AndreaBozzo/ceres-open-data-index huggingface dataset:
Vision Zero Safety

<div>The Vision Zero Safety data comes from a web-based application developed to allow the public to communicate the real and perceived dangers along the roadway from the perspective of either a pedestrian, bicyclist or motorist. The data is captured from a site visitor who can click or tap on a location to report a transportation hazard. Vision Zero is a part of Mayor Bowser’s response to the US Department of Transportation’s Mayor’s Challenge for Safer People and Safer Streets, which aims to improve pedestrian and bicycle transportation safety by showcasing effective local actions, empowering local leaders to take action, and promoting partnerships to advance pedestrian and bicycle safety. Vision Zero requires an all-hands-on-deck approach. More than 20 District government agencies are engaged in the Vision Zero Initiative, including DDOT, Department of Public Works, the Deputy Mayor for Health and Human Services, Metropolitan Police Department, DC Taxi Cab Commission, the Department of Motor Vehicles, the DC Office on Aging, DC Public Schools, Fire and Emergency Medical Services, Homeland Security and Management, Office of Unified Communications, Department of Health, the Office of the Attorney General, Office of the Chief Technology Officer, Office of Disability Rights, Office of Planning, Office of the City Administrator, Office of the State Superintendent of Education, the Deputy Mayor for Education, Office of Policy and Legislative Affairs, and the Deputy Mayor for Planning and Economic Development. Contact the Vision Zero team at <a href='mailto:vision.zero@dc.gov' rel='nofollow ugc' target='_blank'>vision.zero@dc.gov</a>.</div><div><br /></div><div>Please note that this map is not DC's 311 service request system. Department of Transportation (DDOT) staff will investigate the concerns identified on this map and if necessary, submit a 311 request on behalf of the site visitor.  Users always have the option to submit a separate 311 service request at <a href='https://311.dc.gov/' rel='nofollow ugc' target='_blank'>https://311.dc.gov/</a>.</div>

Tags: bicycle, crash, dc-government, ddot, district-of-columbia, driving, emergency, enforcement, medical, mobile, motorist, pedestrian, police, safety, transportation, vision, vision-zero, washington-dc, zero
Organization: District of Columbia
2004 LiDAR - Bare Earth

Bare Earth Light Detection and Ranging (LIDAR) Data - 1m resolution. The dataset contains locations and attributes of bare earth elevations in meters.  Bare earth model is created by identifying those returns that fall on the ground surface and interpolating a surface between these points.  In this manner buildings and vegetation are removed from Bare Earth Model.   This data set does not include bridges and overpasses in the Bare Earth model as the delineation point for these structures is not reliably discernable in the LiDAR data.

Tags: bare-earth, district-of-columbia, elevation, imagery, lidar, washington-dc
Organization: District of Columbia
Job Destination Walk Access

<div style='text-align:Left;'><div><div><p><span><span>This layer considers jobs and destinations to be accessible by walking if the destinations are reachable within 20 minutes. Access to jobs and destinations within a fixed time is measured using the actual networks and not a straight line distance. Destinations include grocery stores, hospitals, community services, education centers, and other significant community areas. Jobs across the region (not just within the District) were used to provide a full picture of employment access.</span></span></p></div></div></div>

Tags: ddot, district-of-columbia, job-destination, movedc, transportation, walk-access, washington-dc
Organization: District of Columbia
2009 LiDAR - Bare Earth

Bare Earth Light Detection and Ranging (LIDAR) Data - 1m resolution. The dataset contains locations and attributes of bare earth elevations in meters.  Bare earth model is created by identifying those returns that fall on the ground surface and interpolating a surface between these points.  In this manner buildings and vegetation are removed from Bare Earth Model.   This data set does not include bridges and overpasses in the Bare Earth model as the delineation point for these structures is not reliably discernable in the LiDAR data.

Tags: bare-earth, district-of-columbia, elevation, imagery, lidar, washington-dc
Organization: District of Columbia
2014 LiDAR - Bare Earth

Bare Earth Light Detection and Ranging (LIDAR) Data - 1m resolution. The dataset contains locations and attributes of bare earth elevations in meters.  Bare earth model is created by identifying those returns that fall on the ground surface and interpolating a surface between these points.  In this manner buildings and vegetation are removed from Bare Earth Model.  This data set does not include bridges and overpasses in the Bare Earth model as the delineation point for these structures is not reliably discernible in the LiDAR data.

Tags: bare-earth, district-of-columbia, elevation, imagery, lidar, washington-dc
Organization: District of Columbia
2004 LiDAR - First Return

First Return Light Detection and Ranging (LIDAR) Data - 1m resolution. The dataset contains locations and attributes of first return elevations in meters.  LIDAR data provided by the Joint Precision Strike Demonstration Project Office of the US Army contained bare earth rasters.  This raster contains elevations of all structures, tree canopies, and bare earth.

