100+ datasets found
  1. 4

    Data Journals: A Survey - Tables

    • data.4tu.nl
    • figshare.com
    • +1more
    zip
    Updated Jun 18, 2014
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    Leonardo Candela; Donatella Castelli; Paolo Manghi; Alice Tani (2014). Data Journals: A Survey - Tables [Dataset]. http://doi.org/10.4121/uuid:d6788296-d0df-400d-ad21-10295e82cd4c
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    zipAvailable download formats
    Dataset updated
    Jun 18, 2014
    Dataset provided by
    ISTI-CNR
    Authors
    Leonardo Candela; Donatella Castelli; Paolo Manghi; Alice Tani
    License

    https://doi.org/10.4121/resource:terms_of_usehttps://doi.org/10.4121/resource:terms_of_use

    Description

    This dataset groups all the tables supplementing the contents of the article "Data Journals: A Survey", which is going to be published by the Journal of the Association for Information Science and Technology (JASIST). Tables are published with no header. Any details can be found in the article.

    Abstract Data occupy a key role in our information society. However, although the amount of published data continues to grow and terms like “data deluge” and “big data” today characterize numerous (research) initiatives, a lot of work is still needed in the direction of publishing data in order to make them effectively discoverable, available, and reusable by others. Several barriers hinder data publishing, from lack of attribution and rewards, vague citation practices, quality issues, to a rather general lack of data sharing culture. Lately, data journals came forward as a solution to overcome some of these barriers. In this study of more than 100 currently existing data journals, we describe the approaches they promote for description, availability, citation, quality and open access or datasets. We close by identifying ways to expand and strengthen the data journals approach as a means to actually promote datasets access and exploitation.

  2. Reweighted Labour Force Survey data summary table

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Dec 3, 2024
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    Office for National Statistics (2024). Reweighted Labour Force Survey data summary table [Dataset]. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/datasets/reweightedlabourforcesurveydatasummarytable
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    xlsxAvailable download formats
    Dataset updated
    Dec 3, 2024
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Reweighted estimates of important Labour Force Survey indicators.

  3. Data from: 2MASS All-Sky Survey Scan Information Table

    • catalog.data.gov
    • s.cnmilf.com
    • +2more
    Updated Jul 4, 2025
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    NASA/IPAC Infrared Science Archive (2025). 2MASS All-Sky Survey Scan Information Table [Dataset]. https://catalog.data.gov/dataset/2mass-all-sky-survey-scan-information-table
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    Dataset updated
    Jul 4, 2025
    Dataset provided by
    NASA/IPAC Extragalactic Database
    Description

    The 2MASS Scan Information Table provides basic data for each scan in the 2MASS All Sky Release. The table is organized according to the broad function and utility of the parameters: positional information, photometric information, source detection statistics, etc.

  4. 2023 American Community Survey: S2701 | Selected Characteristics of Health...

    • data.census.gov
    • test.data.census.gov
    Updated Sep 28, 2019
    + more versions
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    ACS (2019). 2023 American Community Survey: S2701 | Selected Characteristics of Health Insurance Coverage in the United States (ACS 1-Year Estimates Subject Tables) [Dataset]. https://data.census.gov/cedsci/table?q=S2701
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    Dataset updated
    Sep 28, 2019
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2023
    Area covered
    United States
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The health insurance coverage category names were modified in 2010. See https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18 for a list of the insurance type definitions..Beginning in 2017, selected variable categories were updated, including age-categories, income-to-poverty ratio (IPR) categories, and the age universe for certain employment and education variables. See user note entitled "Health Insurance Table Updates" for further details..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  5. American Community Survey: 1-Year Estimates: Detailed Tables 1-Year

    • catalog.data.gov
    • datasets.ai
    Updated Jul 19, 2023
    + more versions
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    U.S. Census Bureau (2023). American Community Survey: 1-Year Estimates: Detailed Tables 1-Year [Dataset]. https://catalog.data.gov/dataset/american-community-survey-1-year-estimates-detailed-tables-1-year-3092c
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    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The American Community Survey (ACS) is an ongoing survey that provides data every year -- giving communities the current information they need to plan investments and services. The ACS covers a broad range of topics about social, economic, demographic, and housing characteristics of the U.S. population. Much of the ACS data provided on the Census Bureau's Web site are available separately by age group, race, Hispanic origin, and sex. Summary files, Subject tables, Data profiles, and Comparison profiles are available for the nation, all 50 states, the District of Columbia, Puerto Rico, every congressional district, every metropolitan area, and all counties and places with populations of 65,000 or more. Detailed Tables contain the most detailed cross-tabulations published for areas 65k and more. The data are population counts. There are over 31,000 variables in this dataset.

