58 datasets found
  1. d

    Wards from 2022

    • opendata.dc.gov
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • +6more
    Updated Jan 6, 2022
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    City of Washington, DC (2022). Wards from 2022 [Dataset]. https://opendata.dc.gov/datasets/wards-from-2022
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    Dataset updated
    Jan 6, 2022
    Dataset authored and provided by
    City of Washington, DC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    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.

  2. d

    ACS 5-Year Housing Characteristics DC Ward

    • catalog.data.gov
    • opdatahub.dc.gov
    • +2more
    Updated Apr 30, 2025
    + more versions
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    City of Washington, DC (2025). ACS 5-Year Housing Characteristics DC Ward [Dataset]. https://catalog.data.gov/dataset/acs-5-year-housing-characteristics-dc-ward
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    Dataset updated
    Apr 30, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

    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.

  3. d

    ACS 5-Year Economic Characteristics DC Ward

    • catalog.data.gov
    • opdatahub.dc.gov
    • +1more
    Updated May 7, 2025
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    City of Washington, DC (2025). ACS 5-Year Economic Characteristics DC Ward [Dataset]. https://catalog.data.gov/dataset/acs-5-year-economic-characteristics-dc-ward
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    Dataset updated
    May 7, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

    Employment, Commuting, Occupation, Income, Health Insurance, Poverty, 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): DP03. 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.

  4. d

    Social Characteristics of Wards 2019-2023 5-Year ACS

    • opdatahub.dc.gov
    • opendata.dc.gov
    Updated Dec 20, 2024
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    City of Washington, DC (2024). Social Characteristics of Wards 2019-2023 5-Year ACS [Dataset]. https://opdatahub.dc.gov/datasets/social-characteristics-of-wards-2019-2023-5-year-acs
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    Dataset updated
    Dec 20, 2024
    Dataset authored and provided by
    City of Washington, DC
    Description

    Household type, Education, Disability, Language, Computer/Internet Use, 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.govGeography: 2022 Ward (State Legislative Districts [Upper Chamber])Current Vintage: 2019-2023ACS Table(s): DP02Data downloaded from: Census Bureau's API for American Community Survey Date of API call: January 2, 2025National Figures: data.census.gov The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. 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. Click here to learn more about ACS data releases.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 2010 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 Pro.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.

  5. d

    Wards from 1975

    • catalog.data.gov
    • datasets.ai
    • +3more
    Updated Feb 4, 2025
    + more versions
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    D.C. Office of the Chief Technology Officer (2025). Wards from 1975 [Dataset]. https://catalog.data.gov/dataset/wards-from-1975
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    D.C. Office of the Chief Technology Officer
    Description

    This dataset contains polygons representing boundaries of District of Columbia's original Home Rule election wards, established in 1975.

  6. d

    Wards from 2002 with Census 2000

    • catalog.data.gov
    • opendata.dc.gov
    • +2more
    Updated Apr 30, 2025
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    D.C. Office of the Chief Technology Officer (2025). Wards from 2002 with Census 2000 [Dataset]. https://catalog.data.gov/dataset/wards-from-2002-with-census-2000
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    Dataset updated
    Apr 30, 2025
    Dataset provided by
    D.C. Office of the Chief Technology Officer
    Description

    2002 Wards. The dataset contains polygons representing boundaries of District of Columbia 2000 election wards, 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. These political jurisdictions were identified from public records, including published maps and written legal descriptions and heads-up digitized from the 1995 orthophotographs, and updates from 2002. All DC GIS data is stored and exported in Maryland State Plane coordinates NAD 83 meters.

  7. d

    Wards from 2002

    • catalog.data.gov
    • opendata.dc.gov
    • +1more
    Updated Feb 4, 2025
    + more versions
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    D.C. Office of the Chief Technology Officer (2025). Wards from 2002 [Dataset]. https://catalog.data.gov/dataset/wards-from-2002
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    D.C. Office of the Chief Technology Officer
    Description

    This dataset contains polygons representing boundaries of District of Columbia's election wards, used from 2002 to 2011.

  8. d

    Demographic Characteristics of DC Wards 2018-2022 5-Year ACS

    • datasets.ai
    21, 3
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    District of Columbia, Demographic Characteristics of DC Wards 2018-2022 5-Year ACS [Dataset]. https://datasets.ai/datasets/demographic-characteristics-of-dc-wards-2018-2022-5-year-acs
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    3, 21Available download formats
    Dataset authored and provided by
    District of Columbia
    Area covered
    Washington
    Description

    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: 2018-2022

    ACS Table(s): DP05

    Data downloaded from: Census Bureau's API for American Community Survey

    Date of API call: January 2, 2024

    National Figures: data.census.gov

    The United States Census Bureau's American Community Survey (ACS):

    This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. 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. Click here to learn more about ACS data releases.
    • 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 2010 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.

