District of Columbia boundary. The dataset is a polygon representing the District of Columbia boundary, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. The boundary was identified from public records and heads-up digitized using a combination of the 1995 orthophotographs, planimetric roads features, and the USGS digital raster graphic quad sheets, and 1999 planimetrics for the Potomac River boundary.Also see the District's Boundary Stone markers.

Data provided here are from the DC's 311 service request center. They represent all service requests such as abandoned automobiles, parking meter repair and bulk trash pickup. Requests are received by the Office of Unified Communications (OUC) through the Mayor's Call Center (311), citizens web intake at https://311.dc.gov, electronic and US mail service or via other methods of communication. The Office of Unified Communications (OUC) oversees the designated call center for all 311 calls and for all District 911 calls. Please also visit the DC 311 Service Request Map which allows the public to see service requests in the last 30 days. Users can view requests by Ward within charts. Just set the area filter to select service requests. Click on a service request to view details.

These data sets represent 23 geographic 5-minute indexes for the counties of Maryland, one 2 1/2-minute index for Washington D.C., and 1-mile square index for Baltimore City. There are 25 vector polygon data sets covered by this metadata report.

Now more than ever, when global supply chains are struggling, having a strong local food system is critical for the success and health of our communities.

The dataset contains locations and attributes of address points, created as part of the Master Address Repository (MAR) for the Office of the Chief Technology Officer (OCTO) and Department of Buildings (DOB). It contains the addresses in the District of Columbia which are typically placed on the buildings. Visit opendata.dc.gov/pages/addressing-in-dc#documentation for more information on the MAR.

Property or parcel data is a critical layer to any city. In DC's complex urban environment, this includes numerous geographies that identify federal government lands, reservations, District lands, personal property and so much more.

such as buildings and trees

The District of Columbia government uses the Master Address Repository (MAR) to implement intelligent search functionality for finding and verifying addresses, place names, blocks and intersections.

The Dark Gray DC Basemap provides a reference map for the District of Columbia projected in Web Mercator. Access the ArcGIS Rest endpoint. The basemap utilizes the most current planimetric and reference data available and represents the real world with foundation map layers derived from base data collection done in 2023.The service is provided by the Office of the Chief Technology Officer.

The DC Basemap provides a reference map for the District of Columbia projected in Web Mercator. Access the ArcGIS Rest endpoint. The basemap utilizes the most current planimetric and reference data available and represents the real world with foundation map layers derived from base data collection done in 2023.The service is provided by the Office of the Chief Technology Officer.

The MAR allows the District Government to more easily compare information across databases and agencies. Learn more about the MAR with these frequently asked questions.

Planned Land Use from the 2021 Comprehensive Plan Amendment Act of 2021. This data set is an update to the 2006 original version, which was digitized from the Generalized Land Use Map of the District of Columbia Comprehensive Plan. It shows which areas of the city are planned for various uses. These uses include residential and commercial uses at various densities, public land, institutional, federal, and industrial uses. Although planned uses and current uses may be similar, this is not a data set describing current land use. This is a generalized product, and cannot be used to identity specific uses for all specific locations in the District of Columbia.

The dataset includes polygons representing the location and attributes of Central Employment Area (CEA). The CEA is the core area of the District of Columbia where the greatest concentration of employment in the city and region is encouraged, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Jurisdictions were identified from public records (map and written description created by the National Capital Planning Commission) and heads-up digitized from the 1995 orthophotographs.

This dataset contains polygons that represent the boundaries of statistical neighborhoods as defined by the DC Department of Health (DC Health). DC Health delineates statistical neighborhoods to facilitate small-area analyses and visualization of health, economic, social, and other indicators to display and uncover disparate outcomes among populations across the city. The neighborhoods are also used to determine eligibility for some health services programs and support research by various entities within and outside of government. DC Health Planning Neighborhood boundaries follow census tract 2010 lines defined by the US Census Bureau. Each neighborhood is a group of between one and seven different, contiguous census tracts. This allows for easier comparison to Census data and calculation of rates per population (including estimates from the American Community Survey and Annual Population Estimates). These do not reflect precise neighborhood locations and do not necessarily include all commonly-used neighborhood designations. There is no formal set of standards that describes which neighborhoods are included in this dataset. Note that the District of Columbia does not have official neighborhood boundaries. Origin of boundaries: each neighborhood is a group of between one and seven different, contiguous census tracts. They were originally determined in 2015 as part of an analytical research project with technical assistance from the Centers for Disease Control and Prevention (CDC) and the Council for State and Territorial Epidemiologists (CSTE) to define small area estimates of life expectancy. Census tracts were grouped roughly following the Office of Planning Neighborhood Cluster boundaries, where possible, and were made just large enough to achieve standard errors of less than 2 for each neighborhood's calculation of life expectancy. The resulting neighborhoods were used in the DC Health Equity Report (2018) with updated names. HPNs were modified slightly in 2019, incorporating one census tract that was consistently suppressed due to low numbers into a neighboring HPN (Lincoln Park incorporated into Capitol Hill). Demographic information were analyzed to identify the bordering group with the most similarities to the single census tract. A second change split a neighborhood (GWU/National Mall) into two to facilitate separate analysis.

Mayor's Order 2017-115. District of Columbia Data Policy. Originating Agency: Office of the Mayor. A comprehensive data policy for the District of Columbia government. The data created and managed by the District government are valuable assets and are independent of the information systems in which the data reside.

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: District-wide. 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.

Census Year 1930 Census Tracts. The dataset contains polygons representing CY 1930 census tracts, created as part of the D.C. Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Census tracts were identified from maps provided by the U.S. Census Bureau and the D.C. Office of Planning. The tract polygons were created by selecting street arcs from the WGIS planimetric street centerlines. Where necessary, polygons were also heads-up digitized from 1995/1999 orthophotographs. METADATA CONTENT IS IN PROCESS OF VALIDATION AND SUBJECT TO CHANGE.

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.

The dataset contains polygons representing boundaries of District of Columbia 2022 election Wards. Boundaries include Census 2020 demographic data for population, age, race and housing. In the United States Census, Wards are the area name-Legal Statistical Area Description (LSAD) Term-Part Indicator for the District of Columbia.

The District is experiencing the impacts of climate change today. At the same time, many residents face pressing social and economic challenges resulting from a legacy of government systems and policies that created and will perpetuate racial inequity until we transform them. The District has not wavered in our commitment to climate action, and as we adopt this strategy to become carbon neutral and climate resilient by 2045, we recognize that tackling climate change is part of a broader commitment to advance health, opportunity, prosperity, and equity for all District residents.Slashing our carbon pollution will require both imagination and bold action, from revisioning our streets, to transforming how we power our homes and buildings. While a climate strategy alone will not solve the racial inequities at the heart of our city’s biggest challenges, the scale of change required offers new avenues to advance opportunity. The community’s vision has shaped the District’s approach to 2045 and will guide future climate action as we craft and implement solutions.