  6. d

    : Public survey data tables 2022/23

    • datasalsa.com
    • data.europa.eu
    csv
    Updated May 24, 2024
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    Charities Regulator (2024). : Public survey data tables 2022/23 [Dataset]. https://datasalsa.com/dataset/?catalogue=data.gov.ie&name=public-survey-data-tables-2022-23
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    csvAvailable download formats
    Dataset updated
    May 24, 2024
    Dataset authored and provided by
    Charities Regulator
    License

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

    Time period covered
    May 24, 2024
    Description

    : Public survey data tables 2022/23. Published by Charities Regulator. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Data tables for a public survey undertaken in 2022-2023...

  7. O

    City Cultural Centers Audit Community Survey - Open Response Data

    • data.austintexas.gov
    • cloud.csiss.gmu.edu
    • +2more
    application/rdfxml +5
    Updated Aug 17, 2020
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    City of Austin, Texas - data.austintexas.gov (2020). City Cultural Centers Audit Community Survey - Open Response Data [Dataset]. https://data.austintexas.gov/City-Government/City-Cultural-Centers-Audit-Community-Survey-Open-/jeyv-db9u
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    application/rdfxml, application/rssxml, xml, csv, tsv, jsonAvailable download formats
    Dataset updated
    Aug 17, 2020
    Dataset authored and provided by
    City of Austin, Texas - data.austintexas.gov
    Description

    This table contains data from the community survey conducted as part of an Audit of the City's Cultural Centers. We surveyed members of the Austin community using a survey developed by the audit team. Survey questions generally asked respondents' opinions on cultural center programs, staff, fees, and facilities. The survey opened January 3 and closed January 27, 2020. Austin community members were invited to take the survey through social media outreach and direct email invitations. The survey and outreach materials were written in English and translated into Spanish, Vietnamese, and Simplified Chinese. A total of 1,330 community members responded to the survey. Respondents were asked only to respond for centers they had visited in the last two years and could respond for more than one center. The comments detailed in this table were in response to open-ended survey items that allowed respondents to give opinions or suggestions about each center's programming, fees, staff, and facilities. Any open-ended responses answered in Spanish, Vietnamese, or Chinese were translated prior to analysis. To gauge the general sentiment of the responses, each was categorized as "Positive," "Negative," "Suggestion," or "N/A." During analysis, some comments were deemed more relevant to other open-ended survey items than the items for which they were originally written. These responses were re-assigned to the survey items that more closely aligned with their subject.

  8. d

    Health Survey for England 2022, Part 2: Data tables

    • digital.nhs.uk
    xlsx
    Updated Sep 24, 2024
    + more versions
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    (2024). Health Survey for England 2022, Part 2: Data tables [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/health-survey-for-england/2022-part-2
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    xlsx(598.0 kB), xlsx(221.4 kB), xlsx(147.0 kB), xlsx(227.9 kB)Available download formats
    Dataset updated
    Sep 24, 2024
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Description

    The tables provide data for adults (defined as people aged 16 and over) and children (defined as people aged between 0 and 15).

  9. 2022 American Community Survey: B25024 | Units in Structure (ACS 1-Year...

    • data.census.gov
    + more versions
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    ACS, 2022 American Community Survey: B25024 | Units in Structure (ACS 1-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT1Y2022.B25024
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2022
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2022 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  10. 2022 American Community Survey: S1702 | Poverty Status in the Past 12 Months...

