100+ datasets found
  1. C

    Property Data with Geographic Identifiers

    • data.wprdc.org
    • gimi9.com
    • +1more
    csv, zip
    Updated Jun 9, 2024
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    Western Pennsylvania Regional Data Center (2024). Property Data with Geographic Identifiers [Dataset]. https://data.wprdc.org/dataset/property-data-with-geographic-identifiers
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    csv, zip, csv(265867153)Available download formats
    Dataset updated
    Jun 9, 2024
    Dataset provided by
    Western Pennsylvania Regional Data Center
    License

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

    Description

    These datasets are clones of popular WPRDC datasets from various publishers that have been reverse-geocoded to add geographic identifiers (e.g., municipality and neighborhood).

    Follow the links in the file descriptions for more information on the original datasets.

    If you get a timeout error when trying to download either "Property Assessment Parcel Data" or "Property Assessment Data with Parcel Centroids", click on the Preview link and use the alternative download link (which should contain the term "downstream").

  2. D

    2020 Census Block Groups; PA, NJ, DE & MD

    • staging-catalog.cloud.dvrpc.org
    • catalog.dvrpc.org
    • +2more
    esri feature class +4
    Updated Feb 15, 2025
    + more versions
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    DVRPC (2025). 2020 Census Block Groups; PA, NJ, DE & MD [Dataset]. https://staging-catalog.cloud.dvrpc.org/dataset/2020-census-block-groups-pa-nj-de-md
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    esri feature class, geojson, html, xml, jsonAvailable download formats
    Dataset updated
    Feb 15, 2025
    Dataset authored and provided by
    DVRPC
    Area covered
    Pennsylvania, New Jersey
    Description

    *USE geoid TO JOIN DATA DOWNLOADED FROM DATA.CENSUS.GOV*

    The TIGER/Line Shapefiles are extracts of selected geographic and cartographic information from the Census Bureau's Master Address File (MAF)/Topologically Integrated Geographic Encoding and Referencing (TIGER) System (MTS).

    The TIGER/Line Shapefiles contain a standard geographic identifier (GEOID) for each entity that links to the GEOID in the data from censuses and surveys. The TIGER/Line Shapefiles do not include demographic data from surveys and censuses (e.g., Decennial Census, Economic Census, American Community Survey, and the Population Estimates Program). Other, non-census, data often have this standard geographic identifier as well. Data from many of the Census Bureau’s surveys and censuses, including the geographic codes needed to join to the TIGER/Line Shapefiles, are available at the Census Bureau’s public data dissemination website (https://data.census.gov/).

    Block Groups (BGs) are statistical divisions of census tracts, are generally defined to contain between 600 and 3,000 people, and are used to present data and control block numbering. A block group consists of clusters of blocks within the same census tract that have the same first digit of their four-digit census block number. For example, blocks 3001, 3002, 3003, . . . , 3999 in census tract 1210.02 belong to BG 3 in that census tract. Most BGs were delineated by local participants in the Census Bureau’s Participant Statistical Areas Program (PSAP). The Census Bureau delineated BGs only where a local or tribal government declined to participate in PSAP, and a regional organization or the State Data Center was not available to participate. A BG usually covers a contiguous area. Each census tract contains at least one BG, and BGs are uniquely numbered within the census tract. Within the standard census geographic hierarchy, BGs never cross state, county, or census tract boundaries, but may cross the boundaries of any other geographic entity. Tribal census tracts and tribal BGs are separate and unique geographic areas defined within federally recognized American Indian reservations and can cross state and county boundaries (see “Tribal Census Tract” and “Tribal Block Group”). The tribal census tracts and tribal block groups may be completely different from the standard county-based census tracts and block groups defined for the same area.

    Downloaded from https://www2.census.gov/geo/tiger/TIGER2022/BG/ on June 22, 2023

  3. D

    2020 Public Use Microdata Areas (PUMAs); PA, NJ, DE & MD

    • staging-catalog.cloud.dvrpc.org
    • catalog.dvrpc.org
    • +2more
    esri feature class +4
    Updated Feb 15, 2025
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    DVRPC (2025). 2020 Public Use Microdata Areas (PUMAs); PA, NJ, DE & MD [Dataset]. https://staging-catalog.cloud.dvrpc.org/dataset/2020-public-use-microdata-areas-pumas-pa-nj-de-md
    Explore at:
    html, geojson, json, esri feature class, xmlAvailable download formats
    Dataset updated
    Feb 15, 2025
    Dataset authored and provided by
    DVRPC
    Area covered
    Pennsylvania, New Jersey
    Description

    *USE geoid TO JOIN DATA DOWNLOADED FROM DATA.CENSUS.GOV*

    The TIGER/Line Shapefiles are extracts of selected geographic and cartographic information from the Census Bureau's Master Address File (MAF)/Topologically Integrated Geographic Encoding and Referencing (TIGER) System (MTS).

    The TIGER/Line Shapefiles contain a standard geographic identifier (GEOID) for each entity that links to the GEOID in the data from censuses and surveys. The TIGER/Line Shapefiles do not include demographic data from surveys and censuses (e.g., Decennial Census, Economic Census, American Community Survey, and the Population Estimates Program). Other, non-census, data often have this standard geographic identifier as well. Data from many of the Census Bureau’s surveys and censuses, including the geographic codes needed to join to the TIGER/Line Shapefiles, are available at the Census Bureau’s public data dissemination website (https://data.census.gov/).

