For CodeAcross NYC 2015, people will break off into teams and work on one of the four problem areas.
Improving real time notification data and tools - Since the launch of the mobile era, we are accustomed to information coming to us. At CodeAcross, we will focus on enhancing datasets and building tools that bring information into the palm of our hands.
– Example: people will work to extend CityGram.nyc by adding datasets and improving its user interface.
Maps and visualizations - One simple way to understand data is to see it mapped or visualized. At CodeAcross, we will take on a number of datasets and improve their mapping ability. Additionally, we are challenging attendants to make data gorgeous and simple to read.
– Example: our friends at MapTime NYC want to make a new transit map layer that separates out each bus, train, and ferry line.
– Example: a number of people have scraped together NYPD’s compstat data and want to visualize it.
Publicly accessible machine readable data - To help the City breath life into its data, we are challenging the community to take existing reports, PDFs, and databases and machine them into structured data.
– Example: Last year, the Mayor signed a law that mandates the City Record to be published as a machine readable file. This team will write parsers and scrape the data into an idealized format.
Open data science using OSEMN - As the city’s datasets have blossomed, we challenge the community to use their analytical skills and make sense of the city’s data.
– Example: Due to the success of NYC 311’s apps and call center, the Department of Transportation’s pothole requests has ballooned. What type of data science can be applied to help streamline this operation.