100+ datasets found
  1. o

    Data from: American Local Government Elections Database

    • osf.io
    Updated Apr 1, 2024
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    Justin de Benedictis-Kessner; Diana Lee; Yamil Velez; Christopher Warshaw (2024). American Local Government Elections Database [Dataset]. http://doi.org/10.17605/OSF.IO/MV5E6
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    Dataset updated
    Apr 1, 2024
    Dataset provided by
    Center For Open Science
    Authors
    Justin de Benedictis-Kessner; Diana Lee; Yamil Velez; Christopher Warshaw
    License

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

    Area covered
    United States
    Description

    No description was included in this Dataset collected from the OSF

  2. d

    Protected Areas Database of the United States (PAD-US) 2.0

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). Protected Areas Database of the United States (PAD-US) 2.0 [Dataset]. https://catalog.data.gov/dataset/protected-areas-database-of-the-united-states-pad-us-2-0
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    United States
    Description

    NOTE: A more current version of the Protected Areas Database of the United States (PAD-US) is available: PAD-US 2.1 https://doi.org/10.5066/P92QM3NT. The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastre Theme (https://communities.geoplatform.gov/ngda-cadastre/). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all public and nonprofit lands and waters. Most are public lands owned in fee; however, long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g. 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of public land and other protected areas, compiling “best available” data provided by managing agencies and organizations. The PAD-US geodatabase maps and describes areas with over twenty-five attributes in nine feature classes to support data management, queries, web mapping services, and analyses. NOTE: A more current version of the Protected Areas Database of the United States (PAD-US) is available: PAD-US 2.1 https://doi.org/10.5066/P92QM3NT This PAD-US Version 2.0 dataset includes a variety of updates and changes from the previous Version 1.4 dataset. The following list summarizes major updates and changes: 1) Expanded database structure with new layers: the geodatabase feature class structure now includes nine feature classes separating fee owned lands, conservation (and other) easements, management designations overlapping fee lands, marine areas, proclamation boundaries and various 'Combined' feature classes (e.g. 'Fee' + 'Easement' + 'Designation' feature classes); 2) Major update of the Federal estate including data from 8 agencies, developed in collaboration with the Federal Geographic Data Committee (FGDC) Federal Lands Working Group (FLWG, https://communities.geoplatform.gov/ngda-govunits/federal-lands-workgroup/); 3) Major updates to 30 States and limited additions to 16 other States; 4) Integration of The Nature Conservancy's (TNC) Secured Lands geodatabase; 5) Integration of Ducks Unlimited's (DU) Conservation and Recreation Lands (CARL) database; 6) Integration of The Trust for Public Land's (TPL) Conservation Almanac database; 7) The Nature Conservancy (TNC) Lands database update: the national source of lands owned in fee or managed by TNC; 8) National Conservation Easement Database (NCED) update: complete update of non-sensitive (suitable for publication in the public domain) easements; 9) Complete National Marine Protected Areas (MPA) update: from the NOAA MPA Inventory, including conservation measure ('GAP Status Code', 'IUCN Category') review by NOAA; 10) First integration of Bureau of Energy Ocean Management (BOEM) managed marine lands: BOEM submitted Outer Continental Shelf Area lands managed for natural resources (minerals, oil and gas), a significant and new addition to PAD-US; 11) Fee boundary overlap assessment: topology overlaps in the PAD-US 2.0 'Fee' feature class have been identified and are available for user and data-steward reference (See Logical_Consistency_Report Section). For more information regarding the PAD-US dataset please visit, https://usgs.gov/gapanalysis/PAD-US/. For more information about data aggregation please review the “Data Manual for PAD-US” available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual .

  3. f

    The Government Finance Database: A Common Resource for Quantitative Research...