    Public Use Microdata Areas (PUMAs) are statistical geographic areas for the dissemination of decennial census and American Community Survey (ACS) Public Use Microdata Sample files in which the Census Bureau provides selected extracts of raw data from a small sample of census records that are screened to protect confidentiality. The ACS also uses the PUMAs as a tabulation geographic entity.

    For the 2020 Census, the State Data Centers in each state, the District of Columbia, and Puerto Rico are involved in the delineation of the 2020 PUMAs. Counties and census tracts are used to define PUMAs, and each PUMA must include at least 100,000 people based on the 2020 Census published counts. For the 2020 Census in Guam and the U.S. Virgin Islands, the Census Bureau establishes a single, separate PUMA for each of these two Island Areas. American Samoa and the Commonwealth of the Northern Mariana Islands do not have PUMAs, because the total population of each is under 100,000 people.

    Downloaded from https://www2.census.gov/geo/tiger/TIGER2022/PUMA/ on June 22, 2023

  4. Geography Lookup API - by Geography ID

    • catalog.data.gov
    • datadiscoverystudio.org
    • +2more
    Updated Mar 11, 2021
    + more versions
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    National Telecommunication and Information Administration, Department of Commerce (2021). Geography Lookup API - by Geography ID [Dataset]. https://catalog.data.gov/dataset/geography-lookup-api-by-geography-id
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    Dataset updated
    Mar 11, 2021
    Dataset provided by
    United States Department of Commercehttp://www.commerce.gov/
    Description

    This API returns a geography of a specified geography type by the geography id.

  5. Census Data

    • catalog.data.gov
    • datadiscoverystudio.org
    • +3more
    Updated Mar 1, 2024
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    U.S. Bureau of the Census (2024). Census Data [Dataset]. https://catalog.data.gov/dataset/census-data
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    Dataset updated
    Mar 1, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.

  6. Next Steps: Sweep 9, 2022: Geographical Identifiers, 2021 Census Boundaries:...

    • beta.ukdataservice.ac.uk
    • datacatalogue.cessda.eu
    Updated 2025
    + more versions
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    UCL Institute Of Education University College London (2025). Next Steps: Sweep 9, 2022: Geographical Identifiers, 2021 Census Boundaries: Secure Access [Dataset]. http://doi.org/10.5255/ukda-sn-9337-1
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    Dataset updated
    2025
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    DataCitehttps://www.datacite.org/
    Authors
    UCL Institute Of Education University College London
    Description
    Next Steps (also known as the Longitudinal Study of Young People in England (LSYPE1)) is a major longitudinal cohort study following a nationally representative group of around 16,000 who were in Year 9 attending state and independent schools in England in 2004, a cohort born in 1989-90.

    The first seven sweeps of the study were conducted annually (2004-2010) when the study was funded and managed by the Department for Education (DfE). The study mainly focused on the educational and early labour market experiences of young people.

    In 2015 Next Steps was restarted, under the management of the Centre for Longitudinal Studies (CLS) at the UCL Faculty of Education and Society (IOE) and funded by the Economic and Social Research Council. The Next Steps Age 25 survey was aimed at increasing the understanding of the lives of young adults growing up today and the transitions out of education and into early adult life.

    The Next Steps Age 32 Survey took place between April 2022 and September 2023 and is the ninth sweep of the study. The Age 32 Survey aimed to provide data for research and policy on the lives of this generation of adults in their early 30s. This sweep also collected information on many wider aspects of cohort members' lives including health and wellbeing, politics and social participation, identity and attitudes as well as capturing personality, resilience, working memory and financial literacy.

    Next Steps survey data is also linked to the National Pupil Database (NPD), the Hospital Episode Statistics (HES), the Individualised Learner Records (ILR) and the Student Loans Company (SLC).

    There are now two separate studies that began under the LSYPE programme. The second study, Our Future (LSYPE2) (available at the UK Data Service under GN 2000110), began in 2013 and will track a sample of over 13,000 young people annually from ages 13/14 through to age 20.

    Further information about Next Steps may be found on the
    CLS website.

    Secure Access datasets:

    Secure Access versions of Next Steps have more restrictive access conditions than Safeguarded versions available under the standard End User Licence (see 'Access' section).

    Secure Access versions of the Next Steps include:

    • sensitive variables from the questionnaire data for Sweeps 1-9. These are available under Secure Access SN 8656.
    • National Pupil Database (NPD) linked data at Key Stages 2, 3, 4 and 5, England. These are available under SN 7104.
    • Linked Individualised Learner Records learner and learning aims datasets for academic years 2005 to 2014, England. These are available under SN 8577.
    • detailed geographic indicators for Sweep 1 and Sweep 8 (2001 Census Boundaries) are available under SN 8189, geographic indicators for Sweep 8 and 9 (2011 Census Boundaries) are available under SN 8190, and geographic indicators for Sweep 9 (2021 Census Boundaries) are available under SN 9337. The Sweep 1 geography file was previously held under SN 7104.
    • Linked Health Administrative Datasets (Hospital Episode Statistics) for financial years 1997-2022 held under SN 8681.
    • Linked Student Loans Company Records for years 2007-2021 held under SN 8848.

    When researchers are approved/accredited to access a Secure Access version of Next Steps, the Safeguarded (EUL) version of the study - Next Steps: Sweeps 1-9, 2004-2023 (SN 5545) - will be automatically provided alongside.

    Users are only allowed one of the three Geographical Identifiers Census Boundaries studies: SN 8189 (2001 Census Boundaries), SN 8190 (2011 Census Boundaries), or SN 9337 (2021 Census Boundaries).

