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 city, town, and village level collected under a data protocol in effect between 2016 and 2021. Other UER datasets include energy use data reported at the county 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-Community-Energy-U/4txm-py4p.

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.

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.

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

The number of reportable job-related incidents that result in the inability of an employee to perform full job duties for at least one working day beyond the day of the incident, as well as a breakdown of the number of Employees and Lost Time Accident Rates.

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.

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.

The Utility Energy Registry (UER) is a database platform that provides streamlined public access to aggregated community-scale 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, and updated the protocol in a modification order on August 12, 2021. The order requires utilities and CCA administrators 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 city, town, and village level. Other UER datasets include energy use data reported at the county and ZIP code level.

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 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.

The Utility Energy Registry (UER) is a database platform that provides streamlined public access to aggregated community-scale 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 and CCA administrators under its regulation to develop and report community energy use data to the UER.

This dataset includes electricity and natural gas usage data reported by utilities at the county level. Other UER datasets include energy use data reported at the city, town, and village, and ZIP code level.

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 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.

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

Wait Assessment measures how evenly buses are spaced. This dataset covers data from 2020 and on. For data between 2015 and 2019, use dataset https://data.ny.gov/Transportation/MTA-Bus-Wait-Assessment-2015-2019/bmix-dpzc.

Service Delivered measures the percentage of scheduled buses that are actually provided during peak hours. This dataset covers data from 2020 and on. For data between 2015 and 2019, use dataset https://data.ny.gov/Transportation/MTA-Bus-Service-Delivered-2015-2019/tw28-zvtk.

Wait Assessment measures how evenly buses are spaced. This dataset covers data between 2015 and 2019. For data from 2020 on, use https://data.ny.gov/Transportation/MTA-Bus-Wait-Assessment-Beginning-2020/swky-c3v4.

This dataset provides information on various indicators of safety measured by Metro-North Railroad. The indicators are a combination of preventative measures taken to prevent unsafe incidents, as well as occurrences of unsafe incidents.

This dataset includes the following safety metrics: customer accident rate, grade crossing incidents, train derailments, train collisions, lost time accident rate, lost time injury rate, employee lost time days.

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.

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. This dataset uses the old methodology in which trips were considered on-time if they arrived at the drop-off location no more than five minutes after the requested time. The Drop-off On-Time Performance dataset with the new methodology can be found at https://data.ny.gov/Transportation/MTA-NYCT-Paratransit-Drop-off-On-Time-Performance-/nxai-wcbd/

This dataset provides information on various indicators of safety measured by Long Island Rail Road. The indicators are a combination of preventative measures taken to prevent unsafe incidents, as well as occurrences of unsafe incidents.

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.

This dataset includes the following safety metrics: customer accident rate, grade crossing incidents, train derailments, train collisions, lost time accident rate, lost time injury rate, employee lost time days.

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 Bus Stop Time is the average time that customers spend waiting at a stop beyond their scheduled wait time.

Additional Travel Time is the average time customers spend onboard a bus beyond their scheduled travel time.

Customer Journey Time Performance is the percentage of customers whose journeys are completed within 5 minutes of their scheduled time.

This dataset covers data between 2017 and 2019. For data from 2020 on, use https://data.ny.gov/Transportation/MTA-Bus-Customer-Journey-Focused-Metrics-Beginning/wrt8-4b59/about_data.