100+ datasets found
  1. r

    State Budget 2021-22 Consolidated government finance statistics...

    • researchdata.edu.au
    Updated Aug 6, 2021
    + more versions
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    data.vic.gov.au (2021). State Budget 2021-22 Consolidated government finance statistics classification data [Dataset]. https://researchdata.edu.au/state-budget-2021-statistics-classification/1733574
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    Dataset updated
    Aug 6, 2021
    Dataset provided by
    data.vic.gov.au
    License

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

    Description

    This data contains general government sector operating expenses, sourced from the Australian Bureau of Statistics historical data and the Department of Treasury and Finance, categorised by ‘government purpose classification’ (GPC) and ‘classification of the functions of government’ (COFOG).\r \r The Australian system of Government Finance Statistics (GFS) was revised by the Australian Bureau of Statistics, with the release of the Australian System of Government Finance Statistics: Concepts, Sources and Methods 2015 Cat. No. 5514.0.\r \r Implementation of the updated GFS manual has resulted in the COFOG framework replacing the former GPC framework, with effect from the 2018-19 financial year for financial reporting under AASB 1049.\r \r The underlying data from 1961-62 to 1997-98 represents a conversion from the original cash series to an accruals basis by estimating depreciation and superannuation expenses based on statistical modelling.\r \r Although the conversion provides a basis for comparison with total expenses in the current series of accrual GFS information from 1998 (in the attached table), the estimated accrued expense items have not been apportioned to individual purpose classifications.\r \r The absence of these splits between functional classifications in the attached table data therefore represents a break in the series and it is not possible to compare individual purpose categories with those in other tables.\r \r Similarly, the transition from GPC to COFOG represents an additional break in the series and comparability between the two frameworks will not be possible.\r \r The key reporting changes from GPC to COFOG are as follows:\r \r - the number of categories has reduced from 12 under GPC to 10 under COFOG; \r - the fuel and energy, agriculture, forestry, fishing and hunting categories have been abolished and are now part of the new economic affairs category. The majority of the outputs in other economic affairs are also included in this new category;\r - public debt transactions have moved from the other purposes category (i.e. primarily interest expense on borrowings) to general public services category;\r - a new environmental protection category was created to include functions such as waste management, water waste management, pollution and production of biodiversity and landscape, which were previously classified under housing and community amenities category, as well as national and state parks functions from the recreation and culture category; and\r - housing functions such as housing assistance and housing concessions are now part of the social protection category

  2. w

    First Home Owners Grant Statistical Data Tool

    • data.wu.ac.at
    api/tool
    Updated Mar 7, 2016
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    State Revenue Office (2016). First Home Owners Grant Statistical Data Tool [Dataset]. https://data.wu.ac.at/schema/www_data_vic_gov_au/M2JhYmY2ZmItZDVmOS00NGIyLTk2MzQtMGFlOWViMjRmZWJi
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    api/toolAvailable download formats
    Dataset updated
    Mar 7, 2016
    Dataset provided by
    State Revenue Office
    License

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

    Description

    The State Revenue Office (SRO) is now publishing a range of First Home Owner Grant statistics. Find out how many Grants, Bonuses and Boost payments have been received in each postcode in Victoria. The SRO have developed an online search tool which will enable users to select a postcode and receive data by number and type of benefit for various years, and months within each year. Graphs representing the data extracted are also available.

  3. Global big data healthcare analytics market size by application 2016 & 2025

    • statista.com
    Updated Feb 21, 2025
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    Statista (2025). Global big data healthcare analytics market size by application 2016 & 2025 [Dataset]. https://www.statista.com/statistics/909669/global-big-data-in-healthcare-analytics-market-size-by-application/
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    Dataset updated
    Feb 21, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    This statistic shows the size of the global big data analytics services market related to healthcare in 2016 and a forecast for 2025, by application. It is predicted that by 2025 the market for health-related financial analytics services using big data will increase to over 13 billion U.S. dollars.

  4. e

    Data from: Statistical Press Release

    • data.europa.eu
    • brightstripe.co.uk
    html
    Updated Oct 11, 2021
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    Northern Ireland Statistics and Research Agency (2021). Statistical Press Release [Dataset]. https://data.europa.eu/data/datasets/statistical_press_release/
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    htmlAvailable download formats
    Dataset updated
    Oct 11, 2021
    Dataset authored and provided by
    Northern Ireland Statistics and Research Agency
    License

    http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence

    Description

    This statistical press release provides statistics for writs and originating summonses issued, cases disposed and orders made in respect of mortgages in the Chancery Division of the Northern Ireland High Court.