    International Data Access Network (IDAN)
    These data are now available to researchers based outside the UK. Selected UKDS SecureLab/controlled datasets from the Institute for Social and Economic Research (ISER) and the Centre for Longitudinal Studies (CLS) have been made available under the International Data Access Network (IDAN) scheme, via a Safe Room access point at one of the UKDS IDAN partners. Prospective users should read the UKDS SecureLab application guide for non-ONS data for researchers outside of the UK via Safe Room Remote Desktop Access. Further details about the IDAN scheme can be found on the UKDS International Data Access Network webpage and on the IDAN website.

  7. California County Boundaries and Identifiers

    • data.ca.gov
    • gis.data.ca.gov
    Updated Mar 4, 2025
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    California Department of Technology (2025). California County Boundaries and Identifiers [Dataset]. https://data.ca.gov/dataset/california-county-boundaries-and-identifiers
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    arcgis geoservices rest api, xlsx, zip, geojson, html, kml, gdb, csv, gpkg, txtAvailable download formats
    Dataset updated
    Mar 4, 2025
    Dataset authored and provided by
    California Department of Technologyhttp://cdt.ca.gov/
    Area covered
    California
    Description

    WARNING: This is a pre-release dataset and its fields names and data structures are subject to change. It should be considered pre-release until the end of March 2025. The schema changed in February 2025 - please see below. We will post a roadmap of upcoming changes, but service URLs and schema are now stable. For deployment status of new services in February 2025, see https://gis.data.ca.gov/pages/city-and-county-boundary-data-status. Additional roadmap and status links at the bottom of this metadata.

    This dataset is continuously updated as the source data from CDTFA is updated, as often as many times a month. If you require unchanging point-in-time data, export a copy for your own use rather than using the service directly in your applications.

    Purpose

    County boundaries along with third party identifiers used to join in external data. Boundaries are from the California Department of Tax and Fee Administration (CDTFA). These boundaries are the best available statewide data source in that CDTFA receives changes in incorporation and boundary lines from the Board of Equalization, who receives them from local jurisdictions for tax purposes. Boundary accuracy is not guaranteed, and though CDTFA works to align boundaries based on historical records and local changes, errors will exist. If you require a legal assessment of boundary location, contact a licensed surveyor.

    This dataset joins in multiple attributes and identifiers from the US Census Bureau and Board on Geographic Names to facilitate adding additional third party data sources. In addition, we attach attributes of our own to ease and reduce common processing needs and questions. Finally, coastal buffers are separated into separate polygons, leaving the land-based portions of jurisdictions and coastal buffers in adjacent polygons. This layer removes the coastal buffer polygons. This feature layer is for public use.

    Related Layers

    This dataset is part of a grouping of many datasets:

    1. Cities: Only the city boundaries and attributes, without any unincorporated areas
    2. Counties: Full county boundaries and attributes, including all cities within as a single polygon
    3. Cities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.
    4. City and County Abbreviations
    5. Unincorporated Areas (Coming Soon)
    6. Census Designated Places
    7. Cartographic Coastline
    Working with Coastal Buffers
    The dataset you are currently viewing excludes the coastal buffers for cities and counties that have them in the source data from CDTFA. In the versions where they are included, they remain as a second polygon on cities or counties that have them, with all the same identifiers, and a value in the COASTAL field indicating if it"s an ocean or a bay buffer. If you wish to have a single polygon per jurisdiction that includes the coastal buffers, you can run a Dissolve on the version that has the coastal buffers on all the fields except OFFSHORE and AREA_SQMI to get a version with the correct identifiers.

    Point of Contact

    California Department of Technology, Office of Digital Services, odsdataservices@state.ca.gov

    Field and Abbreviation Definitions

    • CDTFA_COUNTY: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.
    • CDTFA_COPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering system. The boundary data originate with CDTFA's teams managing tax rate information, so this field is preserved and flows into this dataset.
    • CENSUS_GEOID: numeric geographic identifiers from the US Census Bureau
    • CENSUS_PLACE_TYPE: City, County, or Town, stripped off the census name for identification purpose.
    • GNIS_PLACE_NAME: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information System
    • GNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.
    • CDT_COUNTY_ABBR: Abbreviations of county names - originally derived from CalTrans Division of Local Assistance and now managed by CDT. Abbreviations are 3 characters.
    • CDT_NAME_SHORT: The name of the jurisdiction (city or county) with the word "City" or "County" stripped off the end. Some changes may come to how we process this value to make it more consistent.
    • AREA_SQMI: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.
    • OFFSHORE: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".
    • PRIMARY_DOMAIN: Currently empty/null for all records. Placeholder field for official URL of the city or county
    • CENSUS_POPULATION: Currently null for all records. In the future, it will include the most recent US Census population estimate for the jurisdiction.
    • GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to support offline sync, but is not persistent, so data keyed to it will be orphaned at our next update. Use one of the other persistent identifiers, such as GNIS_ID or GEOID instead.