    • data.census.gov
    + more versions
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    ACS, 2022 American Community Survey: S1702 | Poverty Status in the Past 12 Months of Families (ACS 1-Year Estimates Subject Tables) [Dataset]. https://data.census.gov/table/ACSST1Y2022.S1702?q=S1702
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2022
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2022 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Dollar amounts are adjusted to respective calendar years. For more information, see: Change to Income Deficit..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..The 2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  11. English Housing Survey data on energy performance, heating and insulation

    • gov.uk
    Updated Jul 18, 2024
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    Ministry of Housing, Communities and Local Government (2024). English Housing Survey data on energy performance, heating and insulation [Dataset]. https://www.gov.uk/government/statistical-data-sets/energy-performance
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    Dataset updated
    Jul 18, 2024
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Housing, Communities and Local Government
    Description

    Tables on:

    • heating
    • insultation
    • energy performance

    https://assets.publishing.service.gov.uk/media/668eff0dce1fd0da7b59235a/DA6101_Heating_-_dwellings.ods">DA6101: heating - dwellings

     <p class="gem-c-attachment_metadata"><span class="gem-c-attachment_attribute"><abbr title="OpenDocument Spreadsheet" class="gem-c-attachment_abbr">ODS</abbr></span>, <span class="gem-c-attachment_attribute">199 KB</span></p>
    
    
    
      <p class="gem-c-attachment_metadata">
       This file is in an <a href="https://www.gov.uk/guidance/using-open-document-formats-odf-in-your-organisation" target="_self" class="govuk-link">OpenDocument</a> format
    

    https://assets.publishing.service.gov.uk/media/668eff1c0808eaf43b50cd69/DA6102_Heating_-_areas.ods">DA6102: heating - areas

     <p class="gem-c-attachment_metadata"><span class="gem-c-attachment_attribute"><abbr title="OpenDocument Spreadsheet" class="gem-c-attachment_abbr">ODS</abbr></span>, <span class="gem-c-attachment_attribute">148 KB</span></p>
    
    
    
      <p class="gem-c-attachment_metadata">
       This file is in an <a href="https://www.gov.uk/guidance/using-open-document-formats-odf-in-your-organisation" target="_self" class="govuk-link">OpenDocument</a> format
    

    <a class="govuk-link" target="_self" data-ga4-link='{"event_name":"file_download","type":"attachment"}' href="https://assets.publi

  12. Teacher Follow-up Survey: Tables Library Data

    • datalumos.org
    delimited
    Updated Jun 27, 2025
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    United States Department of Education (2025). Teacher Follow-up Survey: Tables Library Data [Dataset]. http://doi.org/10.3886/E234602V1
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    delimitedAvailable download formats
    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    United States Department of Educationhttp://ed.gov/
    License

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

    Time period covered
    1994 - 2022
    Area covered
    United States
    Description

    About TFSThis is a study of public and private school teachers in elementary and secondary schools and is part of the NTPS study, which collects information from U.S. elementary and secondary schools and their staff. Use this study to learn about teacher retention and attrition rates, characteristics of teachers who stayed in the teaching profession and those who changed professions or retired, activity and occupational information for those who left the position of a K-12 teacher, reasons for moving to a new school or leaving the K-12 teaching profession, and job satisfaction.Data OrganizationEach table has an associated excel and excel SE file, which are grouped together in a folder in the dataset (one folder per table). The folders are named based on the excel file names, as they were when downloaded from the National Center for Education Statistics (NCES) website.In the TFS folder, there is a catalog csv that provides a crosswalk between the folder names and the table titles.The documentation folder contains (1) codebooks for TFS generated in NCES datalabs, (2) questionnaires for TFS downloaded from the study website and (3) reports related to TFS found in the NCES resource library.

  13. 2023 American Community Survey: S2407 | Industry by Class of Worker for the...

    • data.census.gov
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    ACS, 2023 American Community Survey: S2407 | Industry by Class of Worker for the Civilian Employed Population 16 Years and Over (ACS 5-Year Estimates Subject Tables) [Dataset]. https://data.census.gov/table/ACSST5Y2023.S2407
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2023
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Industry titles and their 4-digit codes are based on the North American Industry Classification System (NAICS). The Census industry codes for 2023 and later years are based on the 2022 revision of the NAICS. To allow for the creation of multiyear tables, industry data in the multiyear files (prior to data year 2023) were recoded to the 2022 Census industry codes. We recommend using caution when comparing data coded using 2022 Census industry codes with data coded using Census industry codes prior to data year 2023. For more information on the Census industry code changes, please visit our website at https://www.census.gov/topics/employment/industry-occupation/guidance/code-lists.html..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error i...

