A dataset listing all subway and Staten Island Railway stations, with information on their locations, Station Master Reference Number (MRN), Complex MRN, GTFS Stop ID, the services that stop there, the type of structure the station is on or in, whether the station is in Manhattan’s Central Business District (CBD), and their ADA-accessibility status.

A list of datasets that MTA currently shares and plans to share on data.ny.gov.

This dataset provides insights into safety-related incidents and indicators within New York City Transit (NYCT). NYCT is responsible for overseeing the safety of subway and bus operations, aiming to ensure the well-being of both employees and passengers. This dataset offers information about various safety aspects, including incidents, collisions, and accident prevention indicators within the NYCT system.

This dataset provides systemwide ridership and traffic estimates for subways (including the Staten Island Railway), NYCT bus, MTA Bus, Long Island Rail Road, Metro-North Railroad, Access-A-Ride, Bridges and Tunnels and Staten Island Railway on a monthly basis.

*** DISCLAIMER - This web page is a public resource of general information. The Maryland Mass Transit Administration (MTA) makes no warranty, representation, or guarantee as to the content, sequence, accuracy, timeliness, or completeness of any of the spatial data or database information provided herein. MTA and partner state, local, and other agencies shall assume no liability for errors, omissions, or inaccuracies in the information provided regardless of how caused; or any decision made or action taken or not taken by any person relying on any information or data furnished within. ***

This dataset assesses rail station potential for different forms of transit oriented development (TOD). A key driver of increased transit ridership in Maryland, TOD capitalizes on existing rapid transit infrastructure. The online tool focuses on the MTA’s existing MARC Commuter Rail, Metro Subway, and Central Light Rail lines and includes information specific to each station.

The goal of this dataset is to give MTA planning staff, developers, local governments, and transit riders a picture of how each MTA rail station could attract TOD investment. In order to make this assessment, MTA staff gathered data on characteristics that are likely to influence TOD potential. The station-specific data is organized into 6 different categories referring to transit activity; station facilities; parking provision and utilization; bicycle and pedestrian access; and local zoning and land availability around each station.

As a publicly shared resource, this dataset can be used by local communities to identify and prioritize area improvements in coordination with the MTA that can help attract investment around rail stations.

You can view an interactive version of this dataset at geodata.md.gov/tod.

** Ridership is calculated the following ways: Metro Rail ridership is based on Metro gate exit counts. Light Rail ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. MARC ridership is calculated using two (2) independent methods: Monthly Line level ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. This method of ridership calculation is used by the MTA for official reporting purposes to State level and Federal level reporting. Station level ridership is estimated by using person counts completed by the third party vendor. This method of calculation has not been verified by the FTA for statistical reporting and is used for scheduling purposes only. However, because of the granularity of detail, this information is useful for TOD applications. *Please note that the monthly level ridership and the station level ridership are calculated using two (2) independent methods that are not interchangeable and should not be compared for analysis purposes.

This data contains schedules and associated data for NYCT Subway, NYCT Bus, MTA Bus, LIRR, and Metro-North in GTFS Static format: --Station / bus stop locations --Train lines / bus routes --Schedule information, including holiday services --Schedules for upcoming planned work (LIRR and MNR only)

The Green Book Online is a fully searchable database which gives New Yorkers the opportunity to search for the agencies, offices, boards and commissions that keep our City running. It includes listings for New York City, County, Courts, and New York State government offices.

This deprecated dataset provides systemwide ridership and traffic estimates for subways (including the Staten Island Railway), buses, Long Island Rail Road, Metro-North Railroad, Access-A-Ride, and Bridges and Tunnels, beginning 3/1/2020, and provides a percentage comparison against a comparable pre-pandemic date.

Next-day estimates for daily ridership, without the pre-pandemic comparison, are now provided at https://data.ny.gov/d/sayj-mze2

This retired dataset contains information on entry/exit values for individual control areas and is posted purely for archival purposes. More detailed subway ridership data is now supported through the Subway hourly dataset (https://data.ny.gov/Transportation/MTA-Subway-Hourly-Ridership-Beginning-February-202/wujg-7c2s).

Maryland Department of Transportation's Maryland Transit Administration Fall 2024 Bus Routes including CityLink, LocalLink, QuickLink, Express BusLink and Commuter Bus services. The bus routes service geometry has been updated and now matches the One Maryland One Centerline (OMOC) roadway network. For service change details please see: https://www.mta.maryland.gov/servicechanges/fall2024

This is a MD iMAP hosted service layer. Find more information at https://imap.maryland.gov.Feature Service Layer Link:https://mdgeodata.md.gov/imap/rest/services/Transportation/MD_Transit/FeatureServer/10

Maryland Department of Transportation's Maryland Transit Administration Fall 2024 Bus Stops including CityLink, LocalLink, QuickLink, Express BusLink, and Commuter Bus. Ridership data is based on Automatic Passenger Counting (APC) system average daily weekday bus stop ridership (boarding, alighting, and total) from the Summer 2024 period and does not exclude outliers. For service change details please seehttps://www.mta.maryland.gov/servicechanges/fall2024This is a MD iMAP hosted service layer. Find more information athttps://imap.maryland.gov.Feature Service Layer Link:https://mdgeodata.md.gov/imap/rest/services/Transportation/MD_Transit/FeatureServer/9

The dataset consists of annual procurement contracts data reported by the Metropolitan Transportation Authority to the Authorities Budget Office via the Public Authorities Reporting Information System (PARIS).

