100+ datasets found
  1. Address Ranges

    • hub.arcgis.com
    • azgeo-open-data-agic.hub.arcgis.com
    • +2more
    Updated Aug 30, 2024
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    GeoPlatform ArcGIS Online (2024). Address Ranges [Dataset]. https://hub.arcgis.com/datasets/c65cc7b0bd5b4c2b81da97b96a759b00
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    Dataset updated
    Aug 30, 2024
    Dataset provided by
    https://arcgis.com/
    Authors
    GeoPlatform ArcGIS Online
    Description

    Address ranges describe a label given to a unique collection of addresses that fall along a road or path. Address ranges provide a way of locating homes and businesses based on their street addresses when no other location information is available.Using a house number, street name, street side and ZIP code, address ranges can locate the address to the geographic area associated to that side of the street. Once geocoded, the U.S. Census Bureau can assign the address to a field assignment area or tabulate the data for that address. In addition, academics, researchers, professionals and government agencies outside of the Census Bureau use MAF/TIGER address ranges to transform tabular addresses into geographical datasets for decision-making and analytical purposes.Address ranges must be unique to geocode addresses to the correct location and avoid geocoding conflicts. Multiple elements in MAF/TIGER are required to make an address range unique including street names, address house numbers and street feature geometries, such as street centerlines. The address range data model is designed to maximize geocoding matches with their correct geographic areas in MAF/TIGER by allowing an unlimited number of address range-to-street feature relationships.The Census Bureau’s Geography Division devises numerous operations and processes to build and maintain high quality address ranges so that:Address ranges accurately describe the location of addresses on the ground.Address All possible city-style addresses are geocoded.Address ranges can handle all known address and street name variations.Address ranges conform with current U.S. Postal Service ZIP codes.Address ranges are reliable and free from conflicts.Automated software continually updates existing address ranges, builds new address ranges and corrects errors. An automated operation links address location points and tabular address information to street feature edges with matching street names in the same block to build and modify address ranges.Many business rules and legal value checks ensure quality address range data in MAF/TIGER. For example, business rules prevent adding or modifying address ranges that overlap another house number range with the same street name and ZIP code. Legal value checks verify that address ranges include mandatory attribute information, valid data types and valid character values.Some of the TIGER/Line products for the public include address ranges and give the public the ability to geocode addresses to MAF/TIGER address ranges for the user’s own purpose. The address range files are available for the nation, Puerto Rico and the U.S. Island Areas at the county level. TIGER/Line files require geographic information system (GIS) software to use.The Census Bureau Geocoder Service is a web service provided to the public. The service accepts up to 1,000 input addresses and, based on Census address ranges, returns the interpolated geocoded location and census geographies. Users can access the service a web interface or a representational state transfer (REST) application program interface (API) web service. See the Census Geocoder for more information on this process. Directions on how to use the Census Geocoder available: Geocoding Services Web Application Programming Interface (API)Download: https://www2.census.gov/geo/tiger/TGRGDB24/tlgdb_2024_a_us_addr.gdb.zip

  2. TIGER/Line Shapefile, 2020, County, Imperial County, CA, Topological Faces...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Jan 28, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2020, County, Imperial County, CA, Topological Faces (Polygons With All Geocodes) [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2020-county-imperial-county-ca-topological-faces-polygons-with-all-geocode
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    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://www.commerce.gov/
    Area covered
    Imperial County, California
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile 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 all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. 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.

  3. d

    Geocoded Medicaid office locations in the United States

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Mar 6, 2024
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    Shafer, Paul; Palmer, Maxwell; Cho, Ahyoung; Lynch, Mara; Louis, Pierce; Skinner, Alexandra (2024). Geocoded Medicaid office locations in the United States [Dataset]. http://doi.org/10.7910/DVN/AVRHMI
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    Dataset updated
    Mar 6, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    Shafer, Paul; Palmer, Maxwell; Cho, Ahyoung; Lynch, Mara; Louis, Pierce; Skinner, Alexandra
    Time period covered
    Aug 1, 2023 - Dec 19, 2023
    Area covered
    United States
    Description

