Occupancy status, Units, Rooms, Year built, Owner/Renter (Tenure), Mortgage/Rent costs, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: 2022 Wards (State Legislative Districts [Upper Chamber])Current Vintage: 2019-2023 ACS Table(s): DP04. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

Age, Sex, Race, Ethnicity, Total Housing Units, and Voting Age Population. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: 2022 Wards (State Legislative Districts [Upper Chamber]). Current Vintage: 2019-2023. ACS Table(s): DP05. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

Johnson's Georgetown and the city of Washington historic survey : the capital of the United States of America / by Johnson and Ward.

DC Health Search helps residents and visitors find primary care facilities in the District of Columbia. Users can enter an address to search for nearby facilities within a mile or up to 3 miles. Also, use this web map to search by area such as Ward and ANCs. DC Health Search should not be taken as a recommendation for services by the Department of Health. A complete list of sites that are included in DC Health Search are available on the DC Health website.

Crashes on the roadway blocks network of Washington, DC maintained by the District Department of Transportation (DDOT). In addition to locations, a related table consisting of crash details is available for each crash. This table provides some anonymized information about each of the persons involved in the crash (linked by CRASHID). These crash data are derived from the Metropolitan Police Department's (MPD) crash data management system (COBALT) and represent DDOT's attempt to summarize some of the most requested elements of the crash data. Further, DDOT has attempted to enhance this summary by locating each crash location along the DDOT roadway block line, providing a number of location references for each crash. In the event that location data is missing or incomplete for a crash, it is unable to be published within this dataset. Location points with some basic summary statistics,The DC ward the crash occurredSummary totals for: injuries (minor, major, fatal) by type (pedestrian, bicycle, car), mode of travel involved (pedestrian, bicycle, car), impaired participants (pedestrian, bicyclist, car passengers)If speeding was involvedNearest intersecting street nameDistance from nearest intersectionCardinal direction from the intersectionRead more at https://ddotwiki.atlassian.net/wiki/spaces/GIS0225/pages/2053603429/Crash+Data. Questions on the contents of these layers should be emailed to Metropolitan Police Department or the DDOT Traffic Safety Division. Questions regarding the Open Data DC can be sent to @OpenDataDC

These data represent Wards 2012 in Washington, DC. Urban tree canopy (UTC) and possible planting area (PPA) metrics have been calculated for Wards within the study area. UTC results provided in vector format with attribute fields (area/percent metrics/percent change metrics) for each land cover class and UTC type (UTC, PPA, Unsuitable UTC, UTC Change).

To create this layer, OCTO staff used ABCA's definition of “Full-Service Grocery Stores” (https://abca.dc.gov/page/full-service-grocery-store#gsc.tab=0)– pulled from the Food System Assessment below), and using those criteria, determined locations that fulfilled the categories in section 1 of the definition.Then, staff reviewed the Office of Planning’s Food System Assessment (https://dcfoodpolicycouncilorg.files.wordpress.com/2019/06/2018-food-system-assessment-final-6.13.pdf) list in Appendix D, comparing that to the created from the ABCA definition, which led to the addition of a additional examples that meet, or come very close to, the full-service grocery store criteria. The explanation from Office of Planning regarding how the agency created their list:“To determine the number of grocery stores in the District, we analyzed existing business licenses in the Department of Consumer and Regulatory Affairs (2018) Business License Verification system (located at https://eservices.dcra.dc.gov/BBLV/Default.aspx). To distinguish grocery stores from convenience stores, we applied the Alcohol Beverage and Cannabis Administration’s (ABCA) definition of a full-service grocery store. This definition requires a store to be licensed as a grocery store, sell at least six different food categories, dedicate either 50% of the store’s total square feet or 6,000 square feet to selling food, and dedicate at least 5% of the selling area to each food category. This definition can be found at https://abca.dc.gov/page/full-service-grocery-store#gsc.tab=0. To distinguish small grocery stores from large grocery stores, we categorized large grocery stores as those 10,000 square feet or more. This analysis was conducted using data from the WDCEP’s Retail and Restaurants webpage (located at https://wdcep.com/dc-industries/retail/) and using ARCGIS Spatial Analysis tools when existing data was not available. Our final numbers differ slightly from existing reports like the DC Hunger Solutions’ Closing the Grocery Store Gap and WDCEP’s Grocery Store Opportunities Map; this difference likely comes from differences in our methodology and our exclusion of stores that have closed.”Staff also conducted a visual analysis of locations and relied on personal experience of visits to locations to determine whether they should be included in the list.

Data pertaining the arborist planting zones as part of the Urban Forestry Administration (UFA) in the District's Department of Transportation. UFA's primary mission is to keep the District's street canopy healthy, safe, and growing.

This map displays blocks that are part of the RPP program. This map does not necessarily display areas with available RPP parking. Some blocks where residents are eligible for an RPP Permit may have meters or other signage that restrict the usage of RPP Permits.

RPP Permits and Visitor Parking Permits (VPPs) allow parking at green and red RPP zone signs. Please review and follow on-street signage and parking regulations to avoid receiving a citation.

The DDOT Residential/Visitor Parking Zone layer delineates the residential and visitor parking zone boundaries in the District. In place since 2013, the boundaries are similar to the Ward/ANC boundaries, however they do not always share a boundary with Ward/ANC.

