AndreaBozzo/ceres-open-data-index huggingface dataset:
ACS 1-Year Social Characteristics DC

<div style='text-align:Left;'><div><div><p><span>Household type, Education, Disability, Language, Computer/Internet Use, and more. This service is updated annually with American Community Survey (ACS) 1-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: District-wide. </span><strong>Current Vintage: 2023. ACS Table(s): DP02. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025</strong><span>. 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.</span></p></div></div></div>

Tags: acs, american-community-survey, dc, district-of-columbia, district-wide, social-characteristics, washington-dc
Organization: District of Columbia
ACS 5-Year Demographic Characteristics DC

<div style='text-align:Left;'><div><div><p><span>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. </span><strong>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</strong><span>. 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.</span></p></div></div></div>

Tags: acs, american-community-survey, dc, demographic-characteristics, district-of-columbia, district-wide, washington-dc
Organization: District of Columbia
ACS 1-Year Business Characteristics DC

<div style='text-align:Left;'><div><div><p><span>This layer contains data on the number of employees and the number of establishments for selected 2-digit North American Industry Classification System (NAICS) codes from the the United States Census Bureau's County Business Patterns Program (CBP). This is shown by District boundaries. The full CBP data set (available at census.gov) is updated annually to contain the most currently released CBP data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. </span><strong>Current Vintage: 2022 CBP Table: CB2000CBP. Data downloaded from: Census Bureau's API for County Business Patterns. Date of API call: January 2, 2025</strong><span>. Please cite the Census Bureau and CBP when using this data. Data Processing Notes: Boundaries come from the US Census Bureau 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 Bureau. Downloaded data processed by the Office of Planning on R statistical software and ESRI ArcGIS Desktop. Blank values represent industries where there either were no businesses in that industry and that geography OR industries where the data had to be withheld to avoid disclosing data for individual companies. Users should visit data.census.gov for details on these withheld records.</span></p></div></div></div>

Tags: acs, american-community-survey, business-characteristics, dc, district-of-columbia, district-wide, washington-dc
Organization: District of Columbia
Floodplains Outline from 2023

<div style="text-align:Left;"><div><div><p><span>The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs.</span></p><p><span>The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA.</span></p><p><span>The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set.</span></p><p><span>The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Datum of 1983.For more information, visit </span><a target="_blank" rel="noopener noreferrer" href="https://msc.fema.gov/portal/home"><span><u>https://msc.fema.gov/portal/home</u></span></a><span>.</span></p></div></div></div>

Tags: dc, district-of-columbia, doee, environment-floodplain, fema, firm, insurance, washington-dc, water
Organization: District of Columbia
Census Tracts in 2000

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for almost all geographic areas for which the Census Bureau tabulates data for both the 2010 Census and Census 2000. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

Tags: 1-percent-public-use-microdata-area-code, 106th-congressional-district-code, 108th-congressional-district-code, 11001, 3-digit-zip-code-tabulation-area-code, 5-digit-zip-code-tabulation-area-code, 5-percent-public-use-microdata-area-code, alaska-native-regional-corporation-fips-code, american-indian-alaska-native-native-hawaiian-areas-census-code, block-group, boundaries, census-tract-number, consolidated-city-fips-code, county-fips-code, county-or-equivalent-entity, county-subdivision-fips-code, district-of-columbia, elementary-school-district-local-education-agency-code, fips-55-place-code-for-all-places, land-water-flag, legislative-session-year, metropolitan-statistical-area-consolidated-metropolitan-statistical-area-fips-code, new-england-county-metropolitan-area-fips-code, number, primary-metropolitan-statistical-area-fips-code, rreservation-or-off-reservation-trust-land-indicator, secondary-school-district-local-education-agency-code, state-fips-code, state-legislative-district-lower-chamber-code, state-legislative-district-upper-chamber-code, sub-minor-civil-division-fips-code-in-puerto-rico, table, tabulation-block-number, topological-faces, traffic-analysis-zone-code, tribal-subdivision-code, u-s, unified-school-district-local-education-agency-code, united-states, urban-area-code, urban-growth-area-code, voting-district-code
Organization: District of Columbia
2004 LiDAR - First Return

<p><span style='font-family:&quot;Avenir Next&quot;,serif; color:black; background:white;'>First Return Light Detection and
Ranging (LIDAR) Data - 1m resolution. The dataset contains locations and
attributes of first return elevations in meters.  LIDAR data provided by
the Joint Precision Strike Demonstration Project Office of the US Army
contained bare earth rasters.  This raster contains elevations of all
structures, tree canopies, and bare earth. The first Lidar return reflects the highest elevations of ground features such as tree canopy, buildings, power lines, etc.</span></p>

Tags: district-of-colubia, elevation, first-return, imagery, lidar, washington-dc
Organization: District of Columbia
2008 LiDAR – Bare Earth