    Big “p” policy changes at the state and federal level are certainly important to health equity, such as eligibility for and generosity of Medicaid benefits. Medicaid expansion has significantly expanded the number of people who are eligible for Medicaid and the creation of the health insurance exchanges (Marketplace) under the Affordable Care Act created a very visible avenue through which people can learn that they are eligible. Although many applications are now submitted online, physical access to state, county, and tribal government Medicaid offices still plays a critical role in understanding eligibility, getting help in applying, and navigating required documentation for both initial enrollment and redetermination of eligibility. However, as more government functions have moved online, in-person office locations and/or staff may have been cut to reduce costs, and gentrification has shifted where minoritized, marginalized, and/or low-income populations live, it is unclear if this key local connection point between residents and Medicaid has been maintained. Our objective was to identify and geocode all Medicaid offices in the United States for pairing with other spatial data (e.g., demographics, Medicaid participation, health care use, health outcomes) to investigate policy-relevant research questions. Three coders identified Medicaid office addresses in all 50 states and the District of Columbia by searching state government websites (e.g., Department of Health and Human Services or analogous state agency) during late 2021 and early 2022 for the appropriate Medicaid agency and its office locations, which were then reviewed for accuracy by a fourth coder. Our corpus of Medicaid office addresses was then geocoded using the Census Geocoder from the US Census Bureau (https://geocoding.geo.census.gov/geocoder/) with unresolved addresses investigated and/or manually geocoded using Google Maps. The corpus was updated in August through December 2023 following the end of the COVID-19 public health emergency by a fifth coder as several states closed and/or combined offices during the pandemic. After deduplication (e.g., where multiple counties share a single office) and removal of mailing addresses (e.g., PO Boxes), our dataset includes 3,027 Medicaid office locations. 1 (December 19, 2023) – original version 2 (January 25, 2024) – added related publication (Data in Brief), corrected two records that were missing negative signs in longitude 3 (February 6, 2024) – corrected latitude and longitude for one office (1340 State Route 9, Lake George, NY 12845) 4 (March 4, 2024) – added one office for Vermont after contacting relevant state agency (280 State Road, Waterbury, VT 05671)

  4. f

    Estimated Cohen’s Kappa and percent disagreement of census tract and block...

    • plos.figshare.com
    xls
    Updated Jan 31, 2025
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    Tyler Schappe; Lisa M. McElroy; Moronke Ogundolie; Roland Matsouaka; Ursula Rogers; Nrupen A. Bhavsar (2025). Estimated Cohen’s Kappa and percent disagreement of census tract and block group Federal Information Processing Standards (FIPS) assignments resulting from DeGAUSS and vendor tool geocoding process, stratified by urban/rural category. [Dataset]. http://doi.org/10.1371/journal.pone.0317215.t003
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    xlsAvailable download formats
    Dataset updated
    Jan 31, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Tyler Schappe; Lisa M. McElroy; Moronke Ogundolie; Roland Matsouaka; Ursula Rogers; Nrupen A. Bhavsar
    License

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

    Description

    Estimated Cohen’s Kappa and percent disagreement of census tract and block group Federal Information Processing Standards (FIPS) assignments resulting from DeGAUSS and vendor tool geocoding process, stratified by urban/rural category.

  5. o

    Data from: The Census Place Project: A Method for Geolocating Unstructured...

    • openicpsr.org
    delimited
    Updated Sep 6, 2022
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    Enrico Berkes; Ezra Karger; Peter Nencka (2022). The Census Place Project: A Method for Geolocating Unstructured Place Names [Dataset]. http://doi.org/10.3886/E179401V2
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    delimitedAvailable download formats
    Dataset updated
    Sep 6, 2022
    Dataset provided by
    Ohio State University
    Miami University
    Chicago Federal Reserve Bank
    Authors
    Enrico Berkes; Ezra Karger; Peter Nencka
    License