    Boundary Accuracy
    County boundaries were originally derived from a

  8. c

    Census Tracts in City of Rochester 2020

    • data.cityofrochester.gov
    Updated Dec 14, 2022
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    Open_Data_Admin (2022). Census Tracts in City of Rochester 2020 [Dataset]. https://data.cityofrochester.gov/datasets/d9566b49caa7470cacad1ef6569c3b6c
    Explore at:
    Dataset updated
    Dec 14, 2022
    Dataset authored and provided by
    Open_Data_Admin
    Area covered
    Description

    Dataset Summary About this data: This layer presents the USA 2020 Census tracts within the City of Rochester boundary. The geography is sourced from US Census Bureau 2020 TIGER FGDB (National Sub-State) and cut by the City of Rochester boundary. Data Dictionary: STATE_ABBR: The two-letter abbreviation for a state (such as NY). STATE_FIPS: The two-digit Federal Information Processing Standards (FIPS) code assigned to each US state. New York State is 36. COUNTY_FIP: The three-digit Federal Information Processing Standards (FIPS) code assigned to each US county. Monroe County is 055. STCO_FIPS: The five-digit Federal Information Processing Standards (FIPS) code assigned to iedntify a unique county, typically as a concatenation of the State FIPS code and the County FIPS code. TRACT_FIPS: The six-digit number assigned to each census tract in a US county. FIPS: A unique geographic identifier, typically as a concatenation of State FIPS code, County FIPS code, and Census tract code. POPULATION: The population of a census tract. POP_SQMI: The population per square mile of a census tract. SQMI: The size of a census tract in square miles. Division: The name of the City of Rochester data division that the census tract falls in to. Source: This data comes from the Census Bureau.

  9. a

    2020 Census Block Groups for King County / blkgrp20 area

    • hub.arcgis.com
    • gis-kingcounty.opendata.arcgis.com
    Updated Aug 19, 2021
    + more versions
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    King County (2021). 2020 Census Block Groups for King County / blkgrp20 area [Dataset]. https://hub.arcgis.com/datasets/78843014641f46dbb93718509befb694
    Explore at:
    Dataset updated
    Aug 19, 2021
    Dataset authored and provided by
    King County
    Area covered
    Description

    This layer contains a geographic identifier (GEO_ID_GRP) for each block group that is the key field for the data from censuses and surveys such as Decennial Census, Economic Census, American Community Survey, and the Population Estimates Program. Data from many of the Census Bureau’s surveys and censuses, are available at the Census Bureau’s public data dissemination website (https://data.census.gov/). All original TIGER/Line shapefiles and geodatabases with demographic data are available atThe TIGER/Line Shapefiles are extracts of selected geographic and cartographic information from the Census Bureau's Master Address File (MAF)/Topologically Integrated Geographic Encoding and Referencing (TIGER) Database (MTDB). The shapefiles include information for the fifty states, the District of Columbia, Puerto Rico, and the Island areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the United States Virgin Islands). The shapefiles include polygon boundaries of geographic areas and features, linear features including roads and hydrography, and point features. These shapefiles do not contain any sensitive data or confidential data protected by Title 13 of the U.S.C.Standard block groups are clusters of blocks within the same census tract that have the same first digit of their 4-character census block number (e.g., Blocks 3001, 3002, 3003 to 3999 in census tract 1210.02 belong to block group 3). Current block groups do not always maintain these same block number to block group relationships due to boundary and feature changes that occur throughout the decade. For example, block 3001 might move due to a change in the census tract boundary. Block groups delineated for the 2020 Census generally contain 600 to 3,000 people and a block group usually covers a contiguous area. Each census tract contains one or more block groups and block groups have unique numbers within census tract. Within the standard census geographic hierarchy, block groups never cross county or census tract boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and AIANNH areas.Block groups have a valid range of zero (0) through nine (9). Block groups beginning with a zero generally are in coastal and Great Lakes water and territorial seas. Rather than extending a census tract boundary into the Great Lakes or out to the 3-mile territorial sea limit, the Census Bureau delineated some census tract boundaries along the shoreline or just offshore. Full documentation: https://www2.census.gov/geo/pdfs/maps-data/data/tiger/tgrshp2020/TGRSHP2020_TechDoc.pdf

  10. O

    Census Tract 2010

    • data.sccgov.org
    Updated May 2, 2023
    + more versions
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    (2023). Census Tract 2010 [Dataset]. https://data.sccgov.org/dataset/Census-Tract-2010/nxaw-7ash
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    tsv, application/geo+json, application/rdfxml, csv, xml, application/rssxml, kml, kmzAvailable download formats
    Dataset updated
    May 2, 2023
    Description

    Census tract geometry within Santa Clara County from the 2010 Census Tiger shapefiles.Feature class derived from Tiger line shapefile of 2010 census tracts for Santa Clara County and geographic identifier table, G001. Some attribute names may be when exporting as shapefile due to 10 character limitation of shapefile attribute names. THE GIS DATA IS PROVIDED "AS IS". THE COUNTY MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION, ANY IMPLIED WARRANTIES OR MERCHANTABILITY AND/OR FITNESS FOR A PARTICULAR PURPOSE, REGARDING THE ACCURACY, COMPLETENESS, VALUE, QUALITY, VALIDITY, MERCHANTABILITY, SUITABILITY, AND CONDITION, OF THE GIS DATA. USER'S OF COUNTY'S GIS DATA ARE HEREBY NOTIFIED THAT CURRENT PUBLIC PRIMARY INFORMATION SOURCES SHOULD BE CONSULTED FOR VERIFICATION OF THE DATA AND INFORMATION CONTAINED HEREIN. SINCE THE GIS DATA IS DYNAMIC, IT WILL BY ITS NATURE BE INCONSISTENT WITH THE OFFICIAL COUNTY DATA. ANY USE OF COUNTY'S GIS DATA WITHOUT CONSULTING OFFICIAL PUBLIC RECORDS FOR VERIFICATION IS DONE EXCLUSIVELY AT THE RISK OF THE PARTY MAKING SUCH USE.