  14. American Community Survey: 5-Year Estimates: Detailed Tables 5-Year

    • catalog.data.gov
    Updated Jul 19, 2023
    + more versions
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    U.S. Census Bureau (2023). American Community Survey: 5-Year Estimates: Detailed Tables 5-Year [Dataset]. https://catalog.data.gov/dataset/american-community-survey-5-year-estimates-detailed-tables-5-year
    Explore at:
    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The American Community Survey (ACS) is an ongoing survey that provides data every year -- giving communities the current information they need to plan investments and services. The ACS covers a broad range of topics about social, economic, demographic, and housing characteristics of the U.S. population. Summary files include the following geographies: nation, all states (including DC and Puerto Rico), all metropolitan areas, all congressional districts (116th Congress), all counties, all places, and all tracts and block groups. Summary files contain the most detailed cross-tabulations, many of which are published down to block groups. The data are population and housing counts. There are over 64,000 variables in this dataset.

  15. d

    Health Survey for England 2019 [NS]

    • digital.nhs.uk
    xlsx
    Updated Dec 15, 2020
    + more versions
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    (2020). Health Survey for England 2019 [NS] [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/health-survey-for-england/2019
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    xlsx(182.7 kB), xlsx(220.8 kB), xlsx(538.7 kB), xlsx(258.8 kB), xlsx(126.7 kB), xlsx(228.1 kB), xlsx(249.8 kB), xlsx(418.9 kB)Available download formats
    Dataset updated
    Dec 15, 2020
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Time period covered
    Jan 1, 2019 - Dec 31, 2019
    Area covered
    England
    Description

    Contains tabulated outputs on each topic from the Health Survey for England, 2019

  16. English Housing Survey data on stock profile

    • gov.uk
    Updated Jul 18, 2024
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    Ministry of Housing, Communities and Local Government (2024). English Housing Survey data on stock profile [Dataset]. https://www.gov.uk/government/statistical-data-sets/stock-profile
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    Dataset updated
    Jul 18, 2024
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Housing, Communities and Local Government
    Description
  17. Personal crime prevalence (CSEW open data table)

    • ons.gov.uk
    • cy.ons.gov.uk
    zip
    Updated Apr 24, 2025
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    Office for National Statistics (2025). Personal crime prevalence (CSEW open data table) [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/crimeandjustice/datasets/personalcrimeprevalencecsewopendatatable
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    zipAvailable download formats
    Dataset updated
    Apr 24, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Crime Survey for England and Wales (CSEW) estimates, by each combination of offence group, age, sex, and important demographic characteristics.

  18. c

    Data from: 2MASS Survey Extended Source Reject Table

    • s.cnmilf.com
    • gimi9.com
    • +3more
    Updated Jun 28, 2025
    + more versions
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    NASA/IPAC Infrared Science Archive (2025). 2MASS Survey Extended Source Reject Table [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/2mass-survey-extended-source-reject-table
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    Dataset updated
    Jun 28, 2025
    Dataset provided by
    NASA/IPAC Infrared Science Archive
    Description

    The 2MASS Survey Point and Extended Source "Reject" Tables (PSRT and XSRT) contain the 843,988,897 point and 943,441 extended source measurements from the Survey WDBs that were not selected for inclusion in the All-Sky Release Catalogs. The characteristics of entries in the Reject Tables differs between scans that were and were not selected for inclusion in the All-Sky Release: In the 10,981 survey scans that were not selected for the All-Sky Release, the Reject Tables contain all point and extended source extractions. These include reliable detections of real astrophysical sources, spurious extractions of low signal-to-noise ratio (SNR) events, image artifacts and transients such as cosmic rays and meteor trails. In the 59,731 survey scans that were selected for the All-Sky Release, the Reject Tables contain only those extractions from the Survey WDBs that did not satisfy the source selection criteria used to construct the uniform and reliable All-Sky Release Catalogs. These include detections of faint sources and noise events that are below the Catalog flux and SNR thresholds, and spurious detections of image artifacts and transients. The Reject Tables also contain detections of brighter sources in the overlap regions between adjacent tiles that were removed during the Catalog multiple detection resolution process.