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

    Description

    Researchers use microdata to study the economic development of the United States and the causal effects of historical policies. Much of this research focuses on county- and state-level patterns and policies because comprehensive sub-county data is not consistently available. We describe a new method that geocodes and standardizes the towns and cities of residence for individuals and households in decennial census microdata from 1790--1940. We release public crosswalks linking individuals and households to consistently-defined place names, longitude-latitude pairs, counties, and states. Our method dramatically increases the number of individuals and households assigned to a sub-county location relative to standard publicly available data: we geocode an average of 83% of the individuals and households in 1790--1940 census microdata, compared to 23% in widely-used crosswalks. In years with individual-level microdata (1850--1940), our average match rate is 94% relative to 33% in widely-used crosswalks. To illustrate the value of our crosswalks, we measure place-level population growth across the United States between 1870 and 1940 at a sub-county level, confirming predictions of Zipf's Law and Gibrat's Law for large cities but rejecting similar predictions for small towns. We describe how our approach can be used to accurately geocode other historical datasets.

  6. TIGER/Line Shapefile, 2020, County, Montrose County, CO, Topological Faces...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Jan 28, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2020, County, Montrose County, CO, Topological Faces (Polygons With All Geocodes) [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2020-county-montrose-county-co-topological-faces-polygons-with-all-geocode
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    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Montrose County
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile 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 all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. 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.

  7. TIGER/Line Shapefile, 2020, County, Canadian County, OK, Topological Faces...

    • datasets.ai
    • s.cnmilf.com
    • +1more
    55, 57
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    U.S. Census Bureau, Department of Commerce, TIGER/Line Shapefile, 2020, County, Canadian County, OK, Topological Faces (Polygons With All Geocodes) [Dataset]. https://datasets.ai/datasets/tiger-line-shapefile-2020-county-canadian-county-ok-topological-faces-polygons-with-all-geocode
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    57, 55Available download formats
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau, Department of Commerce
    Area covered
    Canadian County, Oklahoma
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile 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 all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. 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.

  8. d

    Postal Code Conversion File [Canada], November 2019, Census of Canada 2016

    • search.dataone.org
    • borealisdata.ca
    Updated Dec 11, 2024
    + more versions
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    Statistics Canada. Geography Division (2024). Postal Code Conversion File [Canada], November 2019, Census of Canada 2016 [Dataset]. http://doi.org/10.5683/SP3/2TSJOQ
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    Dataset updated
    Dec 11, 2024
    Dataset provided by
    Borealis
    Authors
    Statistics Canada. Geography Division
    Area covered
    Canada
    Description

    The Postal Code Conversion File (PCCF) is a digital file which provides a correspondence between the Canada Post Corporation (CPC) six-character postal code and Statistics Canada's standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes. To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution. The geographic coordinates attached to each postal code on the PCCF are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for planning, or research purposes. The geographic coordinates, which represent the standard geostatistical areas linked to each postal codeOM on the PCCF, are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for marketing, planning, or research purposes. In April 1983, the Statistical Registers and Geography Division released the first version of the PCCF, which linked postal codesOM to 1981 Census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect changes. For this release of the PCCF, the vast majority of the postal codesOM are directly geocoded to 2016 Census geography while others are linked via various conversion processes. A quality indicator for the confidence of this linkage is available in the PCCF.

  9. TIGER/Line Shapefile, 2020, County, Defiance County, OH, Topological Faces...

    • datasets.ai
    • s.cnmilf.com
    • +2more
    55, 57
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    U.S. Census Bureau, Department of Commerce, TIGER/Line Shapefile, 2020, County, Defiance County, OH, Topological Faces (Polygons With All Geocodes) [Dataset]. https://datasets.ai/datasets/tiger-line-shapefile-2020-county-defiance-county-oh-topological-faces-polygons-with-all-geocode
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    57, 55Available download formats
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau, Department of Commerce
    Area covered
    Ohio, Defiance County
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile 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 all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. 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.

  10. TIGER/Line Shapefile, 2022, County, Rockland County, NY, Topological Faces...

    • catalog.data.gov
    Updated Jan 28, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Rockland County, NY, Topological Faces (Polygons With All Geocodes) [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2022-county-rockland-county-ny-topological-faces-polygons-with-all-geocode
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    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Department of Commercehttp://www.commerce.gov/
    United States Census Bureauhttp://census.gov/
    Area covered
    New York, Rockland County
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile 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 all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. 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.