  9. v

    DC Health Planning Neighborhoods

    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • opendata.dc.gov
    • +4more
    Updated Feb 4, 2025
    + more versions
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    City of Washington, DC (2025). DC Health Planning Neighborhoods [Dataset]. https://res1catalogd-o-tdatad-o-tgov.vcapture.xyz/dataset/dc-health-planning-neighborhoods
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

    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.

  10. g

    Demographic Characteristics of DC Wards 2018-2022 5-Year ACS | gimi9.com

    • gimi9.com
    Updated Jun 1, 2022
    + more versions
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    (2022). Demographic Characteristics of DC Wards 2018-2022 5-Year ACS | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_demographic-characteristics-of-dc-wards-2018-2022-5-year-acs
    Explore at:
    Dataset updated
    Jun 1, 2022
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Washington
    Description

    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. Click here to learn more about ACS data releases.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 2010 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.

  11. g

    Housing Characteristics of DC Wards 2018-2022 5-Year ACS | gimi9.com

    • gimi9.com
    Updated Jun 1, 2022
    + more versions
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    (2022). Housing Characteristics of DC Wards 2018-2022 5-Year ACS | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_housing-characteristics-of-dc-wards-2018-2022-5-year-acs/
    Explore at:
    Dataset updated
    Jun 1, 2022
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Washington
    Description

    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. Click here to learn more about ACS data releases.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 2010 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.

  12. v

    DC COVID-19 Vaccine Coverage by Ward

    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • opendata.dc.gov
    • +2more
    Updated May 7, 2025
    + more versions
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    D.C. Office of the Chief Technology Officer (2025). DC COVID-19 Vaccine Coverage by Ward [Dataset]. https://res1catalogd-o-tdatad-o-tgov.vcapture.xyz/dataset/dc-covid-19-vaccine-coverage-by-ward
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    Dataset updated
    May 7, 2025
    Dataset provided by
    D.C. Office of the Chief Technology Officer
    Area covered
    Washington
    Description

    Number of residents who completed the vaccine regimen for COVID-19. Coverage is defined as the number of vaccinated individuals as a proportion of the number of residents living in each ward. The proportion of fully vaccinated residents does not translate to population immunity. Residents who are partially vaccinated may have some level of immunity, immunity may change over time, and non-residents are not be included in the population. Vaccine administration data is reported by facilities and may not be complete.

  13. v

    Urban Tree Canopy by Ward in 2020

    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • opendata.dc.gov
    • +4more
    Updated Feb 4, 2025
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    D.C. Office of the Chief Technology Officer (2025). Urban Tree Canopy by Ward in 2020 [Dataset]. https://res1catalogd-o-tdatad-o-tgov.vcapture.xyz/dataset/urban-tree-canopy-by-ward-in-2020
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    D.C. Office of the Chief Technology Officer
    Description

    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).

  14. d

    DC COVID-19 Cases by Ward

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Feb 5, 2025
    + more versions
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    City of Washington, DC (2025). DC COVID-19 Cases by Ward [Dataset]. https://catalog.data.gov/dataset/dc-covid-19-cases-by-ward
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

    District of Columbia COVID-19 positive cases and total tests reported by Ward. Due to rapidly changing nature of COVID-19, data for March 2020 is limited. General Guidelines for Interpreting Disease Surveillance DataDuring a disease outbreak, the health department will collect, process, and analyze large amounts of information to understand and respond to the health impacts of the disease and its transmission in the community. The sources of disease surveillance information include contact tracing, medical record review, and laboratory information, and are considered protected health information. When interpreting the results of these analyses, it is important to keep in mind that the disease surveillance system may not capture the full picture of the outbreak, and that previously reported data may change over time as it undergoes data quality review or as additional information is added. These analyses, especially within populations with small samples, may be subject to large amounts of variation from day to day. Despite these limitations, data from disease surveillance is a valuable source of information to understand how to stop the spread of COVID19.