    • plos.figshare.com
    doc
    Updated Jun 3, 2023
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    Kawika Pierson; Michael L. Hand; Fred Thompson (2023). The Government Finance Database: A Common Resource for Quantitative Research in Public Financial Analysis [Dataset]. http://doi.org/10.1371/journal.pone.0130119
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    docAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kawika Pierson; Michael L. Hand; Fred Thompson
    License

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

    Description

    Quantitative public financial management research focused on local governments is limited by the absence of a common database for empirical analysis. While the U.S. Census Bureau distributes government finance data that some scholars have utilized, the arduous process of collecting, interpreting, and organizing the data has led its adoption to be prohibitive and inconsistent. In this article we offer a single, coherent resource that contains all of the government financial data from 1967-2012, uses easy to understand natural-language variable names, and will be extended when new data is available.

  4. d

    Protected Areas Database of the United States (PAD-US) 4.0

    • catalog.data.gov
    • data.usgs.gov
    Updated Jul 20, 2024
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    U.S. Geological Survey (2024). Protected Areas Database of the United States (PAD-US) 4.0 [Dataset]. https://catalog.data.gov/dataset/protected-areas-database-of-the-united-states-pad-us-4-0
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    Dataset updated
    Jul 20, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    United States
    Description

    The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastre Theme ( https://ngda-cadastre-geoplatform.hub.arcgis.com/ ). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all open space public and nonprofit lands and waters. Most are public lands owned in fee (the owner of the property has full and irrevocable ownership of the land); however, permanent and long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g., 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of U.S. public land and other protected areas, compiling “best available” data provided by managing agencies and organizations. PAD-US provides a full inventory geodatabase, spatial analysis, statistics, data downloads, web services, poster maps, and data submissions included in efforts to track global progress toward biodiversity protection. PAD-US integrates spatial data to ensure public lands and other protected areas from all jurisdictions are represented. PAD-US version 4.0 includes new and updated data from the following data providers. All other data were transferred from previous versions of PAD-US. Federal updates - The USGS remains committed to updating federal fee owned lands data and major designation changes in regular PAD-US updates, where authoritative data provided directly by managing agencies are available or alternative data sources are recommended. Revisions associated with the federal estate in this version include updates to the Federal estate (fee ownership parcels, easement interest, management designations, and proclamation boundaries), with authoritative data from 7 agencies: Bureau of Land Management (BLM), U.S. Census Bureau (Census Bureau), Department of Defense (DOD), U.S. Fish and Wildlife Service (FWS), National Park Service (NPS), Natural Resources Conservation Service (NRCS), and the U.S. Forest Service (USFS). The federal theme in PAD-US is developed in close collaboration with the Federal Geographic Data Committee (FGDC) Federal Lands Working Group (FLWG, https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup/ ). This includes improved the representation of boundaries and attributes for the National Park Service, U.S. Forest Service, Bureau of Land Management, and U.S. Fish and Wildlife Service lands, in collaboration with agency data-stewards, in response to feedback from the PAD-US Team and stakeholders. Additionally, National Cemetery boundaries were added using geospatial boundary data provided by the U.S. Department of Veterans Affairs and NASA boundaries were added using data contained in the USGS National Boundary Dataset (NBD). State Updates - USGS is committed to building capacity in the state data steward network and the PAD-US Team to increase the frequency of state land and NGO partner updates, as resources allow. State Lands Workgroup ( https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/state-lands-workgroup ) is focused on improving protected land inventories in PAD-US, increase update efficiency, and facilitate local review. PAD-US 4.0 included updates and additions from the following seventeen states and territories: California (state, local, and nonprofit fee); Colorado (state, local, and nonprofit fee and easement); Georgia (state and local fee); Kentucky (state, local, and nonprofit fee and easement); Maine (state, local, and nonprofit fee and easement); Montana (state, local, and nonprofit fee); Nebraska (state fee); New Jersey (state, local, and nonprofit fee and easement); New York (state, local, and nonprofit fee and easement); North Carolina (state, local, and nonprofit fee); Pennsylvania (state, local, and nonprofit fee and easement); Puerto Rico (territory fee); Tennessee (land trust fee); Texas (state, local, and nonprofit fee); Virginia (state, local, and nonprofit fee); West Virginia (state, local, and nonprofit fee); and Wisconsin (state fee data). Additionally, the following datasets were incorporated from NGO data partners: Trust for Public Land (TPL) Parkserve (new fee and easement data); The Nature Conservancy (TNC) Lands (fee owned by TNC); TNC Northeast Secured Areas; Ducks Unlimited (land trust fee); and the National Conservation Easement Database (NCED). All state and NGO easement submissions are provided to NCED. For more information regarding the PAD-US dataset please visit, https://www.usgs.gov/programs/gap-analysis-project/science/protected-areas . For more information regarding the PAD-US dataset please visit, https://www.usgs.gov/programs/gap-analysis-project/science/protected-areas . For more information about data aggregation please review the PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . A version history of PAD-US updates is summarized below (See https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-history/ for more information): 1) First posted - April 2009 (Version 1.0 - available from the PAD-US: Team pad-us@usgs.gov). 2) Revised - May 2010 (Version 1.1 - available from the PAD-US: Team pad-us@usgs.gov). 3) Revised - April 2011 (Version 1.2 - available from the PAD-US: Team pad-us@usgs.gov). 4) Revised - November 2012 (Version 1.3) https://doi.org/10.5066/F79Z92XD 5) Revised - May 2016 (Version 1.4) https://doi.org/10.5066/F7G73BSZ 6) Revised - September 2018 (Version 2.0) https://doi.org/10.5066/P955KPLE 7) Revised - September 2020 (Version 2.1) https://doi.org/10.5066/P92QM3NT 8) Revised - January 2022 (Version 3.0) https://doi.org/10.5066/P9Q9LQ4B 9) Revised - April 2024 (Version 4.0) https://doi.org/10.5066/P96WBCHS Comparing protected area trends between PAD-US versions is not recommended without consultation with USGS as many changes reflect improvements to agency and organization GIS systems, or conservation and recreation measure classification, rather than actual changes in protected area acquisition on the ground.