  11. a

    2020 Census Tracts for King County / tracts20 area

    • hub.arcgis.com
    • king-snocoplanning.opendata.arcgis.com
    • +1more
    Updated Aug 19, 2021
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    King County (2021). 2020 Census Tracts for King County / tracts20 area [Dataset]. https://hub.arcgis.com/datasets/0a4fb77d7dfd447da745b744c0a14bdc
    Explore at:
    Dataset updated
    Aug 19, 2021
    Dataset authored and provided by
    King County
    Area covered
    Description

    This layer contains a unique geographic identifier (GEO_ID_TRT) for each tract group that is the key field for the data from censuses and surveys such as Decennial Census, Economic Census, American Community Survey, and the Population Estimates Program. Data from many of the Census Bureau’s surveys and censuses, are available at the Census Bureau’s public data dissemination website (https://data.census.gov/). All original TIGER/Line shapefiles and geodatabases with demographic data are available atThe TIGER/Line Shapefiles are extracts of selected geographic and cartographic information from the Census Bureau's Master Address File (MAF)/Topologically Integrated Geographic Encoding and Referencing (TIGER) Database (MTDB). The shapefiles include information for the fifty states, the District of Columbia, Puerto Rico, and the Island areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the United States Virgin Islands). The shapefiles include polygon boundaries of geographic areas and features, linear features including roads and hydrography, and point features. These shapefiles do not contain any sensitive data or confidential data protected by Title 13 of the U.S.C.Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and are reviewed and updated by local participants prior to each decennial census. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of decennial census data. Census tracts generally have a population size of 1,200 to 8,000 people with an optimum size of 4,000 people. The spatial size of census tracts varies widely depending on the density of settlement. Ideally, census tract boundaries remain stable over time to facilitate statistical comparisons from census to census. However, physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, significant changes in population may result in splitting or combining census tracts. Census tract boundaries generally follow visible and identifiable features. Census tract boundaries may follow legal boundaries. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. Census Tract Codes and Numbers—Census tract numbers have up to a 4-character basic number and may have an optional 2-character suffix, for example, 1457.02. The Census Bureau uses suffixes to help identify census tract changes for comparison purposes. Full documentation: https://www2.census.gov/geo/pdfs/maps-data/data/tiger/tgrshp2020/TGRSHP2020_TechDoc.pdf

  12. TIGER/Line Shapefile, 2023, County, Kusilvak Census Area, AK, Topological...

    • catalog.data.gov
    Updated Dec 14, 2023
    + more versions
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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, Kusilvak Census Area, AK, Topological Faces (Polygons With All Geocodes) [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2023-county-kusilvak-census-area-ak-topological-faces-polygons-with-all-ge
    Explore at:
    Dataset updated
    Dec 14, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Kusilvak Census Area
    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. California Overlapping Cities and Counties and Identifiers with Coastal...

    • data.ca.gov
    • gis.data.ca.gov
    • +1more
    Updated Feb 20, 2025
    + more versions
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    California Department of Technology (2025). California Overlapping Cities and Counties and Identifiers with Coastal Buffers [Dataset]. https://data.ca.gov/dataset/california-overlapping-cities-and-counties-and-identifiers-with-coastal-buffers
    Explore at:
    xlsx, gdb, kml, txt, gpkg, zip, csv, arcgis geoservices rest api, html, geojsonAvailable download formats
    Dataset updated
    Feb 20, 2025
    Dataset authored and provided by
    California Department of Technologyhttp://cdt.ca.gov/
    Area covered
    California
    Description

    WARNING: This is a pre-release dataset and its fields names and data structures are subject to change. It should be considered pre-release until the end of 2024. Expected changes:

    • Metadata is missing or incomplete for some layers at this time and will be continuously improved.
    • We expect to update this layer roughly in line with CDTFA at some point, but will increase the update cadence over time as we are able to automate the final pieces of the process.
    This dataset is continuously updated as the source data from CDTFA is updated, as often as many times a month. If you require unchanging point-in-time data, export a copy for your own use rather than using the service directly in your applications.

    Purpose

    County and incorporated place (city) boundaries along with third party identifiers used to join in external data. Boundaries are from the authoritative source the California Department of Tax and Fee Administration (CDTFA), altered to show the counties as one polygon. This layer displays the city polygons on top of the County polygons so the area isn"t interrupted. The GEOID attribute information is added from the US Census. GEOID is based on merged State and County FIPS codes for the Counties. Abbreviations for Counties and Cities were added from Caltrans Division of Local Assistance (DLA) data. Place Type was populated with information extracted from the Census. Names and IDs from the US Board on Geographic Names (BGN), the authoritative source of place names as published in the Geographic Name Information System (GNIS), are attached as well. Finally, the coastline is used to separate coastal buffers from the land-based portions of jurisdictions. This feature layer is for public use.

    Related Layers

    This dataset is part of a grouping of many datasets:

    1. Cities: Only the city boundaries and attributes, without any unincorporated areas
    2. Counties: Full county boundaries and attributes, including all cities within as a single polygon
    3. Cities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.
    4. Place Abbreviations
    5. Unincorporated Areas (Coming Soon)
    6. Census Designated Places (Coming Soon)
    7. Cartographic Coastline
    Working with Coastal Buffers
    The dataset you are currently viewing includes the coastal buffers for cities and counties that have them in the authoritative source data from CDTFA. In the versions where they are included, they remain as a second polygon on cities or counties that have them, with all the same identifiers, and a value in the COASTAL field indicating if it"s an ocean or a bay buffer. If you wish to have a single polygon per jurisdiction that includes the coastal buffers, you can run a Dissolve on the version that has the coastal buffers on all the fields except COASTAL, Area_SqMi, Shape_Area, and Shape_Length to get a version with the correct identifiers.