  15. a

    DC Wards Shootings

    • gun-violence-analysis-uofmd.hub.arcgis.com
    Updated Jan 15, 2025
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    University of Maryland (2025). DC Wards Shootings [Dataset]. https://gun-violence-analysis-uofmd.hub.arcgis.com/datasets/dc-wards-shootings
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    Dataset updated
    Jan 15, 2025
    Dataset authored and provided by
    University of Maryland
    Area covered
    Description

    Time enabled layer of shootings in DC, MD, and VA from 2014-2024

  16. d

    Neighborhood Labels

    • catalog.data.gov
    • opendata.dc.gov
    • +5more
    Updated Feb 5, 2025
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    D.C. Office of the Chief Technology Officer (2025). Neighborhood Labels [Dataset]. https://catalog.data.gov/dataset/neighborhood-labels
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    D.C. Office of the Chief Technology Officer
    Description

    This dataset was created by the DC Office of Planning and provides a simplified representation of the neighborhoods of the District of Columbia. These boundaries are used by the Office of Planning to determine appropriate locations for placement of neighborhood names on maps. They do not reflect detailed boundary information, do not necessarily include all commonly-used neighborhood designations, do not match planimetric centerlines, and do not necessarily match Neighborhood Cluster boundaries. There is no formal set of standards that describes which neighborhoods are represented or where boundaries are placed. These informal boundaries are not appropriate for display, calculation, or reporting. Their only appropriate use is to guide the placement of text labels for DC's neighborhoods. This is an informal product used for internal mapping purposes only. It should be considered draft, will be subject to change on an irregular basis, and is not intended for publication.

  17. g

    DC Office of Tax and Revenue Real Property Assessment Map App | gimi9.com

    • gimi9.com
    Updated Jul 26, 2022
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    (2022). DC Office of Tax and Revenue Real Property Assessment Map App | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_dc-office-of-tax-and-revenue-real-property-assessment-map-app/
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    Dataset updated
    Jul 26, 2022
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The DC Office of the Chief Financial Officer (OCFO), Office of Tax and Revenue (OTR), Real Property Tax Administration (RPTA) values all real property in the District of Columbia. This public interactive Real Property Assessment map application accompanies the OCFO MyTax DC and OTR websites. Use this mapping application to search for and view all real property, assessment valuation data, assessment neighborhood areas and sub-areas, detailed assessment information, and many real property valuation reports by various political and administrative areas. View by other administrative areas such as DC Wards, ANCs, DC Squares, and by specific real property characteristics such as property type and/or sale date. If you have questions, comments, or suggestions regarding the Real Property Assessment Map, contact the Real Property Assessment Division GIS Program at (202) 442-6484 or maps.title@dc.gov.

  18. d

    Real Property Tax Assessment Neighborhoods

    • catalog.data.gov
    • datasets.ai
    • +4more
    Updated May 21, 2025
    + more versions
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    DC Office of Tax and Revenue- Real Property Division (2025). Real Property Tax Assessment Neighborhoods [Dataset]. https://catalog.data.gov/dataset/real-property-tax-assessment-neighborhoods
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    Dataset updated
    May 21, 2025
    Dataset provided by
    DC Office of Tax and Revenue- Real Property Division
    Description

    This dataset contains polygons that represent the boundaries of assessment neighborhoods as defined by the DC Office of Tax and Revenue (OTR) Real Property Tax Administration (RPTA). For analysis purposes, RPTA delineates assessment neighborhoods to group properties that are affected by similar economic, political, governmental, and environmental factors. Assessment neighborhoods are defined by the environment of a subject property that has a direct and immediate effect on its value. The assessment neighborhood is a geographic area (in which there are typically fewer than several thousand properties) defined for some useful purpose, such as to ensure for later multiple regression modeling that the properties are homogeneous and share important locational characteristics. Assessment neighborhoods boundaries typically follow street centerlines, hydrological boundaries, and boundaries of major properties such as parks and monuments.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.

  19. d

    Crashes in DC

    • catalog.data.gov
    • datasets.ai
    • +7more
    Updated Aug 6, 2025
    + more versions
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    Metropolitan Police Department (2025). Crashes in DC [Dataset]. https://catalog.data.gov/dataset/crashes-in-dc
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    Dataset updated
    Aug 6, 2025
    Dataset provided by
    Metropolitan Police Department
    Area covered
    Washington
    Description

    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

  20. p

    2023 ANC Changes, Addresses

    • parkdc.com
    • parkdc-dcgis.hub.arcgis.com
    Updated Dec 28, 2022
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    City of Washington, DC (2022). 2023 ANC Changes, Addresses [Dataset]. https://www.parkdc.com/items/d6b6b4f8e3ec44febbd43d68588755ac
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    Dataset updated
    Dec 28, 2022
    Dataset authored and provided by
    City of Washington, DC
    Description

    The addresses that will be in a new ANC when the 2023 ANC boundaries go into effect on January 1st, 2023.Does not include:- Non Residential Addresses

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City of Washington, DC (2022). Wards from 2022 [Dataset]. https://opendata.dc.gov/datasets/wards-from-2022

Wards from 2022

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22 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jan 6, 2022
Dataset authored and provided by
City of Washington, DC
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
Description

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.

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