  11. d

    Postal Code Conversion File [Canada], December 2017, Census of Canada 2016

    • dataone.org
    Updated Dec 28, 2023
    + more versions
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    Geography Division (2023). Postal Code Conversion File [Canada], December 2017, Census of Canada 2016 [Dataset]. http://doi.org/10.5683/SP3/KVTFUM
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Geography Division
    Area covered
    Canada
    Description

    Usage note: please be aware … Statistics Canada confirmed on May 10th, 2018, that a number of particular postal codesOM are missing in the December 2017 release of the PCCF, but was not able provide specifics about why these are missing. However, Statistics Canada checked each missing postal code against the newest internal release of the product, and they did exist in that file. The postal codesOM in question should be available in the August 2018 file. The Postal Code Conversion File (PCCF) is a digital file which provides a correspondence between the Canada Post Corporation (CPC) six-character postal code and Statistics Canada's standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes. Getting started guide To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution. The geographic coordinates attached to each postal code on the PCCF are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for planning, or research purposes. The geographic coordinates, which represent the standard geostatistical areas linked to each postal codeOM on the PCCF, are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for marketing, planning, or research purposes. In April 1983, the Statistical Registers and Geography Division released the first version of the PCCF, which linked postal codesOM to 1981 Census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect changes. For this release of the PCCF, the vast majority of the postal codesOM are directly geocoded to 2016 Census geography while others are linked via various conversion processes. A quality indicator for the confidence of this linkage is available in the PCCF.

  12. TIGER/Line Shapefile, 2020, County, Harrison County, IN, Topological Faces...

    • s.cnmilf.com
    • catalog.data.gov
    Updated Jan 27, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2020, County, Harrison County, IN, Topological Faces (Polygons With All Geocodes) [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/tiger-line-shapefile-2020-county-harrison-county-in-topological-faces-polygons-with-all-geocode
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    Dataset updated
    Jan 27, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://www.commerce.gov/
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile 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 all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. 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.

  13. TIGER/Line Shapefile, 2020, County, La Plata County, CO, Topological Faces...

    • s.cnmilf.com
    • catalog.data.gov
    Updated Jan 27, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2020, County, La Plata County, CO, Topological Faces (Polygons With All Geocodes) [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/tiger-line-shapefile-2020-county-la-plata-county-co-topological-faces-polygons-with-all-geocode
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    Dataset updated
    Jan 27, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://www.commerce.gov/
    Area covered
    La Plata County, Colorado
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile 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 all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. 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.

  14. f

    Results of likelihood ratio tests for differences in percent disagreement...

    • plos.figshare.com
    xls
    Updated Jan 31, 2025
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    Tyler Schappe; Lisa M. McElroy; Moronke Ogundolie; Roland Matsouaka; Ursula Rogers; Nrupen A. Bhavsar (2025). Results of likelihood ratio tests for differences in percent disagreement among strata of census tract and block group assignments between DeGAUSS and vendor tool geocoding. [Dataset]. http://doi.org/10.1371/journal.pone.0317215.t002
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    xlsAvailable download formats
    Dataset updated
    Jan 31, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Tyler Schappe; Lisa M. McElroy; Moronke Ogundolie; Roland Matsouaka; Ursula Rogers; Nrupen A. Bhavsar
    License

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

    Description

    Results of likelihood ratio tests for differences in percent disagreement among strata of census tract and block group assignments between DeGAUSS and vendor tool geocoding.

  15. TIGER/Line Shapefile, 2023, County, Franklin County, VT, Topological Faces...

    • datasets.ai
    • s.cnmilf.com
    • +1more
    55, 57
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    U.S. Census Bureau, Department of Commerce, TIGER/Line Shapefile, 2023, County, Franklin County, VT, Topological Faces (Polygons With All Geocodes) [Dataset]. https://datasets.ai/datasets/tiger-line-shapefile-2023-county-franklin-county-vt-topological-faces-polygons-with-all-geocode
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    57, 55Available download formats
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau, Department of Commerce
    Area covered
    Franklin County, Vermont
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile 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 all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. 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.