<p><span style='font-family:&quot;Avenir Next&quot;,serif; color:#4C4C4C; background:white;'>Bare Earth Light Detection and Ranging (LIDAR) Data - 1m
resolution. The dataset contains locations and attributes of bare earth
elevations in meters.  Bare earth model is created by identifying those
returns that fall on the ground surface and interpolating a surface between
these points.  In this manner buildings and vegetation are removed from
Bare Earth Model.   This data set does not include bridges and overpasses
in the Bare Earth model as the delineation point for these structures is not
reliably discernable in the LiDAR data.</span></p>

Tags: bare-earth, district-of-columbia, elevation, imagery, lidar, washington-dc
Organization: District of Columbia
2008 LiDAR - Last Return

<p><span style='font-family:&quot;Avenir Next&quot;,serif; color:#4C4C4C; background:white;'>2008 Last Return Light Detection and Ranging (LIDAR) Data for
Washington, DC at 1 meter resolution. The last Lidar return reflects the ground level, from which a bald-earth dataset can be extracted.</span></p>

Tags: district-of-columbia, elevation-data, imagery, last-return, lidar, washington-dc
Organization: District of Columbia
DC Estimated Tree Root Zone (Critical) 2020

<font face='Avenir Next W01, Avenir Next W00, Avenir Next, Avenir, Helvetica Neue, sans-serif'><span style='font-size:16px;'>The dataset is the estimate of a tree’s critical root zone, which can not be impacted beyond certain limits. Buffer distances are calculated for trees on all land types in the District that will be used for tree preservation planning purposes.</span></font>

Tags: crz, ddot-urban-forestry-division, root-zone, srz, tree-preservation, tree-protection, ufa
Organization: District of Columbia
2018 LiDAR - Hydro Enforced Digital Terrain Model

<div style='text-align:Left;'><div><div><p><span>The hydro-flattened bare earth DEM was generated using the 2018 DC lidar bare earth points and 3D hydro breaklines to a resolution of 1 m. The bare earth points that fell within 1NPS along the hydro breaklines were excluded from the DEM generation process and put into class 20 – ignored ground. This is analogous to the removal of mass points for the same reason in a traditional photogrammetrically compiled DTM. This process was done in batch using proprietary software. The technicians then used proprietary software for the production of the lidar-derived hydro-flattened bare earth DEM surface in initial grid format at 1 m GSD. Water bodies (inland ponds and lakes), inland streams and rivers, and island holes were hydro-flattened within the DEM. Once the initial, hydro-flattened bare earth DEM was generated, the tiles were checked to ensure that the grid spacing met specifications. The surface was also checked to ensure proper hydro-flattening.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 compressed GeoTIFF raster dataset is available under additional options when viewing downloads.</span></p></div></div></div>

Tags: bare-earth, dc, dem, digital-elevation-model, district-of-columbia, dtm, elevation, hydro-enforced, hydro-flattened, lidar, lidar2018, washington-dc
Organization: District of Columbia
Bank Locations

<div style='text-align:Left;'><div><div><p><span>The Banking Bureau of the Department of Insurance Securities and Banking (DISB) regulates District of Columbia Chartered Banks, mortgage companies, and consumer finance companies. The Bureau strives to ensure a sound and thriving financial services community that provides the products, credit, and capital vital to the needs of District of Columbia residents and businesses. DISB charters and regulates District of Columbia banks and other DC depository financial institutions. DISB also regulates non-depository financial institutions such as mortgage lenders and brokers, money transmitters, consumer finance companies, and check cashers. The data is updated as needed. </span></p></div></div></div>

Tags: atm, banking, business, disb, district-of-columbia, economic, funds, insurance, money, savings, securities, washington-dc
Organization: District of Columbia
Hospital Areas

<div style='text-align:Left;'><div><div><p><span>Hospitals Areas. This dataset contains hospital areas extracted from the DC property layers. These areas of the District of Columbia hospitals, 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.</span></p></div></div></div>

Tags: care, d-c, dc, dc-gis, dcgis, district-of-columbia, health, health-care, health-facility, hospital, hospitals, june2015, open-data, washington, washington-dc
Organization: District of Columbia
DC Estimated Tree Root Zone (Structural)

The dataset is the estimate of a tree’s structural  root zone, which must not be impacted during construction. Buffer distances are calculated for trees on all land types in the District that will be used for tree preservation planning purposes.<div><p><a href='https://opendata.dc.gov/datasets/da0c156ef3d24607b27a0da418970eac/explore' target='_blank' rel='nofollow ugc noopener noreferrer'>DC 2022 LiDAR</a><span> was used and processed using the “Extract Trees using Cluster Analysis” script which is included as part of Esri’s 3D Basemap solution.</span> </p><p>The
extracted tree data set was merged with the UFA tree inventory data, with
preference given to the UFA tree inventory data. All LiDAR-derived trees within
2 meters of a UFA tree were removed as being duplicates. <br /></p>

