Until March 2020, the MTA publicized solicitations on its website for capital projects in its Eye on the Future newsletters. Each report contained information for prospective contractors, engineers, architects and vendors about contracts for professional services, construction, and equipment procurement capital projects that are expected to be advertised for bids during specific time period by the Metropolitan Transportation Authority’s operating agencies.

This dataset includes the RGB Hex code and CMYK values for the colors used by the MTA for its various services, including the New York City Subway, the Staten Island Railway, the Long Island Rail Road, Metro-North Railroad, and Bridges & Tunnels, and for the MTA logo itself.

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).

This dataset provides an estimate of subway travel patterns based on scaled-up OMNY and MetroCard return swipe data. It provides estimated passenger volumes for all populated origin-destination (O-D) pairs aggregated by month, day of the week, and hour of day. It also provides the name, ID, and approximate latitude and longitude of the origin and destination subway complexes.

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).

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).

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).

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.

The 2025-2044 20-Year Needs Assessment outlines capital work the MTA needs to do over the next two decades to keep the region moving. The MTA developed a three-part plan to secure the foundation of the system and ensure another 100 years of service by reconstructing, renewing, and modernizing the system. This dataset includes data on all revenue fleets, except for cars and locomotives used for Metro-North service owned by New Jersey Transit and the Connecticut Department of Transportation that are used in pooled service. The dataset, for each fleet asset, includes the fleet type, its number of units, its useful life, and the years its cars were first and last accepted.

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).

Major felonies reflect the count of arrests made in relation to seven major felony offenses within the MTA system. These offenses are classified as murder, rape, robbery, felony assault, burglary, grand larceny, and grand larceny auto.

Additional Platform Time (APT) is the estimated average extra time that customers spend waiting on the platform for a train, compared with their scheduled wait time.

Additional Train Time (ATT) is the estimated average extra time that customers spend onboard a train, compared to the time they would have spent onboard a train if trains were running according to schedule.

Additional Journey Time (AJT) is the estimated average extra time that customers spend on their journey, compared with the scheduled time. It is the sum of the additional time spent waiting on platforms (APT) and the additional time spent onboard a train (ATT).

Journey Time is the average total time a customer spends on their journey waiting for and riding a specific train line.

Customer Journey Time Performance (CJTP) is the estimated percentage of rider trips that are completed within 5 minutes of their scheduled time.

These measures are estimated for each individual train a customer uses in their journey, also known as an unlinked trip, not all trains in their journey combined.

This dataset covers data from 2020 and on. For data between 2015 and 2019, use dataset https://data.ny.gov/Transportation/MTA-Subway-Customer-Journey-Focused-Metrics-2015-2/r7qk-6tcy.

Additional Platform Time (APT) is the estimated average extra time that customers spend waiting on the platform for a train, compared with their scheduled wait time.

Additional Train Time (ATT) is the estimated average extra time that customers spend onboard a train, compared to the time they would have spent onboard a train if trains were running according to schedule.

Additional Journey Time (AJT) is the estimated average extra time that customers spend on their journey, compared with the scheduled time. It is the sum of the additional time spent waiting on platforms (APT) and the additional time spent onboard a train (ATT).

Journey Time is the average total time a customer spends on their journey waiting for and riding a specific train line.

Customer Journey Time Performance (CJTP) is the estimated percentage of rider trips that are completed within 5 minutes of their scheduled time.

These measures are estimated for each individual train a customer uses in their journey, also known as an unlinked trip, not all trains in their journey combined.

This dataset covers data between 2015 and 2019. For data from 2020 on, use dataset https://data.ny.gov/Transportation/MTA-Subway-Customer-Journey-Focused-Metrics-Beginn/4apg-4kt9.

This 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, Bridges and Tunnels and Staten Island Railway on a monthly basis.

The 2025-2044 20-Year Needs Assessment Comparative Evaluation is a framework which assesses the costs and benefits of potential expansions and enhancements. All potential projects are evaluated using a consistent set of models, tools, and criteria including ridership, time savings, network resilience and sustainability, capacity, equity, network leverage, geographic distribution, and cost. The most promising projects may be advanced for further study and possible inclusion in future capital plans. To view the full comparative evaluation and further details on the methodology, visit future.mta.info.

This dataset provides a detailed breakout of the dedicated taxes and subsidies received from the State of New York and businesses, individuals and localities in the MTA region. This data is obtained from the MTA’s annual budgeting process and is available for each month of a fiscal year, on both an accrual (represented as NREIMB) and a cash basis. Data is categorized by budget scenario, Agency, Financial Plan Year, and subcategories for types of subsidies.

This dataset provides an estimate of subway travel patterns based on scaled-up OMNY and MetroCard return swipe data. It provides estimated passenger volumes for all populated origin-destination (O-D) pairs aggregated by month, day of the week, and hour of day. It also provides the name, ID, and approximate latitude and longitude of the origin and destination subway complexes.

The 2025-2044 20-Year Needs Assessment is a broad, comprehensive blueprint that outlines the MTA region's transportation capital needs for the next generation. It provides an extensive, long-term view based upon rigorous data analysis across all the MTA agencies. The MTA developed a three-part plan to for the next 20 years to achieve the transit network New Yorkers deserve. It is based on three fundamental ideas: rebuild the foundation of the system to ensure its survival, improve our network to meet 21st century needs, and expand to support future growth. This dataset includes data on the conditions of most assets in the MTA system.

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 reflects the monthly number of employee-reported incidents of workplace violence, as defined by New York State Labor Law Section 27-B, against on-duty MTA employees. This dataset divides workplace violence incidents into groupings according to New York State Penal Law Related Offenses. The same data is available in the MTA Workplace Violence Labor Law Incidents dataset, which divides the data as reported pursuant to New York State Labor Law Section 27-B.

Ridership projections for the Metropolitan Transportation Authority, developed by McKinsey & Company, to help management assess the financial impact of the COVID-19 pandemic on MTA operations.

Service alerts in the MTA system are generated to inform passengers of both scheduled and unscheduled events that affect the transit network. These events can range from planned maintenance and construction activities to unexpected incidents such as accidents, track maintenance or planned work and more. The process of creating alerts involves the continuous monitoring of the transit system, including station locations, track statuses, and external factors that might impact service. When a potential disruption is identified, an alert is generated to provide passengers with timely and accurate information about how their travel might be affected.

This dataset provides actual and projected monthly headcount data, obtained from the MTA’s annual budgeting process, for each month of a fiscal year, categorized by budget scenario, Agency, function, occupational group, and segmented by non-reimbursable (NREIMB) or reimbursable (REIMB) positions.

The dataset provides financial information on total positions in Function/Occupational Group related to different MTA Agencies budgetary estimates and actuals. For a more comprehensive view of this data, please use MTA Headcount at data.ny.gov/d/ui26-n8p4.