Bus Speeds measure how quickly buses travel along their routes. This dataset covers data from 2020 and on. For data between 2015 and 2019, use dataset https://data.ny.gov/Transportation/MTA-Bus-Speeds-2015-2019/cudb-vcni.

The percent of the time that elevators and escalators are operational systemwide.

Service Delivered measures the percentage of scheduled trains that are actually provided during peak hours on weekdays (7 AM to 10 AM and 4 PM to 7 PM) and weekends (10 AM to 6 PM) for a given month. This dataset covers data from 2020 and on. For data between 2015 and 2019, use dataset https://data.ny.gov/Transportation/MTA-Subway-Service-Delivered-2015-2019/32ch-sei3.

The percent of the time that elevators and escalators are operational systemwide.

Service Reliability metrics evaluate MNR’s ability to deliver timely and effective service to its customers. Included in these metrics are: Service Type, Major Incidents, 4m to 6m Train Delays, Average Delay per Late Train, Number of Trains Over 15 Minutes Late, Number of Short Trains.

Ride Time measures customer trip duration. Actual vs. Scheduled presents travel time variance, Average Travel Time presents the average actual trip duration, and Max Ride Time by trip distance category.

Max Ride Time Performance presents the percentage of trips performed with Access-A-Ride’s established max ride time standards between 2018 and 2023. This dataset is now retired as this metric can be calculated from MTA NYCT Paratransit Ride Time (https://data.ny.gov/Transportation/MTA-NYCT-Paratransit-Ride-Time-Beginning-2017/wtm4-vjm7/).

This indicator shows the number of subway and bus journeys made each month by passengers using Reduced-Fare MetroCards between 2018 and 2023. This dataset is now retired, with data on reduced-fare usage of the transit system available in the hourly bus (https://data.ny.gov/Transportation/MTA-Bus-Hourly-Ridership-Beginning-February-2022/kv7t-n8in/) and subway (https://data.ny.gov/Transportation/MTA-Subway-Hourly-Ridership-Beginning-February-202/wujg-7c2s/) ridership datasets.

Drop-off On-Time Performance (OTP) measures the quality of provider service, comparing actual to customer-requested drop-off time for trips scheduled with an appointment time. Trips are considered on-time if they are no more than 30 minutes early, and no later than the appointment time.

On-Time Performance (OTP) determines how frequently a commuter train arrives at its final destination within 5 minutes and 59 seconds of its scheduled time.

Terminal On-Time Performance measures the percentage of trains arriving at their destination terminals as scheduled. This dataset covers data from 2020 and on. For data between 2015 and 2019, use dataset https://data.ny.gov/Transportation/MTA-Subway-Terminal-On-Time-Performance-2015-2019/f6rf-2a3t.

Pickup On-Time Performance (OTP) measures the quality of provider service, comparing actual to promised pickup time. Trips are considered on-time if they arrive no more than 20 minutes after the promised time. This dataset also includes trips that arrive within 15 and 30 minutes of the promised time.

Service Delivered measures the percentage of scheduled trains that are actually provided during peak hours on weekdays (7 AM to 10 AM and 4 PM to 7 PM) and weekends (10 AM to 6 PM) for a given month. This dataset covers data between 2015 and 2019. For data from 2020 on, use dataset https://data.ny.gov/Transportation/MTA-Subway-Service-Delivered-Beginning-2020/bg59-42xi.

Mean Distance Between Failures represents the number of miles a rail car travels before a mechanical failure makes the train arrive at its final destination more than 5 minutes and 59 seconds later than scheduled. This measures the reliability of equipment in revenue service.

This metric tracks the monthly dollar amount of chargebacks and the percentage of transactions that have been disputed with the customer receiving a refund.

Mean Distance Between Failures reports how frequently bus mechanical problems cause delays.

On-Time Performance (OTP) determines how frequently a commuter train arrives at its final destination within 5 minutes and 59 seconds of its scheduled time.

Wait Assessment measures how regularly trains are spaced during peak hours at selected timepoints on each line.

Terminal On-Time Performance measures the percentage of trains arriving at their destination terminals as scheduled. This dataset covers data between 2015 and 2019. For data from 2020 on, use dataset https://data.ny.gov/Transportation/MTA-Subway-Terminal-On-Time-Performance-Beginning-/vtvh-gimj.

Mean Distance Between Failures represents the number of miles a rail car travels before a mechanical failure makes the train arrive at its final destination more than 5 minutes and 59 seconds later than scheduled. This measures the reliability of equipment in revenue service.

This dataset provides data on how fast buses are traveling between pairs of subsequent timepoints (the major stops on a bus route) for every bus route in the system. It will provide the average speed in miles per hour between pairs of timepoints, the average travel time in minutes, the road distance in miles, and the number of bus trips for each bus route aggregated by month, day of the week, and hour of day. It also provides the type of bus trip (Local, Limited, SBS, Express, School), the borough of the bus route, the names of the timepoints, their coordinates, and the stop sequence order of the first two timepoints in a pair.

Mean Distance Between Service Interruptions is the average distance traveled by a bus between all delays and/or inconveniences to customers.

The Utility Energy Registry (UER) is a database platform that provides streamlined public access to aggregated community-scale utility-reported energy data. The UER is intended to promote and facilitate community-based energy planning and energy use awareness and engagement. On April 19, 2018, the New York State Public Service Commission (PSC) issued the Order Adopting the Utility Energy Registry under regulatory CASE 17-M-0315. The order requires utilities under its regulation to develop and report community energy use data to the UER.

This dataset includes electricity and natural gas usage data reported at the county level level collected under a data protocol in effect between 2016 and 2021. Other UER datasets include energy use data reported at the city, town, and village, and ZIP code level. Data collected after 2021 were collected according to a modified protocol. Those data may be found at https://data.ny.gov/Energy-Environment/Utility-Energy-Registry-Monthly-County-Energy-Use-/46pe-aat9.

Data in the UER can be used for several important purposes such as planning community energy programs, developing community greenhouse gas emissions inventories, and relating how certain energy projects and policies may affect a particular community. It is important to note that the data are subject to privacy screening and fields that fail the privacy screen are withheld.

The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and accelerate economic growth. reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit nyserda.ny.gov or follow us on X, Facebook, YouTube, or Instagram.