Interface for Querying and Data Mining for NYC Yellow and Green Taxi Trip Data

Big data analysis is often seen as a complex process for processing large sets of data to uncover hidden information and patterns. This information can then be used by different groups of people to make decisions, to run their businesses and processes more efficiently. Just as important as the analysis technique used, so is the way we present that information. The purpose of our research is to investigate how large data generated by day to day activities in an urban environment can be processed to support analysis and visualization is support of public awareness and decision making. Specifically, New York City's large and regularly updated open data sets focused on taxi rides provide an excellent opportunity for the development of user-friendly web based interface for visualization and querying. Faced with an ever increasing (in both size and diversity) access to open data sets interfaces such as the one we designed nd developed will become valuable tools for public and specialized access (such as journalistic investigation). The application was built using state of the art technologies and provides a visualization of trends in ridership data from the New York City Taxi and Limousine Commission.