Tags: district-of-columbia, elevation, first-return, imagery, lidar, washington-dc
Organization: District of Columbia
2009 LiDAR - Intensity

Intensity Light Detection and Ranging (LIDAR) Data - 1m resolution. Intensity information is captured from the Reflective Surface pulse and indicates the relative energy returned to the sensor as compared to the energy transmitted.  The Intensity image is not calibrated or normalized but indicates differences in energy absorption due to the the interaction of the surface materials with laser energy at the wavelength transmitted by the sensor.

Tags: district-of-columbia, elevation, imagery, intensity, lidar, washington-dc
Organization: District of Columbia
Neighborhood Investment Fund Areas

<div style='text-align:Left;'><div><div><p><span>The dataset contains locations and attributes of Neighborhood Investment Fund Areas (NIF).The Neighborhood Investment Fund is an annual, non-lapsing fund to finance economic development and neighborhood revitalization in 12 targeted areas of the District. The fund is capitalized by an annual contribution of 15 percent of the personal property tax, not to exceed $10 million. The Neighborhood Investment Fund supports neighborhood revitalization through the Target Area Grant Program (TAPG) and Predevelopment and Project Grants (PDG).</span></p></div></div></div>

Tags: business, district-of-columbia, dmped, economic, fund, investment, money, neighborhood, tax, washington-dc
Organization: District of Columbia
LiDAR - Reflective Surface - 2009

Reflective Surface Light Detection and Ranging (LIDAR) Data for Washington, DC at 1 meter resolution.  Reflective surface data represents the DEM created by laser energy reflected from the first surface encountered by the laser pulse.  Some energy may continue beyond this initial surface to be reflected by a subsequent surface as represented by the Last Return data.

Tags: district-of-columbia, elevation, imagery, lidar, reflective-surface, washington-dc
Organization: District of Columbia
Job Destination Rail Access AM Peak

<div style='text-align:Left;'><div><div><p><span><span>This layer considers jobs and destinations to be accessible by Metrorail if the destinations are reachable within 30 minutes by train. Access to jobs and destinations within a fixed time is measured using the actual networks and not a straight line distance. Destinations include grocery stores, hospitals, community services, education centers, and other significant community areas. Jobs across the region (not just within the District) were used to provide a full picture of employment access.</span></span></p></div></div></div>

Tags: ddot, district-of-columbia, job-destination, metro, movedc, rail, transportation, washington-dc
Organization: District of Columbia
Job Destination Bus Access AM Peak

<div style='text-align:Left;'><div><div><p><span><span>This layer considers jobs and destinations to be accessible by bus if the destinations are reachable within 30 minutes. Access to jobs and destinations within a fixed time is measured using the actual networks and not a straight line distance. Destinations include grocery stores, hospitals, community services, education centers, and other significant community areas. Jobs across the region (not just within the District) were used to provide a full picture of employment access.</span></span></p></div></div></div>

Tags: bus-access, ddot, district-of-columbia, job-destination, movedc, transportation, washington-dc
Organization: District of Columbia
2015 LiDAR - Intensity

<div>The District of Columbia government requires a comprehensive range of GIS data and photogrammetric mapping to support a wide variety of applications through the DC GIS program. Due to technology advances, expanding user base needs, and aging data, DC GIS acquired new LIDAR data in spring 2015 to establish a more thorough and better quality core LIDAR dataset The LiDAR data products are suitable for 1 foot (or less) contour generation. Intensity images generated from the RPC data for the DC OCTO 2015 LiDAR project covering approximately 80 square miles, in which its extents cover Arlington County in Washington DC. Intensity is a measure, collected for every point, of the return strength of the laser pulse that generated the point. It is based, in part, on the reflectivity of the object struck by the laser pulse.  This project consists of deliverables in accordance with USGS v1.2 specifications and meets or exceeds the level of quality for QL1 (8 points per meter).</div>

Tags: district-of-columbia, elevation, imagery, intensity, lidar, washington-dc
Organization: District of Columbia
Job Destination Bike Access

<div style='text-align:Left;'><div><div><p><span><span>This layer considers jobs and destinations to be accessible by bike if the destinations are reachable within 30 minutes. Access to jobs and destinations within a fixed time is measured using the actual networks and not a straight line distance. Destinations include grocery stores, hospitals, community services, education centers, and other significant community areas. Jobs across the region (not just within the District) were used to provide a full picture of employment access.</span></span></p></div></div></div>

Tags: bike-access, ddot, district-of-columbia, job-destination, movedc, transportation, washington-dc
Organization: District of Columbia
Average Weekday Intrazonal Shared Mobility Trips

New transportation modes have grown in the District in the last decade, including private for-hire vehicle companies and micromobility options, such as shared bikes and scooters. In 2019, there were over 60 million trips taken by private for-hire vehicles to, from, or within the District, and 128 million in the region. This map shows the distribution of average daily weekday private for-hire vehicle trips across neighborhood zones in the District in 2019.


