Historical Data on the Buildings of Washington DC, collected over 15 years by Brian Kraft, with support from JMT Inc., for the DC Historic Preservation Office. Most of the data comes from the building permits issued by the city, especially from 1877 to 1949. Sources are named for all buildings and other sources include real estate maps, tax assessments, newspaper reports, and the DC Office of Tax and Revenue, mostly for buildings after 1949. Work on this data is ongoing but we feel that this will be a valuable and enjoyable research tool as it is.

Moving citation locations in the District of Columbia. The Vision Zero data contained in this layer pertain to moving violations issued by the District of Columbia's Metropolitan Police Department (MPD) and partner agencies with the authority. For example, DC's enforcement camera program cites speeders, blocking the box, and other moving offenses. Moving violation locations are summarized ticket counts based on time of day, week of year, year, and category of violation. Data was originally downloaded from the District Department of Motor Vehicle's eTIMS meter work order management system. Data was exported into DDOT’s SQL server, where the Office of the Chief Technology Officer (OCTO) geocoded citation data to the street segment level. Data was then visualized using the street segment centroid coordinates.

Affordable housing production and preservation projects are managed by the Department of Housing and Community Development (DHCD), the Deputy Mayor for Planning and Economic Development (DMPED), the DC Housing Authority, the DC Housing Finance Agency and DC's Inclusionary Zoning program. This dataset comprehensively covers affordable housing projects which started (i.e. reached financial closing and/or started construction) or completed since January of 2015. The data includes affordable housing projects (production and preservation, rental and for-sale) which were subsidized by DMPED, DHCD, DCHFA, or DCHA, and those which were produced as a result of Planned Unit Development (PUD) proffers or Inclusionary Zoning (IZ) requirements.

The following datasets are not published in Open Data DC as of March 11, 2018. They will be prioritized for publication in FY19. 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.

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.gov. Geography: District-wide. Current Vintage: 2019-2023. ACS Table(s): DP02. 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 Office of the Chief Technology Officer (OCTO), within the District of Columbia (DC) government, manages the District’s data program. This includes open data, data curation, data integration, data storage, data science, data application development and Geographic Information Systems (GIS). The open data handbook explains the process and steps OCTO undertakes when an agency submits an open dataset for publication. The handbook outlines dataset rules, documentation requirements, and policies to make data consistent and standardized. This applies to any dataset submitted for publication on the Open Data DC portal that is classified as Level 0: Open as defined in the District’s Data Policy. For previous versions of the handbook visit https://opendata.dc.gov/pages/handbook.

District of Columbia COVID-19 total tests reported by DC Health Planning Neighborhoods. 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.

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.

This dataset is host to DC Water's information about Pipe Materials. The dataset is updated when updates are made available. The information provided is limited to the best available data in DC Water’s possession at the time the dataset was loaded.Data Disclaimer: District of Columbia Water and Sewer Authority (“D.C. Water”) provides data available on this website as a service to the public. The data provided by D.C. Water is based on historical data, information directly provided by DC Water's installation contractor and in some cases, information acquired during physical inspections. DC Water does not guarantee the accuracy of this data and assumes no liability for any errors. The data shall be used for the sole purpose of providing property owners and residents with information regarding this program and not for any commercial, legal or other use. D.C. Water assumes no liability for any decisions made or action taken or not taken by anyone using data provided from this website. D.C. Water reserves the right to alter, amend or terminate at any time the display of this data.

The Framework keeps each agency that has responsibility for a given data set at the center of decision-making and handling of the data. It guides agencies in their review of key considerations like data security, retention and archive periods, sensitivity of information, and the scope of uses authorized. DC agencies are the drivers of every incidence of data sharing and are empowered by the Office of the Chief Technology Officer (OCTO) to maintain active control over access and permissions to every data element throughout its lifecycle.

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.

About this dataset

Context

The dataset tabulates the data for the District of Columbia, DC population pyramid, which represents the District of Columbia population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for District of Columbia, DC, is 23.0.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for District of Columbia, DC, is 17.9.
• Total dependency ratio for District of Columbia, DC is 40.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for District of Columbia, DC is 5.6.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the District of Columbia population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the District of Columbia for the selected age group is shown in the following column.
• Population (Female): The female population in the District of Columbia for the selected age group is shown in the following column.
• Total Population: The total population of the District of Columbia for the selected age group is shown in the following column.

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 District of Columbia Population by Age. You can refer the same here

This dataset includes all identifiable DCPS public elementary schools, middle schools, education campuses, high schools, and special education schools, as well as learning centers. This dataset does not include private or charter schools. School locations were identified from a database from the District of Columbia Public Schools, Office of Facilities Management.

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 Master Address Repository (MAR) is a complex and widely accessed database that is increasingly being accessed by many DC Government applications. For such a widely used databases, it is important to have high quality documentation readily accessible. As a result, this document contains the table definitions for the most important views, tables and feature classes within the MAR.

About this dataset

Context

The dataset tabulates the District of Columbia population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for District of Columbia. The dataset can be utilized to understand the population distribution of District of Columbia by age. For example, using this dataset, we can identify the largest age group in District of Columbia.

Key observations

The largest age group in District of Columbia, DC was for the group of age 30 to 34 years years with a population of 76,902 (11.44%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in District of Columbia, DC was the 85 years and over years with a population of 9,859 (1.47%). 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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the District of Columbia is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of District of Columbia 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 District of Columbia Population by Age. You can refer the same here

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.

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.

This template covers section 2.5 Resource Fields: Entity and Attribute Information of the Data Discovery Form cited in the Open Data DC Handbook (2022). It completes documentation elements that are required for publication. Each field column (attribute) in the dataset needs a description clarifying the contents of the column. Data originators are encouraged to enter the code values (domains) of the column to help end-users translate the contents of the column where needed, especially when lookup tables do not exist.