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.

Building structures include parking garages, ruins, monuments, and buildings under construction along with residential, commercial, industrial, apartment, townhouses, duplexes, etc. Buildings equal to or larger than 9.29 square meters (100 square feet) are captured. Buildings are delineated around the roof line showing the building "footprint." Roof breaks and rooflines, such as between individual residences in row houses or separate spaces in office structures, are captured to partition building footprints. This includes capturing all sheds, garages, or other non-addressable buildings over 100 square feet throughout the city. Atriums, courtyards, and other “holes” in buildings created as part of demarcating the building outline are not part of the building capture. This includes construction trailers greater than 100 square feet. Memorials are delineated around a roof line showing the building "footprint."Bleachers are delineated around the base of connected sets of bleachers. Parking Garages are delineated at the perimeter of the parking garage including ramps. Parking garages sharing a common boundary with linear features must have the common segment captured once. A parking garage is only attributed as such if there is rooftop parking. Not all rooftop parking is a parking garage, however. There are structures that only have rooftop parking but serve as a business. Those are captured as buildings. Fountains are delineated around the base of fountain structures.

DC celebrates International Open Data Day with events, sessions and activities that include Open Data into them. Open Data Day, or week, is typically observed in the first weeks of March. It is an annual celebration of open data all over the world.

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.

Mayor's Order 2017-115 establishes a comprehensive data policy for the District 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. As such, the District government shall: maintain an inventory of its enterprise datasets; classify enterprise datasets by level of sensitivity; regularly publish the inventory, including the classifications, as an open dataset; and strategically plan and manage its investment in data.The greatest value from the District’s investment in data can only be realized when enterprise datasets are freely shared among District agencies, with federal and regional governments, and with the public to the fullest extent consistent with safety, privacy, and security. For more information, please visit https://opendata.dc.gov/pages/edi-overview. Previous years of EDI can be found on Open Data.

The Office of the Chief Technology Officer (OCTO), within the District of Columbia (DC) government, manages the District’s data program. This includes open data, business intelligence, data curation, and Geographic Information Systems (GIS). The open data handbook explains the process and steps the OCTO data program undertakes when an agency submits an open dataset. More importantly, the handbook documents dataset rules, metadata requirements, and policies to make data consistent and standardized. This applies to any dataset submitted for publication on DC’s open data portal.

Mayor's Order 2017-115 establishes a comprehensive data policy for the District 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. As such, the District government shall:Maintain an inventory of its enterprise datasets;Classify enterprise datasets by level of sensitivity;Regularly publish the inventory, including the classifications, as an open dataset; andStrategically plan and manage its investment in data.The greatest value from the District’s investment in data can only be realized when enterprise datasets are freely shared among District agencies, with federal and regional governments, and with the public to the fullest extent consistent with safety, privacy, and security. For more information, please visit https://octo.dc.gov/page/district-columbia-data-policy. Previous years of EDI can be found on Open Data.

These data represent detailed land cover in Washington, DC. The data were derived using remote sensing technologies on satellite imagery from the Pleiades satellite, flown in 2020 and 2020 DC LiDAR. This dataset provided as an ArcGIS Image service. Please note, the download feature for this image service in Open Data DC provides a compressed PNG, JPEG or TIFF. The full raster GeoTIFF dataset is available under additional options when viewing downloads.

Mayor's Order 2017-115 establishes a comprehensive data policy for the District 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. As such, the District government shall: maintain an inventory of its enterprise datasets; classify enterprise datasets by level of sensitivity; regularly publish the inventory, including the classifications, as an open dataset; and strategically plan and manage its investment in data.The greatest value from the District’s investment in data can only be realized when enterprise datasets are freely shared among District agencies, with federal and regional governments, and with the public to the fullest extent consistent with safety, privacy, and security. For more information, please visit https://opendata.dc.gov/pages/edi-overview. Previous years of EDI can be found on Open Data.

You can use this page to explore Green Infrastructure (GI) practices throughout the District of Columbia. Use the filters to search for GI installed through specific DOEE programs or to search for GI of a specific type. You can also download GI data from the District's publicly-available layer of Best Management Practice (BMP) data.

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.

Open Data Handbook Curation Detailed Diagram. DC’s data submission process involves four steps as depicted in this diagram. Overall, the data analysts guide the data owner and other analysts as needed to run the data through the submission process, with different groups leading each part (see all caps in diagram above). Their application occurs in a unified database infrastructure consisting of a data warehouse and geospatial database. While there are specific processes and guidelines for each database, they share an overall setting where consistency and standardization are promoted and supported for their individual data curation processes.

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: Census Tracts. 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.

A generalized dataset of existing land use in the District of Columbia as existed during its most recent extract of the common ownership lots. This dataset is different from the Comprehensive Plan - Future Land Use, which shows land use as envisioned in the latest version of DC’s Comprehensive Plan. The primary land use categories used in this dataset are similar, but not identical. The Office of the Chief Technology Officer (OCTO) compared two datasets to create this generalized existing land use data. The data source identifying property use is the Property Use Code Lookup from the Office of Tax and Revenue (OTR). An index provided by the Office of Planning assigns each OTR property use code with a “primary land use” designation. Through an automated process, the common ownership lots were then joined with this index to create the Existing Land Use. Only properties with an assigned use code from OTR are categorized. Other properties without a use code were left as NULL. Many of these tend to be public lands such as national parks. Refer to https://opendata.dc.gov/pages/public-lands.This dataset has no legal status and is intended primarily as a resource and informational tool. The Office of the Chief Technology Officer anticipates replicating this work annually.

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.

The DC Housing Authority provides quality affordable housing to extremely low- through moderate-income households, fosters sustainable communities, and cultivates opportunities for residents to improve their lives. The following is a subset of the District Government Land (Owned, Operated, and or managed) dataset that include buildings with a "public housing" use type.

The dataset contains constructed unique geospatial identifier for buildings. A buildings UBID is the north axis aligned "bounding box" of its footprint represented as the centroid (in the GDAL grid reference system format), which is represented by the first set of characters before the first dash, and four cardinal extents, which are represented by the four sets of numbers after the first dash (North, East, South, West),The data has been constructed by spatially joining the latest (2019) building footprints published in DC Open Data with the Common Ownership Lot shapefile. The UBIDs were coded using US DOE’s Implementation code. Please note that the current data set may include some unnecessary structures identified as buildings. These included sheds, overhangs, bus stops, and other structures that do not need to be assigned a UBID. An updated version of the UBID dataset will be released when this issue is resolved. This project is the result of the US DOE Better Buildings Building Energy Data Analysis (BEDA) Accelerator. US DOE is working with stakeholders including state and local governments, commercial and residential building data aggregators, property owners, and product and service providers to develop the UBID system and to pilot it in real-world settings. US DOE and its partners are demonstrating the benefits of UBID in managing and cross-referencing large building datasets and in reducing the costs and enhancing the value proposition of leveraging building energy data. UBIDs For more information regarding UBIDs please visit: https://www.energy.gov/eere/buildings/unique-building-identifier-ubid

Traffic volume of Roadway Blocks. The dataset contains traffic volume data, created as part of the District of Columbia, Department of Transportation (DDOT) Roads and Highways database. A database provided by the District of Columbia, Department of Transportation identified traffic volume. Count data is collected (both direction) at pre-selected locations on Highway Performance Monitoring System (HPMS) Sections on a three-year cycle. These counts are converted to Annual Average Daily Traffic (AADT).

About this dataset

Context

The dataset tabulates the population of Washington by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Washington across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 52.39% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Washington is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Washington total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Washington Population by Race & Ethnicity. You can refer the same here