This is a breakdown of every collision in NYC by location and injury. This data is collected because the NYC Council passed Local Law #11 in 2011. This data is manually run every month and reviewed by the TrafficStat Unit before being posted on the NYPD website. Each record represents a collision in NYC by city, borough, precinct and cross street. This data can be used by the public to see how dangerous/safe intersections are in NYC. The information is presented in pdf and excel format to allow the casual user to just view the information in the easy to read pdf format or use the excel files to do a more in-depth analysis.
Yelp allows developers to access rich local data through their Search and Business APIs. Within minutes, developers can retrieve business listing data, star ratings, deals, an image URL, and much more. For questions or comments, contact: email@example.com.
Open NY provides access to hundreds of high-quality New York State government datasets, each with an API endpoint and detailed documentation. From liquor licenses to hospital data, it contains valuable and up-to-date information which you can freely include in your next civic-oriented application. For questions or comments, contact firstname.lastname@example.org
The Foursquare API powers the location layer of the internet, giving developers access to our powerful reverse geocoder and venue database of over 60 million places. We turn latitude and longitude points into real meaning. For questions or comments, contact: email@example.com
The SeatGeek API is the canonical source of data on all live events (from sports to concert to theater and more), both within New York City as well as worldwide.
You can easily retrieve detailed event information with the SeatGeek API--everything from the lat/lon of a venue to the average ticket price for a show. It’s all wrapped up in a clean, well-documented API, with no rate limits and no cost to use.
The Alliance for Downtown New York collects various types of data for Lower Manhattan, particularly the Water Street area. We have residential and commercial building information, retail data, Big Belly trashcans and other streetscape locations (citiBike, StreetCharge, etc.), ferry and subway ridership and much more. Everything you need to raise the StreetIQ of Water Street. For questions and comments, contact firstname.lastname@example.org
You already know that NYTimes.com is an unparalleled source of news and information. But it's a premier source of data, too — why just read the news when you can hack it? The Times APIs allow you to work with rich sets of Times data, including article metadata and abstracts, movie reviews and best-seller lists, and NYTimes.com user comments. For questions or comments, contact: email@example.com
CartoDB wraps any spatial data into an API. Allowing you to query and spatially query data using REST and returning results in JSON and GeoJSON. There is also a Maps API that will let you embed and build maps from data directly into your websites or mobile applications. The platform is scalable, fast, and made to make beautiful maps. For questions or comments, contact: firstname.lastname@example.org.
Mapbox makes it easy to find bars on foursquare, search for hotels on Hipmunk, and organize notes in Evernote. With Mapbox, design and publish maps that tell stories, integrate with apps, and represent brands. For questions or comments, contact: email@example.com
Enigma Public is a public data platform bringing together billions of records across federal, state, local and international sources. Spanning everything from SEC filings, to real estate records, environmental violations, import records, demographic data and much more, Enigma Public provides a single point of access to public data through a web application and data APIs. For questions or comments, contact: firstname.lastname@example.org
The Voting Information Project (VIP) offers cutting edge technology tools to provide voters with access to customized election information to help them navigate the voting process and cast an informed vote. VIP works with election officials across the nation to ensure this information is official and reliable. We answer voters’ basic questions like “Where is my polling place?” “What’s on my ballot?” and “How do I navigate the voting process?”
LinkUp only indexes jobs that are found on corporate career websites. Today, our U.S site lists roughly 1,500,000 jobs from over 40,000 company websites. Since we don't allow jobs to be manually posted to LinkUp, and because of the sources we index (real companies), we have the cleanest and highest quality dataset of jobs on the web - no job scams, lead-gen pollution, or fraudulent postings. For questions or comments, contact: email@example.com
Carpoolworld brings people together for ridesharing, using a pioneering search engine that matches individuals based on their trip origins and destinations, anywhere on the planet. The Carpoolworld API gives developers access to the web site's essential functions to create trips, find matches, and contact potential travel partners. The API is developed using the RESTful style. Responses are formatted in XML. For questions or comments, contact: firstname.lastname@example.org
High resolution land cover data set for New York City. This is the 3ft version of the high-resolution land cover dataset for New York City. Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The minimum mapping unit for the delineation of features was set at 3 square feet. The primary sources used to derive this land cover layer were the 2010 LiDAR and the 2008 4-band orthoimagery. Ancillary data sources included GIS data (city boundary, building footprints, water, parking lots, roads, railroads, railroad structures, ballfields) provided by New York City (all ancillary datasets except railroads); UVM Spatial Analysis Laboratory manually created railroad polygons from manual interpretation of 2008 4-band orthoimagery. The tree canopy class was considered current as of 2010; the remaining land-cover classes were considered current as of 2008. Object-Based Image Analysis (OBIA) techniques were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. More than 35,000 corrections were made to the classification. Overall accuracy was 96%. This dataset was developed as part of the Urban Tree Canopy (UTC) Assessment for New York City. As such, it represents a 'top down' mapping perspective in which tree canopy over hanging other features is assigned to the tree canopy class. At the time of its creation this dataset represents the most detailed and accurate land cover dataset for the area. This project was funded by National Urban and Community Forestry Advisory Council (NUCFAC) and the National Science Fundation (NSF), although it is not specifically endorsed by either agency. The methods used were developed by the University of Vermont Spatial Analysis Laboratory, in collaboration with the New York City Urban Field Station, with funding from the USDA Forest Service.
Twilio provides a software and cloud-based communications platform that enables developers and businesses to build communications solutions that meet their specific needs. Whether integrating voice, messaging or VoIP capabilities into a web or mobile app or building a complete call center, Twilio removes traditional obstacles to creating effective communications experiences. For questions or comments, contact: email@example.com