Ben Wellington: How we found the worst place to park in New York City — using big data

Ben Wellington is a data scientist. He has worked in big data analyzing for many years. In this talk, Ben demonstrated how he used data collected from New York city government and used them to make positive changes. In fact, Mayor Bloomberg fully recognized the limitation of one city government can do. Therefore, he decided to make sure all New Yorkers have access to the data which used to develop policy. By that means, people can utilize this data to improve our lives. For example, Ben used the data from the transportation department to analyze the average taxi speed in New York City. He wanted to know when is the rush hour begins and ends. The result showed that there is no rush hour in New York City. From 8 am to 6 pm, the average taxi speed is only about 11.5 MPH.  The only exception is from midnight to 5:18 am in the next morning.  Another important discovery is how Ben found the worst space to park in New York City. He used big data to analyze the parking tickets for drivers parking their car near a fire hydrant. He found two most ticketed parking spots and they brought about 55,000 dollars a year to the city government. Ben was curious about this phenomenon so he decided to find out why. He went into the field to discover there were actually misleading signs around the hydrants. So he wrote to the city government and informed them those signs were causing many drivers to be unfairly ticketed. For five years the city government ticked drivers in those parking spots, but one citizen found something, within a few weeks the problem was fixed. That is why Ben believed data must be made accessible to the general public, he said "We can empower our citizens to be better partners for government".  Beside this, Ben also advocated the idea of "Open data" in this talk. While collecting the data for parking lot issue, he found out that raw data provided by government are not in easy to handle format. That means people need to do a lot of data pre-processing before any analysis can be started. Ben argued that government should start normalizing the data format, such as an open data standard. The state, federal government and other countries will follow, then people can write a single program and parse the data without any other obstacles. People can focus on the question itself.