The Permit Status application helps citizens locate a permit and obtain information about permitted activities in their community from their smart phone, tablet or PC. This application is used by constituents within District of Columbia, but can also be used by NGOs, contractors or internal Department staff to locate a permit by permit number.To locate a permit, simply enter an address, or Ward in the search box. Or, you can use your current location to find a permit near you. The application will then zoom to the location on the map and relevant information about the permitted or pending permits will be presented to you.

The dataset contains a subset of locations and attributes of incidents reported in the ASAP (Analytical Services Application) crime report database by the District of Columbia Metropolitan Police Department (MPD). Visit https://crimecards.dc.gov for more information. This data is shared via an automated process where addresses are geocoded to the District's Master Address Repository and assigned to the appropriate street block. Block locations for some crime points could not be automatically assigned resulting in 0,0 for x,y coordinates. These can be interactively assigned using the MAR Geocoder.On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.

The dataset contains a subset of locations and attributes of incidents reported in the ASAP (Analytical Services Application) crime report database by the District of Columbia Metropolitan Police Department (MPD). Visit crimecards.dc.gov for more information. This data is shared via an automated process where addresses are geocoded to the District's Master Address Repository and assigned to the appropriate street block. Block locations for some crime points could not be automatically assigned resulting in 0,0 for x,y coordinates. These can be interactively assigned using the MAR Geocoder.On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.

Data Source: Open Data DC and American Community Survey (ACS) 1-Year Estimates.

Why This Matters

Living further from full-service grocery stores can force residents to shop for food at locations that are more expensive or have fewer healthy options, leading to worse health outcomes for conditions such as obesity or diabetes.

Beyond basic nutrition, food is an integral part of culture. Having access to a wide array of culturally relevant foods has been shown to improve well-being among Black, Indigenous, and people of color communities.

Across the United States, predominantly-Black communities have fewer supermarkets than predominantly white and Hispanic communities. A pattern of disinvestment limits the availability of fresh and healthy foods.

The District Response

The Food Access Fund (FAF) Grant increases equitable access to fresh, healthy, and affordable food by supporting the opening of new grocery stores in areas with low food access, with priority given to locations in Ward 7 or Ward 8. The Produce Plus Program provides financial support for residents with low access to fresh foods to spend at local farmers markets.

The SUN Bucks program provides additional grocery-buying benefits to income-eligible families when schools are closed for the summer and children no longer have access to free or reduced-cost meals at school.

The DC Food Policy Council convenes six working groups, including the Food Access & Equity working group that aims to communicate and collaborate with residents to increase awareness of District food benefit programs and healthy food retail.

The dataset contains a subset of locations and attributes of incidents reported in the ASAP (Analytical Services Application) crime report database by the District of Columbia Metropolitan Police Department (MPD). Visit crimecards.dc.gov for more information. This data is shared via an automated process where addresses are geocoded to the District's Master Address Repository and assigned to the appropriate street block. Block locations for some crime points could not be automatically assigned resulting in 0,0 for x,y coordinates. These can be interactively assigned using the MAR Geocoder.On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.

Mail ballot drop boxes are available at select locations beginning June 13, 2025 to July 15, 2025 at 8:00 PM.

The dataset contains locations and attributes of Places of Worship. Information provided by various sources identified Places of Worship such as churches and faith based organizations. DC GIS staff geo-processed this data from a variety of sources.

Farm retail outlets operating in the District of Columbia, and Montgomery and Prince George’s counties with at least one DC Produce Incentive Program-authorized farmer/vendor.

Data Source: DC Office of the Chief Medical Examiner (OCME) and American Community Survey (ACS) 1-Year Estimates

Why This Matters

Opioid-related overdoses have been continuously rising since the late 1990s, with synthetic opioids (such as Tramadol or Fentanyl) being responsible for a sharp rise in opioid-related deaths since 2013.

Opioid Use Disorder (OUD) is treatable, and recovery is possible. Accessing treatment can help people regain their health and continue avoid the dangers associated with opioid misuse.

Several systemic inequities, including disparities in the treatment of mental health disorders, have led to Black individuals dying from opioid overdoses at a higher rate than white individuals.

The District Response

LIVE.LONG.DC (LLDC) is the District’s strategic plan to reduce opioid use, misuse, and related deaths. The plan provides a strategic framework that guides opioid work and investments.

The District does work to prevent, reduce the harm of, treat, and aid in the recovery of opioid use. This includes educational efforts, supplying Naloxone, no-cost rides to initial treatment appointments, and recovery support services.

The Interactive, Ward-specific map provides information about opioid use disorder and substance us disorder-related resources and services available in the District.

Point crash locations along the DDOT GIS centerline network. In addition to the location of the crash location, some basic summary statistics of the crash are provided. This data set is also attributed with a number of important attributes that indicate:The DC ward the crash occured in.Summary totals of:Number of Injuries (Minor, Major, Fatal), broken down by type (Ped, Bike, Car)Type of vehicles involved (Ped, Bike, Car)Type of impaired participant (Ped, Bike, Car driver)Was speeding involved?Nearest intersecting streetnameDistance from that intersectionCardinal direction from the intersection