    Source agency: Northern Ireland Statistics and Research Agency

    Designation: National Statistics

    Language: English

    Alternative title: Mortgage Press Release

  5. Concerns about the usage of consumer data for commercial purposes in Europe...

    • statista.com
    Updated Aug 17, 2023
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    Statista (2023). Concerns about the usage of consumer data for commercial purposes in Europe 2022 [Dataset]. https://www.statista.com/statistics/1406479/concern-use-consumer-data-europe/
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    Dataset updated
    Aug 17, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 24, 2022 - Dec 4, 2022
    Area covered
    Europe
    Description

    During a 2022 survey, 70 percent of responding online buyers from 27 European Union countries stated that they were concerned that their personal data could be used for other purposes and did not know with whom it might be shared. Among the presented countries, the share was highest in Spain, at 85 percent.

  6. d

    Department of Labor, Office of Research (Current Employment Statistics NSA...

    • catalog.data.gov
    • data.ct.gov
    • +3more
    Updated Aug 9, 2024
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    data.ct.gov (2024). Department of Labor, Office of Research (Current Employment Statistics NSA 1990 - Current) [Dataset]. https://catalog.data.gov/dataset/department-of-labor-office-of-research-current-employment-statistics-nsa-1990-current
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    Dataset updated
    Aug 9, 2024
    Dataset provided by
    data.ct.gov
    Description

    Historical Employment Statistics 1990 - current. The Current Employment Statistics (CES) more information program provides the most current estimates of nonfarm employment, hours, and earnings data by industry (place of work) for the nation as a whole, all states, and most major metropolitan areas. The CES survey is a federal-state cooperative endeavor in which states develop state and sub-state data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor Statistics (BLS). Estimates produced by the CES program include both full- and part-time jobs. Excluded are self-employment, as well as agricultural and domestic positions. In Connecticut, more than 4,000 employers are surveyed each month to determine the number of the jobs in the State. For more information please visit us at http://www1.ctdol.state.ct.us/lmi/ces/default.asp.

  7. d

    WDFW Item Statistics By Month

    • catalog.data.gov
    • data.wa.gov
    • +1more
    Updated Mar 22, 2025
    + more versions
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    data.wa.gov (2025). WDFW Item Statistics By Month [Dataset]. https://catalog.data.gov/dataset/wdfw-item-statistics-by-month
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    Dataset updated
    Mar 22, 2025
    Dataset provided by
    data.wa.gov
    Description

    Data provided here is used by WDFW’s partners, government entities, schools, private businesses, and the general public. WDFW actively promotes inter-agency data exchange and resource sharing. Every effort is made to provide accurate, complete, and timely information on this site. However, some content may be incomplete or out of date. The content on this site is subject to change without notice. The Washington Department of Fish and Wildlife (WDFW) shall not be liable for any activity involving this data with regard to lost profits or savings or any other consequential damages; or the fitness for use of the data for a particular purpose; or the installation of the data, its use, or the results obtained.

  8. Global number of breached user accounts Q1 2020-Q3 2024

    • statista.com
    Updated Nov 8, 2024
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    Global number of breached user accounts Q1 2020-Q3 2024 [Dataset]. https://www.statista.com/statistics/1307426/number-of-data-breaches-worldwide/
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    Dataset updated
    Nov 8, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    During the third quarter of 2024, data breaches exposed more than 422 million records worldwide. Since the first quarter of 2020, the highest number of data records were exposed in the first quarter of 202, more than 818 million data sets. Data breaches remain among the biggest concerns of company leaders worldwide. The most common causes of sensitive information loss were operating system vulnerabilities on endpoint devices. Which industries see the most data breaches? Meanwhile, certain conditions make some industry sectors more prone to data breaches than others. According to the latest observations, the public administration experienced the highest number of data breaches between 2021 and 2022. The industry saw 495 reported data breach incidents with confirmed data loss. The second were financial institutions, with 421 data breach cases, followed by healthcare providers. Data breach cost Data breach incidents have various consequences, the most common impact being financial losses and business disruptions. As of 2023, the average data breach cost across businesses worldwide was 4.45 million U.S. dollars. Meanwhile, a leaked data record cost about 165 U.S. dollars. The United States saw the highest average breach cost globally, at 9.48 million U.S. dollars.

