duo remain eager to explore how else data can improve their lives in Singapore and have a few ideas up their sleeves. Shanyang is keen to plot an isochrone map of the city, a diagram that uses lines to connect areas in the city that have similar travel times via public transport or car. “Now that I’m looking for an apartment, I’m looking at which locale is good for me because I only have a few frequently visited venues in Singapore,” he says. Alvin’s dream project is also about enhancing the experience of getting around sunny Singapore: Imagine walking around the city with cloud above you always. By tapping into data on cloud coverage and the position of the sun from Singapore’s weather radar, and figuring out the heights of buildings here, Alvin can create a service that computes pathways around the city with the most shade. “That calculation should change every 5 minutes… and you could choose paths that are air-conditioned or not,” he says. “It’s data science made cool.”