    Point of Contact

    California Department of Technology, Office of Digital Services, odsdataservices@state.ca.gov

    Field and Abbreviation Definitions

    • COPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering system
    • Place Name: CDTFA incorporated (city) or county name
    • County: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.
    • Legal Place Name: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information System
    • GNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.
    • GEOID: numeric geographic identifiers from the US Census Bureau Place Type: Board on Geographic Names authorized nomenclature for boundary type published in the Geographic Name Information System
    • Place Abbr: CalTrans Division of Local Assistance abbreviations of incorporated area names
    • CNTY Abbr: CalTrans Division of Local Assistance abbreviations of county names
    • Area_SqMi: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.
    • COASTAL: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".
    • GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to support offline sync, but is not persistent, so data keyed to it will be orphaned at our next update. Use one of the other persistent identifiers, such as GNIS_ID or GEOID instead.

    Accuracy

    CDTFA"s source data notes the following about accuracy:

    City boundary changes and county boundary line adjustments filed with the Board of Equalization per Government Code 54900. This GIS layer contains the boundaries of the unincorporated county and incorporated cities within the state of California. The initial dataset was created in March of 2015 and was based on the State Board of Equalization tax rate area boundaries. As of April 1, 2024, the maintenance of this dataset is provided by the California Department of Tax and Fee Administration for the purpose of determining sales and use tax rates. The boundaries are continuously being revised to align with aerial imagery when areas of conflict are discovered between the original boundary provided by the California State Board of Equalization and the boundary made publicly available by local, state, and federal government. Some differences may occur between actual recorded boundaries and the boundaries used for sales and use tax purposes. The boundaries in this map are representations of taxing jurisdictions for the purpose of determining sales and use tax rates and should not be used to determine precise city or county boundary line locations. COUNTY = county name; CITY = city name or unincorporated

  14. Millennium Cohort Study: Sweep 6 Geographical Identifiers Using 2001 Census...

    • beta.ukdataservice.ac.uk
    Updated 2024
    + more versions
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    Institute Of Education University Of London (2024). Millennium Cohort Study: Sweep 6 Geographical Identifiers Using 2001 Census Boundaries: Secure Access [Dataset]. http://doi.org/10.5255/ukda-sn-8231-1
    Explore at:
    Dataset updated
    2024
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    DataCitehttps://www.datacite.org/
    Authors
    Institute Of Education University Of London
    Description

    Background:
    The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:

    • to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will require
    • to provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)
    • to collect information on previously neglected topics, such as fathers' involvement in children's care and development
    • to focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may be
    • to emphasise intergenerational links including those back to the parents' own childhood
    • to investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when available
    Additional objectives subsequently included for MCS were:
    • to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)
    • to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of England

    Further information about the MCS can be found on the Centre for Longitudinal Studies web pages.

    The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

    The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old.

    End User Licence versions of MCS studies:
    The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.

    Sub-sample studies:
    Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).

    Release of Sweeps 1 to 4 to Long Format (Summer 2020)
    To support longitudinal research and make it easier to compare data from different time points, all data from across all sweeps is now in a consistent format. The update affects the data from sweeps 1 to 4 (from 9 months to 7 years), which are updated from the old/wide to a new/long format to match the format of data of sweeps 5 and 6 (age 11 and 14 sweeps). The old/wide formatted datasets contained one row per family with multiple variables for different respondents. The new/long formatted datasets contain one row per respondent (per parent or per cohort member) for each MCS family. Additional updates have been made to all sweeps to harmonise variable labels and enhance anonymisation.

    How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
    For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

    Secure Access datasets:
    Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).

    Secure Access versions of the MCS include:

    • detailed sensitive variables not available under EUL. These have been grouped thematically and are held under SN 8753 (socio-economic, accommodation and occupational data), SN 8754 (self-reported health, behaviour and fertility), SN 8755 (demographics, language and religion) and SN 8756 (exact participation dates). These files replace previously available studies held under SNs 8456 and 8622-8627
    • detailed geographical identifier files which are grouped by sweep held under SN 7758 (MCS1), SN 7759 (MCS2), SN 7760 (MCS3), SN 7761 (MCS4), SN 7762 (MCS5 2001 Census Boundaries), SN 7763 (MCS5 2011 Census Boundaries), SN 8231 (MCS6 2001 Census Boundaries), SN 8232 (MCS6 2011 Census Boundaries), SN 8757 (MCS7), SN 8758 (MCS7 2001 Census Boundaries) and SN 8759 (MCS7 2011 Census Boundaries). These files replace previously available files grouped by geography SN 7049 (Ward level), SN 7050 (Lower Super Output Area level), and SN 7051 (Output Area level)
    • linked education administrative datasets for Key Stages 1, 2, 4 and 5 held under SN 8481 (England). This replaces previously available datasets for Key Stage 1 (SN 6862) and Key Stage 2 (SN 7712)
    • linked education administrative datasets for Key Stage 1 held under SN 7414 (Scotland)
    • linked education administrative dataset for Key Stages 1, 2, 3 and 4 under SN 9085 (Wales)
    • linked NHS Patient Episode Database for Wales (PEDW) for MCS1 – MCS5 held under SN 8302
    • linked Scottish Medical Records data held under SNs 8709, 8710, 8711, 8712, 8713 and 8714;
    • Banded Distances to English Grammar Schools for MCS5 held under SN 8394
    • linked Health Administrative Datasets (Hospital Episode Statistics) for England for years 2000-2019 held under SN 9030
    • linked Hospital of Birth data held under SN 5724.

    The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application.

    Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page).