  9. SSI Monthly Statistics - Current Report

    • catalog.data.gov
    Updated Feb 1, 2023
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    Social Security Administration (2023). SSI Monthly Statistics - Current Report [Dataset]. https://catalog.data.gov/dataset/ssi-monthly-statistics
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    Dataset updated
    Feb 1, 2023
    Dataset provided by
    Social Security Administrationhttp://www.ssa.gov/
    Description

    Monthly data on federally administered Supplemental Security Income payments.

  10. d

    CRIME STATISTICS DATA ANALYTICS

    • search.dataone.org
    • borealisdata.ca
    • +1more
    Updated Dec 28, 2023
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    Kwong, Cheryl; Anweiler, Drew; Sarafraz, Mary (2023). CRIME STATISTICS DATA ANALYTICS [Dataset]. http://doi.org/10.5683/SP2/IE6NRY
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Kwong, Cheryl; Anweiler, Drew; Sarafraz, Mary
    Description

    Crime isn't a topic most people want to use mental energy to think about. We want to avoid harm, protect our loved ones, and hold on to what we claim is ours. So how do we remain vigilant without digging too deep into the filth that is crime? Data, of course. The focus of our study is to explore possible trends between crime and communities in the city of Calgary. Our purpose is visualize Calgary criminal behaviour in order to help increase awareness for both citizens and law enforcement. Through the use of our visuals, individuals can make more informed decisions to improve the overall safety of their lives. Some of the main concerns of the study include: how crime rates increase with population, which areas in Calgary have the most crime, and if crime adheres to time-sensative patterns.

  11. Hydrographic and Impairment Statistics Database: FIIS

    • catalog.data.gov
    • gimi9.com
    • +1more
    Updated Jun 4, 2024
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    National Park Service (2024). Hydrographic and Impairment Statistics Database: FIIS [Dataset]. https://catalog.data.gov/dataset/hydrographic-and-impairment-statistics-database-fiis
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    Dataset updated
    Jun 4, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Description

    Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).

  12. Data from: Combined Statistical Areas

    • azgeo-open-data-agic.hub.arcgis.com
    • azgeo-data-hub-agic.hub.arcgis.com
    • +3more
    Updated Jun 5, 2024
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    GeoPlatform ArcGIS Online (2024). Combined Statistical Areas [Dataset]. https://azgeo-open-data-agic.hub.arcgis.com/datasets/geoplatform::combined-statistical-areas-3
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    https://arcgis.com/
    Authors
    GeoPlatform ArcGIS Online
    Area covered
    Description

    Combined Statistical Areas (CSAs) consist of two or more adjacent CBSAs that have substantial employment interchange. The CBSAs that combine to create a CSA retain separate identities within the larger CSA. Because CSAs represent groupings of metropolitan and/or micropolitan statistical areas, they should not be ranked or compared with individual metropolitan and micropolitan statistical areas.Download: https://www2.census.gov/geo/tiger/TGRGDB24/tlgdb_2024_a_us_nationgeo.gdb.zip Layer: Combined_Statistical_AreaMetadata: https://meta.geo.census.gov/data/existing/decennial/GEO/GPMB/TIGERline/Current_19115/series_tl_2023_csa.shp.iso.xml

  13. s

    Data from: Facebook Users

    • searchlogistics.com
    Updated Mar 17, 2025
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    (2025). Facebook Users [Dataset]. https://www.searchlogistics.com/learn/statistics/social-media-user-statistics/
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    Dataset updated
    Mar 17, 2025
    License

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

    Description

    Facebook is fast approaching 3 billion monthly active users. That’s about 36% of the world’s entire population that log in and use Facebook at least once a month.