  5. f

    Data from: Expenditure Categories.

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Kawika Pierson; Michael L. Hand; Fred Thompson (2023). Expenditure Categories. [Dataset]. http://doi.org/10.1371/journal.pone.0130119.t007
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kawika Pierson; Michael L. Hand; Fred Thompson
    License

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

    Description

    Every set of expenditure data follows a similar organization. This table shows how to interpret the names given to the variables in the database, references the census object codes used to create them, and provides a short description of each. The indentation of the variables in the first column indicates how subcategories of data collapse into larger categories. More detailed descriptions of each category can be found in the Census’ 2006 classification manual (http://www.census.gov/govs/classification/) included with the database download.Expenditure Categories.

  6. f

    The Impact of Requiring Consecutive Data on Average Population.

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Kawika Pierson; Michael L. Hand; Fred Thompson (2023). The Impact of Requiring Consecutive Data on Average Population. [Dataset]. http://doi.org/10.1371/journal.pone.0130119.t011
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kawika Pierson; Michael L. Hand; Fred Thompson
    License

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

    Description

    This table displays how the average population of included governments will change when researchers require consecutive years of data. The calculations are shown by government type, and each column increases the number of required years by one.The Impact of Requiring Consecutive Data on Average Population.

  7. United States Google Search Trends: Government Measures: Government Subsidy

    • ceicdata.com
    + more versions
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    CEICdata.com, United States Google Search Trends: Government Measures: Government Subsidy [Dataset]. https://www.ceicdata.com/en/united-states/google-search-trends-by-categories/google-search-trends-government-measures-government-subsidy
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    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Feb 23, 2025 - Mar 6, 2025
    Area covered
    United States
    Description

    United States Google Search Trends: Government Measures: Government Subsidy data was reported at 0.000 Score in 14 May 2025. This stayed constant from the previous number of 0.000 Score for 13 May 2025. United States Google Search Trends: Government Measures: Government Subsidy data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 14 May 2025, with 1261 observations. The data reached an all-time high of 0.000 Score in 14 May 2025 and a record low of 0.000 Score in 14 May 2025. United States Google Search Trends: Government Measures: Government Subsidy data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s United States – Table US.Google.GT: Google Search Trends: by Categories.