  16. d

    Postal Code Conversion File [Canada], November 2001, Census of Canada 1996

    • search.dataone.org
    • borealisdata.ca
    Updated Dec 18, 2024
    + more versions
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    Statistics Canada. Geography Division (2024). Postal Code Conversion File [Canada], November 2001, Census of Canada 1996 [Dataset]. http://doi.org/10.5683/SP3/TXHY85
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    Dataset updated
    Dec 18, 2024
    Dataset provided by
    Borealis
    Authors
    Statistics Canada. Geography Division
    Area covered
    Canada
    Description

    The Postal Code Conversion File (PCCF) is a digital file which provides a correspondence between the Canada Post Corporation (CPC) six-character postal code and Statistics Canada's standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes. The geographic coordinates attached to each postal code on the PCCF are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for planning, or research purposes. In April 1983, the Geography Division released the first version of the Postal Code Conversion File, which linked postal codes to census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect postal code changes provided by Canada Post Corporation. Every five years, the postal code linkages on the Postal Code Conversion File are “converted” to the latest census geographic areas. The original Postal Code Conversion File was linked to the 1981 Census geographic areas. Since then, the Postal Code Conversion File has undergone four “conversions”, following the 1986, 1991 and 1996 censuses. An automated system was used for the 1991-1996 conversion. Also, for the first time, the 1996 Census reported postal codes were used to validate the PCCF links. To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution.

  17. TIGER/Line Shapefile, 2023, County, Leelanau County, MI, Topological Faces...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Dec 15, 2023
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2023). TIGER/Line Shapefile, 2023, County, Leelanau County, MI, Topological Faces (Polygons With All Geocodes) [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2023-county-leelanau-county-mi-topological-faces-polygons-with-all-geocode
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    Dataset updated
    Dec 15, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Michigan, Leelanau County
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile 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 all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. 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.

  18. d

    Postal Code Conversion File [Canada], September 2008, Census of Canada 2006

    • search.dataone.org
    • borealisdata.ca
    Updated Dec 18, 2024
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    Geography Division (2024). Postal Code Conversion File [Canada], September 2008, Census of Canada 2006 [Dataset]. http://doi.org/10.5683/SP3/FOZXZR
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    Dataset updated
    Dec 18, 2024
    Dataset provided by
    Borealis
    Authors
    Geography Division
    Area covered
    Canada
    Description

    The Postal Code Conversion File (PCCF) is a digital file which provides a correspondence between the Canada Post Corporation (CPC) six-character postal code and Statistics Canada's standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes. Getting started guide To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution. The geographic coordinates attached to each postal code on the PCCF are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for planning, or research purposes. In April 1983, the Geography Division released the first version of the PCCF, which linked postal codes to 1981 Census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect changes. For this release of the PCCF, the vast majority of the postal codes are directly geocoded to 2006 Census geography. This improves precision of the file over the previous conversion process used to align postal code linkages to new geographic areas after each census. About 94% of the postal codes were linked to geographic areas using the new automated process. A quality indicator for the confidence of this linkage is available in the PCCF.

  19. d

    Postal Code Conversion File [Canada], June 2022, Census of Canada 2021

    • search.dataone.org
    Updated Dec 11, 2024
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    Statistics Canada. Geography Division (2024). Postal Code Conversion File [Canada], June 2022, Census of Canada 2021 [Dataset]. http://doi.org/10.5683/SP3/VUSYDJ
    Explore at:
    Dataset updated
    Dec 11, 2024
    Dataset provided by
    Borealis
    Authors
    Statistics Canada. Geography Division
    Area covered
    Canada
    Description

    The Postal Code Conversion File (PCCF) is a digital file which provides a correspondence between the Canada Post Corporation (CPC) six-character postal code and Statistics Canada's standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes. To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution. New to the June 2022 version, a separate data file is available for retired postal codes. The retired file uses the same record layout as the PCCF file. The same syntax file can be used for both the PCCF data file and the retired data file. The geographic coordinates attached to each postal code on the PCCF are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for planning, or research purposes. The geographic coordinates, which represent the standard geostatistical areas linked to each postal codeOM on the PCCF, are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for marketing, planning, or research purposes. In April 1983, the Statistical Registers and Geography Division released the first version of the PCCF, which linked postal codesOM to 1981 Census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect changes. For this release of the PCCF, the vast majority of the postal codesOM are directly geocoded to 2016 Census geography while others are linked via various conversion processes. A quality indicator for the confidence of this linkage is available in the PCCF.