Tags: district-of-columbia, for-hire-vehicles, intrazonal-trips, micromobility, movedc, tnc, transportation, transportation-modes, washington-dc
Organization: District of Columbia
Average Weekday Interzonal Shared Mobility Trips

New transportation modes have grown in the District in the last decade, including private for-hire vehicle companies and micromobility options, such as shared bikes and scooters. In 2019, there were over 60 million trips taken by private for-hire vehicles to, from, or within the District, and 128 million in the region. This map shows the distribution of average daily weekday private for-hire vehicle trips across neighborhood zones in the District in 2019.

Tags: district-of-columbia, for-hire-vehicles, interzonal-trips, micromobility, movedc, tnc, transportation, transportation-modes, washington-dc
Organization: District of Columbia
FOIA Legacy

<div style='text-align:Left;'><div><div><p><span>In the summer of 2024, the District of Columbia migrated its FOIA records management to a new system. This dataset houses the archived Freedom of Information Act (FOIA) requests to DC Government by various organizations and individuals -received beginning September 2, 2014 through June 14, 2024. FOIA request that did not close prior to June 14, 2024 were migrated to the new system in July 2024. Their original dates and status remain the same within this archive. Updated information for any outstanding migrated FOIA requests can be cross-referenced in the FOIA Legacy Crossover dataset that is also found on Open Data DC.</span></p></div></div></div>

Tags: district-of-columbia, foia, freedom-of-information-act, government, operations, os, washington-dc
Organization: District of Columbia
Economic Development Zones

<div style='text-align:Left;'><div><div><p><span>This data is used for the planning and management of Washington by local government agencies. To create economic development zones to assist in stimulating the expansion of commercial and industrial businesses, long-term employment, and homeownership in disadvantaged areas of the District and to amend the District of Columbia Real Property Tax Revision Act of 1974, An Act Relating to the levying and collecting of taxes and assessments, and for other purposes, An Act To provide for the abatement of nuisances in the District of Columbia by the Commissioners of said District, and for other purposes, the District of Columbia Public Works Act of 1954, the District of Columbia Income and Franchise Tax Act of 1947, and the Lower Income Home ownership Tax Abatement and Incentive Act of 1983 to make conforming amendments.</span></p></div></div></div>

Tags: business, dc, development, district-of-columbia, economic, edz, op, washington-dc
Organization: District of Columbia
Vision Zero DC

Vision Zero is a safe systems approach to reducing injuries and deaths on our roadways, looking at how our entire transportation system can create a safe environment for travel. The District Government has an all-hands-on-deck approach, with five key agencies involved, and another 25 agencies with some role to play - safe users, safe streets, safe vehicles, safe speeds, post crash care. <div><br /></div><div>Good government is doing the best thing for the most people. While many efforts that DDOT undertakes contribute to a culture of traffic safety and safe systems, DDOT needs a strategic approach to address streets and neighborhoods that continuously see the highest fatal and serious injury crash rates and, as a close second, areas that have the highest risk. This strategy is supplemented by prioritizing streets and neighborhoods that have seen historic disinvestment and high numbers of vulnerable populations. Between these methods of project prioritization, DDOT can more effectively mitigate future crashes to see reductions in fatality and serious injury rates, while reducing transportation disparities in the District.</div>

Tags: featuredprogram, hub-site, vision-zero, vision-zero-dc, ward_all
Organization: District of Columbia
2022 Final Assisted Reproductive Technology (ART) Services and Profiles

ART data are made available as part of the National ART Surveillance System (NASS) that collects success rates, services, profiles and annual summary data from fertility clinics across the U.S. There are four datasets available: ART Services and Profiles, ART Patient and Cycle Characteristics, ART Success Rates, and ART Summary. All four datasets may be linked by “ClinicID.” ClinicID is a unique identifier for each clinic that reported cycles. The Services and Profiles dataset provides an overview of clinic services, the clinic’s contact information, location, the medical director’s name, and summary statistics.

Tags: art, assisted-reproductive-technology, clinic, fertility, infertility, services, success-rates
Organization: U.S. Department of Health & Human Services
500 Cities: Local Data for Better Health, 2016 release

This is the complete dataset for the 500 Cities project 2016 release. This dataset includes 2013, 2014 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2013, 2014), Census Bureau 2010 census population data, and American Community Survey (ACS) 2009-2013, 2010-2014 estimates. More information about the methodology can be found at www.cdc.gov/500cities.
Note: During the process of uploading the 2015 estimates, CDC found a data discrepancy in the published 500 Cities data for the 2014 city-level obesity crude prevalence estimates caused when reformatting the SAS data file to the open data format. . The small area estimation model and code were correct. This data discrepancy only affected the 2014 city-level obesity crude prevalence estimates on the Socrata open data file, the GIS-friendly data file, and the 500 Cities online application. The other obesity estimates (city-level age-adjusted and tract-level) and the Mapbooks were not affected. No other measures were affected. The correct estimates are update in this dataset on October 25, 2017.