  8. f

    Special District Growth.

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Kawika Pierson; Michael L. Hand; Fred Thompson (2023). Special District Growth. [Dataset]. http://doi.org/10.1371/journal.pone.0130119.t012
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kawika Pierson; Michael L. Hand; Fred Thompson
    License

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

    Description

    This table displays the growth of special districts by comparing the 1977 data with the 2007 data, and is ordered by the number of districts existing in the 2007 data. The absolute number of special districts of each type is displayed, along with the percentage change between the two years, and the proportion of all special districts that each type comprises. The code column is the special district function code used by the census.Special District Growth.

  9. f

    Current Charge Functions.

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Kawika Pierson; Michael L. Hand; Fred Thompson (2023). Current Charge Functions. [Dataset]. http://doi.org/10.1371/journal.pone.0130119.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kawika Pierson; Michael L. Hand; Fred Thompson
    License

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

    Description

    This table describes a detailed breakdown of the different current charge function codes reported in the data. NEC stands for not elsewhere classified. The indentation of the variables in the first column indicates how subcategories of data collapse into larger categories. More detailed descriptions of each function code can be found in the Census’ 2006 classification manual (http://www.census.gov/govs/classification/) included with the database download.Current Charge Functions.

  10. f

    Miscellaneous General Revenue Variables.

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Kawika Pierson; Michael L. Hand; Fred Thompson (2023). Miscellaneous General Revenue Variables. [Dataset]. http://doi.org/10.1371/journal.pone.0130119.t005
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kawika Pierson; Michael L. Hand; Fred Thompson
    License

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

    Description

    This table describes the coding of the miscellaneous revenue variables and provides a short description of each. NEC stands for not elsewhere classified. The indentation of the variables in the first column indicates how subcategories of data collapse into larger categories. More detailed descriptions of each variable can be found in the Census’ 2006 classification manual (http://www.census.gov/govs/classification/) included with the database download.Miscellaneous General Revenue Variables.

  11. f

    Expenditure Function Codes.

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Kawika Pierson; Michael L. Hand; Fred Thompson (2023). Expenditure Function Codes. [Dataset]. http://doi.org/10.1371/journal.pone.0130119.t008
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kawika Pierson; Michael L. Hand; Fred Thompson
    License

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

    Description

    The data include a number of different functional separations for expenditures and the table above shows the name of each along with the corresponding census function number or numbers included in that expenditure function. NEC stands for not elsewhere classified. The indentation of the variables in the first column indicates how subcategories of data collapse into larger categories. More detailed descriptions of each expenditure function can be found in the Census’ 2006 classification manual (http://www.census.gov/govs/classification/) included with the database download.Expenditure Function Codes.

  12. p

    Governments in Maryland, United States - 108 Verified Listings Database

    • poidata.io
    csv, excel, json
    Updated Jul 14, 2025
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    Poidata.io (2025). Governments in Maryland, United States - 108 Verified Listings Database [Dataset]. https://www.poidata.io/report/government/united-states/maryland
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    json, excel, csvAvailable download formats
    Dataset updated
    Jul 14, 2025
    Dataset provided by
    Poidata.io
    Area covered
    Maryland, United States
    Description

    Comprehensive dataset of 108 Governments in Maryland, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

  13. f

    The Impact of Requiring Consecutive Data on Sample Size.

    • plos.figshare.com
    xls
    Updated Jun 4, 2023
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    Kawika Pierson; Michael L. Hand; Fred Thompson (2023). The Impact of Requiring Consecutive Data on Sample Size. [Dataset]. http://doi.org/10.1371/journal.pone.0130119.t010
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kawika Pierson; Michael L. Hand; Fred Thompson
    License

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

    Description

    This table displays how the sample size will change when researchers require consecutive years of data. The calculations are shown by government type, and each column increases the number of required years by one.The Impact of Requiring Consecutive Data on Sample Size.