  19. M

    American Community Survey 5-Year Summary File

    • gisdata.mn.gov
    • data.wu.ac.at
    fgdb, gpkg, html, shp +1
    Updated Dec 20, 2024
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    Metropolitan Council (2024). American Community Survey 5-Year Summary File [Dataset]. https://gisdata.mn.gov/dataset/us-mn-state-metc-society-census-acs
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    html, fgdb, shp, xlsx, gpkgAvailable download formats
    Dataset updated
    Dec 20, 2024
    Dataset provided by
    Metropolitan Council
    Description

    The American Community Survey (ACS) provides detailed demographic, social, economic, commuting and housing statistics based on continuous survey data collection. Data collected over the most recent 5 years are batched, summarized and published the following December.

    These files contain summary data for Census Block Groups (CensusACSBlockGroup.xlsx), Tracts (CensusACSTract.xlsx), minor civil divisions (CensusACSMCD.xlsx), school districts (CensusACSSchoolDistrict.xlsx), and ZIP code tabulation areas (CensusACSZipCode.xlsx). No shapefiles are included, but these data files can be joined to associated shapefile datasets available elsewhere on this site. To facilitate this, the data files are also available as DBF tables and in a geodatabase.

    Starting with the 2016-2020 data, tract and block group boundaries are those used in the 2020 Census. Starting with the 2017-2021 data, ZIP Code Tabulation Areas are those defined based on the 2020 Census. If you need the most recent ACS data for the tract and block group boundaries used in the 2010 Census, contact Matt Schroeder (information below).

  20. Brazil Employment: Industry

    • ceicdata.com
    Updated Mar 25, 2018
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    CEICdata.com (2018). Brazil Employment: Industry [Dataset]. https://www.ceicdata.com/en/brazil/continuous-national-household-sample-survey-monthly
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    Dataset updated
    Mar 25, 2018
    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
    Sep 1, 2020 - Aug 1, 2021
    Area covered
    Brazil
    Variables measured
    Wage/Earnings
    Description

    Employment: Industry data was reported at 11,498.000 Person th in Aug 2021. This records an increase from the previous number of 11,238.000 Person th for Jul 2021. Employment: Industry data is updated monthly, averaging 11,931.000 Person th from Mar 2012 (Median) to Aug 2021, with 114 observations. The data reached an all-time high of 13,373.000 Person th in Oct 2014 and a record low of 10,507.000 Person th in Aug 2020. Employment: Industry data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Global Database’s Brazil – Table BR.GBA001: Continuous National Household Sample Survey: Monthly.

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Leonardo Candela; Donatella Castelli; Paolo Manghi; Alice Tani (2014). Data Journals: A Survey - Tables [Dataset]. http://doi.org/10.4121/uuid:d6788296-d0df-400d-ad21-10295e82cd4c

Data Journals: A Survey - Tables

Explore at:
zipAvailable download formats
Dataset updated
Jun 18, 2014
Dataset provided by
ISTI-CNR
Authors
Leonardo Candela; Donatella Castelli; Paolo Manghi; Alice Tani
License

https://doi.org/10.4121/resource:terms_of_usehttps://doi.org/10.4121/resource:terms_of_use

Description

This dataset groups all the tables supplementing the contents of the article "Data Journals: A Survey", which is going to be published by the Journal of the Association for Information Science and Technology (JASIST). Tables are published with no header. Any details can be found in the article.

Abstract Data occupy a key role in our information society. However, although the amount of published data continues to grow and terms like “data deluge” and “big data” today characterize numerous (research) initiatives, a lot of work is still needed in the direction of publishing data in order to make them effectively discoverable, available, and reusable by others. Several barriers hinder data publishing, from lack of attribution and rewards, vague citation practices, quality issues, to a rather general lack of data sharing culture. Lately, data journals came forward as a solution to overcome some of these barriers. In this study of more than 100 currently existing data journals, we describe the approaches they promote for description, availability, citation, quality and open access or datasets. We close by identifying ways to expand and strengthen the data journals approach as a means to actually promote datasets access and exploitation.

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