  14. d

    HES-DID Data Linkage Report

    • digital.nhs.uk
    pdf
    Updated Jun 5, 2015
    + more versions
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    (2015). HES-DID Data Linkage Report [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/hes-did-data-linkage-report
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    pdf(281.3 kB), pdf(165.3 kB), pdf(183.1 kB)Available download formats
    Dataset updated
    Jun 5, 2015
    License

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

    Time period covered
    Apr 1, 2014 - Jan 31, 2015
    Area covered
    England
    Description

    This is the latest statistical publication of linked HES (Hospital Episode Statistics) and DID (Diagnostic Imaging Data set) data held by the Health and Social Care Information Centre. The HES-DID linkage provides the ability to undertake national (within England) analysis along acute patient pathways to understand typical imaging requirements for given procedures, and/or the outcomes after particular imaging has been undertaken, thereby enabling a much deeper understanding of outcomes of imaging and to allow assessment of variation in practice. This publication aims to highlight to users the availability of this updated linkage and provide users of the data with some standard information to assess their analysis approach against. The two data sets have been linked using specific patient identifiers collected in HES and DID. The linkage allows the data sets to be linked from April 2012 when the DID data was first collected; however this report focuses on patients who were present in the either data set in the period 1 April 2014 to 31 January 2015 only. For DID this is provisional 2014-15 data. For HES this is provisional 2014-15 data. The linkage used for this publication was created on 7 May 2015 and released together with this publication on 5 June 2015. The linkage utilises all historic HES patient identifying data up to 30 April 2015 and all patient identifying DID data submitted prior to 28 April 2015

  15. d

    Teaching undergraduates with quantitative data in the social sciences at...

    • search.dataone.org
    • dataone.org
    • +3more
    Updated Jun 14, 2024
    + more versions
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    Renata Gonçalves Curty; Rebecca Greer; Torin White (2024). Teaching undergraduates with quantitative data in the social sciences at University of California Santa Barbara [Dataset]. https://search.dataone.org/view/sha256%3A62b393a77343a0b237b65b163d9e5ce3a697794d16469015c1f0822dba227e1e
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    Dataset updated
    Jun 14, 2024
    Dataset provided by
    Dryad Digital Repository
    Authors
    Renata Gonçalves Curty; Rebecca Greer; Torin White
    Time period covered
    Apr 15, 2022
    Description

    The interview data was gathered for a project that investigated the practices of instructors who use quantitative data to teach undergraduate courses within the Social Sciences. The study was undertaken by employees of the University of California, Santa Barbara (UCSB) Library, who participated in this research project with 19 other colleges and universities across the U.S. under the direction of Ithaka S+R. Ithaka S+R is a New York-based research organization, which, among other goals, seeks to develop strategies, services, and products to meet evolving academic trends to support faculty and students.

    The field of Social Sciences has been notoriously known for valuing the contextual component of data and increasingly entertaining more quantitative and computational approaches to research in response to the prevalence of data literacy skills needed to navigate both personal and professional contexts. Thus, this study becomes particularly timely to identify current instructors’ practi..., The project followed a qualitative and exploratory approach to understand current practices of faculty teaching with data. The study was IRB approved and was exempt by the UCSB’s Office of Research in July 2020 (Protocol 1-20-0491).Â

    The identification and recruitment of potential participants took into account the selection criteria pre-established by Ithaka S+R: a) instructors of courses within the Social Sciences, considering the field as broadly defined, and making the best judgment in cases the discipline intersects with other fields; b) instructors who teach undergraduate courses or courses where most of the students are at the undergraduate level; c) instructors of any rank, including adjuncts and graduate students; as long as they were listed as instructors of record of the selected courses; d) instructors who teach courses were students engage with quantitative/computational data.Â

    The sampling process followed a combination of strategies to more easily identify instructo..., The data folder contains 10Â pdf files with de-identified transcriptions of the interviews and the pdf files with the recruitment email and the interview guide.Â

  16. Marketing spend on third-party audience data in the U.S. 2017-2021

    • statista.com
    Updated Dec 10, 2024
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    Statista (2024). Marketing spend on third-party audience data in the U.S. 2017-2021 [Dataset]. https://www.statista.com/statistics/1202754/third-party-audience-data-spending-usa/
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    Dataset updated
    Dec 10, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2021, expenditure on third party audience data in the United States amounted to 22 billion U.S. dollars, out of which 13.3 billion was spent on data itself and 8.7 billion on audience data activation solutions.

  17. Data from: Sample statistics.

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Zhenguo Liu; Ting Ji; Ling Yin; Jie Shen; Fang Shen; Guohong Chen (2023). Sample statistics. [Dataset]. http://doi.org/10.1371/journal.pone.0081001.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Zhenguo Liu; Ting Ji; Ling Yin; Jie Shen; Fang Shen; Guohong Chen
    License

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

    Description

    Agilent Bioanalyzer 2100 RNA integrity number.The total unigene number in the DFCI Honey Bee Gene Index database is 25007; http://compbio.dfci.harvard.edu/cgi-bin/tgi/gimain.pl?gudb=honeybee.**The unique matched genes from all five samples cover the DFCI database completely.