<p>Tree
diameter (DBH, in inches) was estimated for the LiDAR-derived trees from
calculated tree height (in feet) based on the equation: DBH = 0.4003*height -
1.9557. This equation was derived from a statistical analysis of a detailed
park inventory tree data set and has an R^2 = 0.7418.</p><p>Extreme
outliers were also modified, with any DBH larger than 80 inches being converted
to a DBH of 80 inches.<br /></p><p>Critical
Root Zone (CRZ) was calculated as a buffer of 1.5 feet for every inch of DBH,
whereas Structural Root Zone (SRZ) was calculated as a buffer of 0.5 feet for
every inch of DBH.<br /></p><br /></div>

Tags: crz, ddot-urban-forestry-division, root-zone, srz, tree-preservation, tree-protection, ufa
Organization: District of Columbia
Post Offices

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The dataset contains locations and attributes of Post Offices, 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. Information provided by the United States Postal Service (USPS) and DC GIS staff geo-processed the data.</SPAN></P></DIV></DIV></DIV>

Tags: cultural, district-of-columbia, open-data, public-service, society, washington-dc
Organization: District of Columbia
2022 LiDAR - Normalized Digital Surface Model

<div style='text-align:Left;'><div><p><span>Normalized Digital Surface Model - 1m resolution. The dataset contains the 1m Normalized Digital Surface Model for the District of Columbia. Some areas have limited data. The lidar dataset redaction was conducted under the guidance of the United States Secret Service. All data returns were removed from the dataset within the United States Secret Service redaction boundary except for classified ground points and classified water points.</span></p></div></div>

Tags: bare-earth, district-of-columbia, elevation, lidar, lidar2022, ndsm, normalized-digital-surface-model, washington-dc
Organization: District of Columbia
2018 LiDAR - Normalized Digital Surface Model

<div style='text-align:Left;'><div><div><p><span>Normalized Digital Surface Model - 1m resolution. The dataset contains the Normalized Digital Surface Model for the Washington Area. Voids exist in the data due to data redaction conducted under the guidance of the United States Secret Service. All lidar data returns and collected data were removed from the dataset based on the redaction footprint shapefile generated in 2017. 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 compressed GeoTIFF raster dataset is available under additional options when viewing downloads.</span></p></div></div></div>

Tags: bare-earth, dc, dem, digital-elevation-model, digital-surface-model, district-of-columbia, elevation, lidar, lidar2018, ndsm, washington-dc
Organization: District of Columbia
2018 LiDAR - Digital Surface Model

<div style='text-align:Left;'><div><div><p><span>Digital Surface Model - 1m resolution. The dataset contains the 1m Digital Surface Model for the Washington Area. Voids exist in the data due to data redaction conducted under the guidance of the United States Secret Service. All lidar data returns and collected data were removed from the dataset based on the redaction footprint shapefile generated in 2017. 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 compressed GeoTIFF raster dataset is available under additional options when viewing downloads.</span></p></div></div></div>

Tags: bare-earth, dc, dem, digital-elevation-model, digital-surface-model, district-of-columbia, dsm, elevation, lidar, lidar2018, washington-dc
Organization: District of Columbia
FOIA Legacy Crossover

<div style='text-align:Left;'><div><div><p><span>In the summer of 2024, the District of Columbia migrated its FOIA records management to a new system. This dataset houses the archived Freedom of Information Act (FOIA) requests to DC Government by various organizations and individuals - that have now closed since the June 14, 2024 migration. Their original details remain unchanged in the </span><a href='https://opendata.dc.gov/datasets/foia-legacy/about' style='text-decoration:underline;' rel='nofollow ugc'><span>FOIA Legacy</span></a><span> dataset, also found on Open Data DC.</span></p></div></div></div>

Tags: district-of-columbia, foia, freedom-of-information-act, government, operations, os, washington-dc
Organization: District of Columbia
2015 LiDAR – Bare Earth

Bare Earth Light Detection and Ranging (LIDAR) Data - 2 foot resolution. The dataset contains locations and attributes of bare earth elevations in meters.  Bare earth model is created by identifying those returns that fall on the ground surface and interpolating a surface between these points.  In this manner buildings and vegetation are removed from Bare Earth Model.  This data set does not include bridges and overpasses in the Bare Earth model as the delineation point for these structures is not reliably discernible in the LiDAR data. This metadata record describes the data products derived from the LiDAR data for the DC OCTO 2015 LiDAR project covering approximately 80 square miles, in which its extents cover Arlington County in Washington DC. This project consists of deliverables in accordance with USGS v1.2 specifications and meets or exceeds the level of quality for QL1 (8 points per meter).

Tags: bare-earth, elevation-data, imagery, lidar, washington-dc
Organization: District of Columbia