Tags: 500-cities, census, estimates, prevalence, tracts
Organization: U.S. Department of Health & Human Services
2021 Final Assisted Reproductive Technology (ART) Summary

Data were updated on September 11, 2024.

ART data are made available as part of the National ART Surveillance System (NASS) that collects success rates, services, profiles and annual summary data from fertility clinics across the U.S. There are four datasets available: ART Services and Profiles, ART Patient and Cycle Characteristics, ART Success Rates, and ART Summary. All four datasets may be linked by “ClinicID.” ClinicID is a unique identifier for each clinic that reported cycles. The Summary dataset provides a full snapshot of clinic services and profile, patient characteristics, and ART success rates. It is worth noting that patient medical characteristics, such as age, diagnosis, and ovarian reserve, affect ART treatment’s success. Comparison of success rates across clinics may not be meaningful because of differences in patient populations and ART treatment methods. The success rates displayed in this dataset do not reflect any one patient’s chance of success. Patients should consult with a doctor to understand their chance of success based on their own characteristics.

Tags: art, assisted-reproductive-technology, clinic, fertility, infertility, services, success-rates
Organization: U.S. Department of Health & Human Services
Telehealth Services Provided to the Medicaid and CHIP Population

This data set includes monthly counts and rates (per 1,000 beneficiaries) of services provided via telehealth, including live audio video, remote patient monitoring, store and forward, and other telehealth, to Medicaid and CHIP beneficiaries, by state. 

These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating telehealth services measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Claims Volume - OT, Procedure Codes - OT Professional. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data. 

Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

Tags: chip, dq-atlas, medicaid, service-use, t-msis-analytic-files, telehealth
Organization: U.S. Department of Health & Human Services
IHS Facility Locator

<p>This map can be used to find an Indian Health Service, Tribal or Urban Indian Health Program facility. This map can be used to:&#13;<br />
Zoom in to a general location to see if there is a facility in that region.&#13;<br />
Enter your current location in the form to see the facilities available.&#13;<br />
Find a specific facility by selecting the "Facility Information" tab and typing in the name of the facility that you are trying to find.&#13;</p>

Tags: health-care-providers, indian-health-service
Organization: U.S. Department of Health & Human Services
2018 Child and Adult Health Care Quality Measures

Performance rates on frequently reported health care quality measures in the CMS Medicaid/CHIP Child and Adult Core Sets, for FFY 2018 reporting.

Source: Mathematica analysis of MACPro and Form CMS-416 reports for the FFY 2018 reporting cycle. For more information, see the Children's Health Care Quality Measures and Adult Health Care Quality Measures webpages.

Tags: core-sets, performance-rates, quality-measures
Organization: U.S. Department of Health & Human Services
Beneficiaries who could benefit from integrated care, 2017-2021

This table presents three populations of beneficiaries who could benefit from different levels of integrated care, 2017-2021: (1) beneficiaries who received services for a behavioral health (BH) condition; (2) beneficiaries who received services for a behavioral health condition who also received services for at least one of a number of select physical health (PH) conditions (a subset of population 1); and (3) beneficiaries prescribed medications for substance use disorders who do not have a medical claim for a behavioral health condition (a subset of population 1).

Some states have serious data quality issues, making the data unusable for identifying this population. To assess data quality, analysts used measures featured in the DQ Atlas. Data for a state are considered unusable based on DQ Atlas thresholds for the following topics: Total Medicaid and CHIP Enrollment, Claims Volume - IP, Claims Volume - OT, Claims Volume - IP, Diagnosis Code - IP, Diagnosis Code - OT, Procedure Codes - OT Professional, Gender, Age, Zip code, Race and ethnicity, Eligibility group code, Enrollment in CMC Plans. 

Data from Maryland, Tennessee, and Utah are omitted for the tables due to data quality concerns. Maryland was excluded in 2017 due to unusable diagnosis codes in the IP file and the OT file. Tennessee was excluded due to unusable diagnosis codes in the IP file in 2017 - 2019. Utah was excluded due to unusable procedure codes on OT professional claims in 2017 - 2020. In addition, states with a high data quality concern on one or more measures are noted in the table in the "Data Quality" column. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods.

Tags: behavioral-health-care, chip, integrated-care, medicaid
Organization: U.S. Department of Health & Human Services