  14. w

    Consolidated Human Activities Database (CHAD)

    • data.wu.ac.at
    • catalog.data.gov
    • +1more
    Updated Jan 1, 2014
    + more versions
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    U.S. Environmental Protection Agency (2014). Consolidated Human Activities Database (CHAD) [Dataset]. https://data.wu.ac.at/odso/data_gov/NmE3NjAwYzctOTc0Yi00YTkzLWIwYjgtMTFjNDFiZTFjYWRh
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    Dataset updated
    Jan 1, 2014
    Dataset provided by
    U.S. Environmental Protection Agency
    Area covered
    bc433b691eb83a32860504082a84631a15b815d0
    Description

    The Consolidated Human Activity Database (CHAD) contains data obtained from human activity studies that were collected at city, state, and national levels. CHAD is intended to be an input file for exposure/intake dose modeling and/or statistical analysis.

  15. NOAA Monthly U.S. Climate Divisional Database (NClimDiv)

    • ncei.noaa.gov
    • data.noaa.gov
    kmz
    Updated Mar 1, 2014
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    NOAA Monthly U.S. Climate Divisional Database (NClimDiv) [Dataset]. https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00005
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    kmzAvailable download formats
    Dataset updated
    Mar 1, 2014
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    Authors
    Vose, Russell S.; Applequist, Scott; Squires, Mike; Durre, Imke; Menne, Matthew J.; Williams, Claude N., Jr.; Fenimore, Chris; Gleason, Karin; Arndt, Derek
    Time period covered
    Jan 1, 1895 - Present
    Area covered
    Description

    In March 2015, data for thirteen Alaskan climate divisions were added to the NClimDiv data set. Data for the new Alaskan climate divisions begin in 1925 through the present and are included in all monthly updates. Alaskan climate data include the following elements for divisional and statewide coverage: average temperature, maximum temperature (highs), minimum temperature (lows), and precipitation. The Alaska NClimDiv data were created and updated using similar methodology as that for the CONUS, but with a different approach to establishing the underlying climatology. The Alaska data are built upon the 1971-2000 PRISM averages whereas the CONUS values utilize a base climatology derived from the NClimGrid data set. In January 2025, the National Centers for Environmental Information (NCEI) began summarizing the State of the Climate for Hawaii. This was made possible through a collaboration between NCEI and the University of Hawaii/Hawaii Climate Data Portal and completes a long-standing gap in NCEI's ability to characterize the State of the Climate for all 50 states. NCEI maintains monthly statewide, divisional, and gridded average temperature, maximum temperatures (highs), minimum temperature (lows) and precipitation data for Hawaii over the period 1991-2025. As of November 2018, NClimDiv includes county data and additional inventory files In March 2015, data for thirteen Alaskan climate divisions were added to the NClimDiv data set. Data for the new Alaskan climate divisions begin in 1925 through the present and are included in all monthly updates. Alaskan climate data include the following elements for divisional and statewide coverage: average temperature, maximum temperature (highs), minimum temperature (lows), and precipitation. The Alaska NClimDiv data were created and updated using similar methodology as that for the CONUS, but with a different approach to establishing the underlying climatology. The Alaska data are built upon the 1971-2000 PRISM averages whereas the CONUS values utilize a base climatology derived from the NClimGrid data set.

    As of November 2018, NClimDiv includes county data and additional inventory files.

  16. US EPA The Consolidated Human Activity Database (CHAD)

    • catalog.data.gov
    • data.ca.gov
    • +1more
    Updated Nov 27, 2024
    + more versions
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    California Environmental Protection Agency (2024). US EPA The Consolidated Human Activity Database (CHAD) [Dataset]. https://catalog.data.gov/dataset/us-epa-the-consolidated-human-activity-database-chad
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    Dataset updated
    Nov 27, 2024
    Dataset provided by
    California Environmental Protection Agencyhttps://calepa.ca.gov/
    Description

    The Consolidated Human Activity Database (CHAD) is a resource for learning about human exposure and health studies and predictive models.