  20. TIGER/Line Shapefile, 2020, County, Franklin County, VT, Topological Faces...

    • datasets.ai
    • s.cnmilf.com
    • +1more
    55, 57
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    U.S. Census Bureau, Department of Commerce, TIGER/Line Shapefile, 2020, County, Franklin County, VT, Topological Faces (Polygons With All Geocodes) [Dataset]. https://datasets.ai/datasets/tiger-line-shapefile-2020-county-franklin-county-vt-topological-faces-polygons-with-all-geocode
    Explore at:
    55, 57Available download formats
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau, Department of Commerce
    Area covered
    Franklin County, Vermont
    Description

    The TIGER/Line shapefiles and related database files (.dbf) 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 shapefile 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 all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. 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.

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GeoPlatform ArcGIS Online (2024). Address Ranges [Dataset]. https://hub.arcgis.com/datasets/c65cc7b0bd5b4c2b81da97b96a759b00
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Address Ranges

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Dataset updated
Aug 30, 2024
Dataset provided by
https://arcgis.com/
Authors
GeoPlatform ArcGIS Online
Description

Address ranges describe a label given to a unique collection of addresses that fall along a road or path. Address ranges provide a way of locating homes and businesses based on their street addresses when no other location information is available.Using a house number, street name, street side and ZIP code, address ranges can locate the address to the geographic area associated to that side of the street. Once geocoded, the U.S. Census Bureau can assign the address to a field assignment area or tabulate the data for that address. In addition, academics, researchers, professionals and government agencies outside of the Census Bureau use MAF/TIGER address ranges to transform tabular addresses into geographical datasets for decision-making and analytical purposes.Address ranges must be unique to geocode addresses to the correct location and avoid geocoding conflicts. Multiple elements in MAF/TIGER are required to make an address range unique including street names, address house numbers and street feature geometries, such as street centerlines. The address range data model is designed to maximize geocoding matches with their correct geographic areas in MAF/TIGER by allowing an unlimited number of address range-to-street feature relationships.The Census Bureau’s Geography Division devises numerous operations and processes to build and maintain high quality address ranges so that:Address ranges accurately describe the location of addresses on the ground.Address All possible city-style addresses are geocoded.Address ranges can handle all known address and street name variations.Address ranges conform with current U.S. Postal Service ZIP codes.Address ranges are reliable and free from conflicts.Automated software continually updates existing address ranges, builds new address ranges and corrects errors. An automated operation links address location points and tabular address information to street feature edges with matching street names in the same block to build and modify address ranges.Many business rules and legal value checks ensure quality address range data in MAF/TIGER. For example, business rules prevent adding or modifying address ranges that overlap another house number range with the same street name and ZIP code. Legal value checks verify that address ranges include mandatory attribute information, valid data types and valid character values.Some of the TIGER/Line products for the public include address ranges and give the public the ability to geocode addresses to MAF/TIGER address ranges for the user’s own purpose. The address range files are available for the nation, Puerto Rico and the U.S. Island Areas at the county level. TIGER/Line files require geographic information system (GIS) software to use.The Census Bureau Geocoder Service is a web service provided to the public. The service accepts up to 1,000 input addresses and, based on Census address ranges, returns the interpolated geocoded location and census geographies. Users can access the service a web interface or a representational state transfer (REST) application program interface (API) web service. See the Census Geocoder for more information on this process. Directions on how to use the Census Geocoder available: Geocoding Services Web Application Programming Interface (API)Download: https://www2.census.gov/geo/tiger/TGRGDB24/tlgdb_2024_a_us_addr.gdb.zip

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