A. Summary Current inventory of transit rail signals maintained by Muni MOW. B. METHODOLOGY Manual edits to Access database export. C. UPDATE FREQUENCY Updated as changes are made through SRC and Rail CCB. D. OTHER CRITICAL INFO n/a E. ATTRIBUTES CNN: The intersection associated with the signal; STREET_1, _2, _3, _4: The cross streets nearest to the signal; LOC: Whether the signal is at an intersection or at a midblock _location; LAT: Latitude in WGS-84; LON: Longitude in WGS-84; SIGNAL_TYPE: The type of signal (i.e. whether it shows ROW or a switch position); SIGNAL_ID: The ID of the signal per Muni records; LINE: Which lines use the signal, or if the signal is on a non-revenue track segment; DIRECTION: If used for a line, whether it is the inbound or outbound track; NO_ASPECTS: The number of aspects that comprise the signal; ASPECT_1, _2, _3, _4, _5: A description of the aspects from top to bottom; SIGNAL_HEAD_SIZE: The diameter of the signal head; SRC_NO: The number for the latest SRC Work Order that concerns this signal; DATE_SUBMITTED: The date that the SRC Work Order was submitted to the shop; DATE_COMPLETED: The latest date that work was completed on this signal;Date_Last: Date of last edit

Italy Borsa Italiana: Listed Companies: MTA data was reported at 326.000 Unit in 2017. This records an increase from the previous number of 310.000 Unit for 2016. Italy Borsa Italiana: Listed Companies: MTA data is updated yearly, averaging 229.000 Unit from Dec 1975 (Median) to 2017, with 43 observations. The data reached an all-time high of 326.000 Unit in 2017 and a record low of 141.000 Unit in 1981. Italy Borsa Italiana: Listed Companies: MTA data remains active status in CEIC and is reported by Italian Stock Exchange. The data is categorized under Global Database’s Italy – Table IT.Z006: Stock Exchange Statistics: Annual.

430 Global export shipment records of Mta plus with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

Italy Number of Listed Companies: MTA International data was reported at 96.000 Unit in Nov 2018. This stayed constant from the previous number of 96.000 Unit for Oct 2018. Italy Number of Listed Companies: MTA International data is updated monthly, averaging 36.000 Unit from Dec 2009 (Median) to Nov 2018, with 105 observations. The data reached an all-time high of 96.000 Unit in Nov 2018 and a record low of 36.000 Unit in Jun 2016. Italy Number of Listed Companies: MTA International data remains active status in CEIC and is reported by Italian Stock Exchange. The data is categorized under Global Database’s Italy – Table IT.Z005: Number of Listed Companies and Shares.

Italy Number of Listed Companies: MTA Foreign data was reported at 2.000 Unit in Oct 2018. This records a decrease from the previous number of 3.000 Unit for Sep 2018. Italy Number of Listed Companies: MTA Foreign data is updated monthly, averaging 5.000 Unit from Dec 2009 (Median) to Oct 2018, with 104 observations. The data reached an all-time high of 5.000 Unit in Nov 2014 and a record low of 2.000 Unit in Oct 2018. Italy Number of Listed Companies: MTA Foreign data remains active status in CEIC and is reported by Italian Stock Exchange. The data is categorized under Global Database’s Italy – Table IT.Z005: Number of Listed Companies and Shares.

Mexico Imports: MTA: Others data was reported at 3.312 USD mn in Feb 2019. This records a decrease from the previous number of 5.449 USD mn for Jan 2019. Mexico Imports: MTA: Others data is updated monthly, averaging 0.985 USD mn from Jan 1993 (Median) to Feb 2019, with 314 observations. The data reached an all-time high of 5.449 USD mn in Jan 2019 and a record low of 0.140 USD mn in Sep 1996. Mexico Imports: MTA: Others data remains active status in CEIC and is reported by Bank of Mexico. The data is categorized under Global Database’s Mexico – Table MX.JA011: Imports: by Commodities.

User personas are a human-centered design tool that help open data program administrators design programs offerings for the full community open data users for maximum reach and impact. User personas help keep real people in mind when designing program offerings and can identify user segments in the open data community that have the potential to use open data to help solve problems. The Metropolitan Transportation Authority (MTA) is excited to share our open data user personas which were designed in collaboration with our existing open data community through multiple stakeholder workshops.

This dataset contains information on customer feedback submitted by riders of the transit system on the MTA’s website. For each piece of feedback provided, it is categorized as a complaint or commendation, and there is information provided for the agency (Buses, Subway, Long Island Rail Road, or Metro-North Railroad), the subject matter, the subject detail, the issue detail, the year, the quarter, and, if applicable, the branch/line/route.