  17. F

    All Employees, Federal

    • fred.stlouisfed.org
    json
    Updated Jul 3, 2025
    + more versions
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    (2025). All Employees, Federal [Dataset]. https://fred.stlouisfed.org/series/CES9091000001
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    jsonAvailable download formats
    Dataset updated
    Jul 3, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for All Employees, Federal (CES9091000001) from Jan 1939 to Jun 2025 about establishment survey, federal, government, employment, and USA.

  18. p

    Governments in Iowa, United States - 101 Verified Listings Database

    • poidata.io
    csv, excel, json
    Updated Jun 25, 2025
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    Poidata.io (2025). Governments in Iowa, United States - 101 Verified Listings Database [Dataset]. https://www.poidata.io/report/government/united-states/iowa
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    csv, excel, jsonAvailable download formats
    Dataset updated
    Jun 25, 2025
    Dataset provided by
    Poidata.io
    Area covered
    Iowa, United States
    Description

    Comprehensive dataset of 101 Governments in Iowa, United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

  19. United States US: Government Expenditure on Tertiary Education: % of...

    • ceicdata.com
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    CEICdata.com, United States US: Government Expenditure on Tertiary Education: % of Government Expenditure on Education [Dataset]. https://www.ceicdata.com/en/united-states/education-statistics/us-government-expenditure-on-tertiary-education--of-government-expenditure-on-education
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    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2010 - Dec 1, 2014
    Area covered
    United States
    Variables measured
    Education Statistics
    Description

    United States US: Government Expenditure on Tertiary Education: % of Government Expenditure on Education data was reported at 27.502 % in 2014. This records an increase from the previous number of 27.227 % for 2013. United States US: Government Expenditure on Tertiary Education: % of Government Expenditure on Education data is updated yearly, averaging 27.227 % from Dec 2010 (Median) to 2014, with 5 observations. The data reached an all-time high of 28.463 % in 2012 and a record low of 25.653 % in 2010. United States US: Government Expenditure on Tertiary Education: % of Government Expenditure on Education data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. Expenditure on tertiary education is expressed as a percentage of total general government expenditure on education. General government usually refers to local, regional and central governments.; ; United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics.; Median;

  20. National Address Database

    • hub.arcgis.com
    • data-isdh.opendata.arcgis.com
    Updated Apr 7, 2022
    + more versions
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    Esri U.S. Federal Datasets (2022). National Address Database [Dataset]. https://hub.arcgis.com/datasets/fedmaps::national-address-database-1/explore
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    Dataset updated
    Apr 7, 2022
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri U.S. Federal Datasets
    Area covered
    Description

    National Address DatabaseThis National Geospatial Data Asset (NGDA) dataset, shared as a U.S. Department of Transportation (USDOT) feature layer, displays address data in the United States. Per USDOT, "The U.S. Department of Transportation (USDOT) and its partners from all levels of government recognize the need for a National Address Database (NAD). Accurate and up-to-date addresses are critical to transportation safety and are a vital part of Next Generation 9-1-1. They are also essential for a broad range of government services, including mail delivery, permitting, and school siting. To meet this need, USDOT partners with address programs from state, local, and tribal governments to compile their authoritative data into the NAD."District of Columbia (DC) Residential AddressesData currency: Current federal service (Address Points from National Address Database)NGDAID: 196 (National Address Database (NAD))For more information: Getting to know the National Address Database (NAD); National Address DatabaseFor feedback, please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Transportation Theme Community. Per the Federal Geospatial Data Committee (FGDC), Transportation is defined as the "means and aids for conveying persons and/or goods. The transportation system includes both physical and non-physical components related to all modes of travel that allow the movement of goods and people between locations".For other NGDA Content: Esri Federal Datasets

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Justin de Benedictis-Kessner; Diana Lee; Yamil Velez; Christopher Warshaw (2024). American Local Government Elections Database [Dataset]. http://doi.org/10.17605/OSF.IO/MV5E6

Data from: American Local Government Elections Database

Related Article
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3 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Apr 1, 2024
Dataset provided by
Center For Open Science
Authors
Justin de Benedictis-Kessner; Diana Lee; Yamil Velez; Christopher Warshaw
License

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

Area covered
United States
Description

No description was included in this Dataset collected from the OSF

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