https://doi.org/10.4121/resource:terms_of_usehttps://doi.org/10.4121/resource:terms_of_use
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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Reweighted estimates of important Labour Force Survey indicators.
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.
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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.
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.
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: 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...
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.
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The tables provide data for adults (defined as people aged 16 and over) and children (defined as people aged between 0 and 15).
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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.
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License information was derived automatically
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.
Tables on:
<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>
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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
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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
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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.
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License information was derived automatically
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...
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.
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Contains tabulated outputs on each topic from the Health Survey for England, 2019
Table on stock profile.
ODS, 141 KB
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Crime Survey for England and Wales (CSEW) estimates, by each combination of offence group, age, sex, and important demographic characteristics.
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.
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).
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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.
https://doi.org/10.4121/resource:terms_of_usehttps://doi.org/10.4121/resource:terms_of_use
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.