    International Data Access Network (IDAN)
    These data are now available to researchers based outside the UK. Selected UKDS SecureLab/controlled datasets from the Institute for Social and Economic Research (ISER) and the Centre for Longitudinal Studies (CLS) have been made available under the International Data Access Network (IDAN) scheme, via a Safe Room access point at one of the UKDS IDAN partners. Prospective users should read the UKDS SecureLab application guide for non-ONS data for researchers outside of the UK via Safe Room Remote Desktop Access. Further details about the IDAN scheme can be found on the UKDS International Data Access Network webpage and on the IDAN website.

  15. TIGER/Line Shapefile, 2023, County, Nez Perce County, ID, Topological Faces...

    • catalog.data.gov
    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, Nez Perce County, ID, Topological Faces (Polygons With All Geocodes) [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2023-county-nez-perce-county-id-topological-faces-polygons-with-all-geocod
    Explore at:
    Dataset updated
    Dec 15, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Nez Perce 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.

  16. REV 2.0 Eligible and Ineligible Census Tracts

    • data.cnra.ca.gov
    • gis.data.cnra.ca.gov
    • +2more
    Updated Apr 8, 2024
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    California Energy Commission (2024). REV 2.0 Eligible and Ineligible Census Tracts [Dataset]. https://data.cnra.ca.gov/dataset/rev-2-0-eligible-and-ineligible-census-tracts
    Explore at:
    arcgis geoservices rest api, geojson, zip, kml, html, csvAvailable download formats
    Dataset updated
    Apr 8, 2024
    Dataset authored and provided by
    California Energy Commissionhttp://www.energy.ca.gov/
    License

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

    Description

    Census tracts are designated as urban, rural center, or rural through SB 1000 analysis. These designations are being used for the REV 2.0 and Community Charging in Urban Areas GFOs.

    • Rural centers are contiguous urban census tracts with a population of less than 50,0000. Urban census tracts are tracts where at least 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria.
    • Rural communities are census tracts where less than 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria.
    • Urban communities are contiguous urban census tracts with a population of 50,000 or greater. Urban census tracts are tracts where at least 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria.
    Data Dictionary:
    • OBJECTID: Unique ID
    • STATEFP: State FIPS Code
    • COUNTYFP: County FIPS Code
    • TRACTCE: Census Tract ID
    • GEOID: Geographic Identifier
    • Name: Census Tract ID Name (short)
    • NAMELSAD: Census Tract ID Name (long)
    • ALAND: Land Area (square meters)
    • AWATER: Water Area (square meters)
    • DAC: Whether or not a census tract is a disadvantaged community as defined by SB 535 and designated by CalEPA using CalEnviroScreen 4.0 (May 2022 update)
    • Income_Group: Whether or not a census tract is low-, middle-, or high-income as defined by AB 1550 and designated by CARB and the CEC (June 2023 update)
    • Urban_Rural_RuralCenter: Whether or not a census tract is urban, rural, or rural center as defined and designated by the CEC through the SB 1000 Assessment (2024 update)
    • PerCap_100k_L2DCFC: Number of public Level 2 and DC fast chargers per 100,000 people in a census tract
    • DAC_andor_LIC: Whether or not a census tract is a disadvantaged or low-income community as defined by SB 535 and AB 1550 and designated by CalEPA and CARB
    • UCC_eligible: Whether or not the census tract is an eligible area for the Community Charging in Urban Areas GFO. For a site to be eligible, it must be in a census tract that is either a disadvantaged or low-income community, and urban, and has below the state average for per capita public Level 2 and DC fast chargers as defined by the CEC.
    • REV2_eligible: Whether or not the census tract is an eligible area for the Rural Electric Vehicle Charging 2.0 GFO. For a site to be eligible, it must be in a rural or rural center census tract as defined by the CEC.
    • Shape_Area: Census tract shape area (square meters)
    • Shape_Length: Census tract shape length (square meters)

  17. TIGER/Line Shapefile, 2023, County, Bonner County, ID, Topological Faces...

    • catalog.data.gov
    • datasets.ai
    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, Bonner County, ID, Topological Faces (Polygons With All Geocodes) [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2023-county-bonner-county-id-topological-faces-polygons-with-all-geocodes
    Explore at:
    Dataset updated
    Dec 15, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    Bonner 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

    TIGER/Line Shapefile, 2012, county, Nassau County, NY, Current Other...

    • datadiscoverystudio.org
    tgrshp (compressed)
    Updated Jan 1, 2012
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division (2012). TIGER/Line Shapefile, 2012, county, Nassau County, NY, Current Other Identifiers Relationship File [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/15623a27c3564252bdeaff0e152f5acb/html
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    tgrshp (compressed)Available download formats
    Dataset updated
    Jan 1, 2012
    Authors
    U.S. Department of Commerce, U.S. Census Bureau, Geography Division
    Area covered
    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. The Other Identifiers Relationship File contains external identifier codes, such as National Hydrographic Dataset (NHD) codes and individual county identifiers. The edge to which an Other Identifiers Relationship File record applies can be determined by linking to the All Lines shapefile on the permanent edge identifier (TLID) attribute. Not every TLID has an external identifier associated with it and some TLIDs may have more than one.

  19. TIGER/Line Shapefile, 2020, County, Bonner County, ID, Topological Faces...

    • s.cnmilf.com
    • 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, 2020, County, Bonner County, ID, Topological Faces (Polygons With All Geocodes) [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/tiger-line-shapefile-2020-county-bonner-county-id-topological-faces-polygons-with-all-geocodes
    Explore at:
    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://www.commerce.gov/
    Area covered
    Bonner 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.

  20. c

    Next Steps: Sweep 8 and 9, 2016 and 2022: Geographical Identifiers, 2011...

    • datacatalogue.cessda.eu
    Updated May 16, 2025
    + more versions
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    University College London, UCL Institute of Education (2025). Next Steps: Sweep 8 and 9, 2016 and 2022: Geographical Identifiers, 2011 Census Boundaries: Secure Access [Dataset]. http://doi.org/10.5255/UKDA-SN-8190-2
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    Dataset updated
    May 16, 2025
    Dataset provided by
    Centre for Longitudinal Studies
    Authors
    University College London, UCL Institute of Education
    Time period covered
    Aug 19, 2015 - Sep 23, 2023
    Area covered
    England
    Variables measured
    Individuals, Families/households, National
    Measurement technique
    Compilation/Synthesis
    Description

    Abstract copyright UK Data Service and data collection copyright owner.

    Next Steps (also known as the Longitudinal Study of Young People in England (LSYPE1)) is a major longitudinal cohort study following a nationally representative group of around 16,000 who were in Year 9 attending state and independent schools in England in 2004, a cohort born in 1989-90.

    The first seven sweeps of the study were conducted annually (2004-2010) when the study was funded and managed by the Department for Education (DfE). The study mainly focused on the educational and early labour market experiences of young people.

    In 2015 Next Steps was restarted, under the management of the Centre for Longitudinal Studies (CLS) at the UCL Faculty of Education and Society (IOE) and funded by the Economic and Social Research Council. The Next Steps Age 25 survey was aimed at increasing the understanding of the lives of young adults growing up today and the transitions out of education and into early adult life.

    The Next Steps Age 32 Survey took place between April 2022 and September 2023 and is the ninth sweep of the study. The Age 32 Survey aimed to provide data for research and policy on the lives of this generation of adults in their early 30s. This sweep also collected information on many wider aspects of cohort members' lives including health and wellbeing, politics and social participation, identity and attitudes as well as capturing personality, resilience, working memory and financial literacy.

    Next Steps survey data is also linked to the National Pupil Database (NPD), the Hospital Episode Statistics (HES), the Individualised Learner Records (ILR) and the Student Loans Company (SLC).

    There are now two separate studies that began under the LSYPE programme. The second study, Our Future (LSYPE2) (available at the UK Data Service under GN 2000110), began in 2013 and will track a sample of over 13,000 young people annually from ages 13/14 through to age 20.

    Further information about Next Steps may be found on the CLS website.

    Secure Access datasets:

    Secure Access versions of Next Steps have more restrictive access conditions than Safeguarded versions available under the standard End User Licence (see 'Access' section).

    Secure Access versions of the Next Steps include:

    • sensitive variables from the questionnaire data for Sweeps 1-9. These are available under Secure Access SN 8656.
    • National Pupil Database (NPD) linked data at Key Stages 2, 3, 4 and 5, England. These are available under SN 7104.
    • Linked Individualised Learner Records learner and learning aims datasets for academic years 2005 to 2014, England. These are available under SN 8577.
    • detailed geographic indicators for Sweep 1 and Sweep 8 (2001 Census Boundaries) are available under SN 8189, geographic indicators for Sweep 8 and 9 (2011 Census Boundaries) are available under SN 8190, and geographic indicators for Sweep 9 (2021 Census Boundaries) are available under SN 9337. The Sweep 1 geography file was previously held under SN 7104.
    • Linked Health Administrative Datasets (Hospital Episode Statistics) for financial years 1997-2022 held under SN 8681.
    • Linked Student Loans Company Records for years 2007-2021 held under SN 8848.

    When researchers are approved/accredited to access a Secure Access version of Next Steps, the Safeguarded (EUL) version of the study - Next Steps: Sweeps 1-9, 2004-2023 (SN 5545) - will be automatically provided alongside.


    International Data Access Network (IDAN)
    These data are now available to researchers based outside the UK. Selected UKDS SecureLab/controlled datasets from the Institute for Social and Economic Research (ISER) and the Centre for Longitudinal Studies (CLS) have been made available under the International Data Access Network (IDAN) scheme, via a Safe Room access point at one of the UKDS IDAN partners. Prospective users should read the UKDS SecureLab application guide for non-ONS data for researchers outside of the UK via Safe Room Remote Desktop Access. Further details about the IDAN scheme can be found on the UKDS International Data Access Network webpage and on the IDAN website.


    Latest edition information:
    For the second edition (January 2025), the Sweep 9 data and documentation have been added.


    Main Topics:

    The Next Steps: Sweep 8, 2016: Geographical Identifiers, 2011 Census Boundaries: Secure Access data include the address at interview linked to:
    • Country
    • Region 2010
    • Ward 1998
    • Census Statistic Ward 2003
    • Output Area 2011
    • Lower Super Output Area 2011
    • Middle Super Output Area 2011
    • Local Authority District / Unitary Authority...

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Western Pennsylvania Regional Data Center (2024). Property Data with Geographic Identifiers [Dataset]. https://data.wprdc.org/dataset/property-data-with-geographic-identifiers

Property Data with Geographic Identifiers

Explore at:
csv, zip, csv(265867153)Available download formats
Dataset updated
Jun 9, 2024
Dataset provided by
Western Pennsylvania Regional Data Center
License

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

Description

These datasets are clones of popular WPRDC datasets from various publishers that have been reverse-geocoded to add geographic identifiers (e.g., municipality and neighborhood).

Follow the links in the file descriptions for more information on the original datasets.

If you get a timeout error when trying to download either "Property Assessment Parcel Data" or "Property Assessment Data with Parcel Centroids", click on the Preview link and use the alternative download link (which should contain the term "downstream").

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