  18. d

    HES-MHMDS Data Linkage Report

    • digital.nhs.uk
    pdf
    Updated Jun 13, 2014
    + more versions
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    (2014). HES-MHMDS Data Linkage Report [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/hes-mhmds-data-linkage-report
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    pdf(254.9 kB), pdf(176.6 kB), pdf(164.4 kB)Available download formats
    Dataset updated
    Jun 13, 2014
    License

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

    Time period covered
    Apr 1, 2013 - Feb 28, 2014
    Area covered
    England
    Description

    This is the latest monthly (February 2014) statistical publication in relation to the linked HES (Hospital Episode Statistics) and MHMDS (Mental Health Minimum Data Set) data. The two data sets have been linked using specific patient identifiers collected in HES and MHMDS. The linkage allows the data sets to be linked in this manner from 2006-07; however, this report focuses on patients who were present in the two data sets in the period April 2013 to February 2014 only. The bridging file used for this publication was also released on 13 June 2014; it utilises the latest published Provisional (Monthly) HES data and year-to-date MHMDS data relating to the period April 2013 to February 2014. The HES-MHMDS linkage provides the ability to undertake national (within England) analysis along acute patient pathways for mental health service users' interactions with acute secondary care.

  19. Federal Justice Statistics Program: Offenders Admitted to Prison, 2007

    • catalog.data.gov
    • icpsr.umich.edu
    • +2more
    Updated Feb 13, 2023
    + more versions
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    Bureau of Justice Statistics (2023). Federal Justice Statistics Program: Offenders Admitted to Prison, 2007 [Dataset]. https://catalog.data.gov/dataset/federal-justice-statistics-program-offenders-admitted-to-prison-2007
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    Dataset updated
    Feb 13, 2023
    Dataset provided by
    Bureau of Justice Statisticshttp://bjs.ojp.gov/
    Description

    The data contain records of sentenced offenders committed to the custody of the Bureau of Prisons (BOP) during fiscal year 2007. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database, as well as "SAF" variables that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 7.9-7.16. Variables containing identifying information (e.g., name, Social Security Number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.

  20. Data from: World Mineral Statistics Dataset

    • metadata.bgs.ac.uk
    • brightstripe.co.uk
    • +3more
    ogc api - features +3
    Updated 1918
    + more versions
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    British Geological Survey (1918). World Mineral Statistics Dataset [Dataset]. https://metadata.bgs.ac.uk/geonetwork/srv/api/records/9df8df51-6332-37a8-e044-0003ba9b0d98
    Explore at:
    ogc:wfs, ogc api - features, www:link-1.0-http--link, ogc:wmsAvailable download formats
    Dataset updated
    1918
    Dataset authored and provided by
    British Geological Surveyhttps://www.bgs.ac.uk/
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    http://inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/INSPIRE_Directive_Article13_1dhttp://inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/INSPIRE_Directive_Article13_1d

    Area covered
    Earth
    Description

    The British Geological Survey has one of the largest databases in the world on the production and trade of minerals. The dataset contains annual production statistics by mass for more than 70 mineral commodities covering the majority of economically important and internationally-traded minerals, metals and mineral-based materials. For each commodity the annual production statistics are recorded for individual countries, grouped by continent. Import and export statistics are also available for years up to 2002. Maintenance of the database is funded by the Science Budget and output is used by government, private industry and others in support of policy, economic analysis and commercial strategy. As far as possible the production data are compiled from primary, official sources. Quality assurance is maintained by participation in such groups as the International Consultative Group on Non-ferrous Metal Statistics. Individual commodity and country tables are available for sale on request.

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data.vic.gov.au (2021). State Budget 2021-22 Consolidated government finance statistics classification data [Dataset]. https://researchdata.edu.au/state-budget-2021-statistics-classification/1733574

State Budget 2021-22 Consolidated government finance statistics classification data

Explore at:
Dataset updated
Aug 6, 2021
Dataset provided by
data.vic.gov.au
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Description

This data contains general government sector operating expenses, sourced from the Australian Bureau of Statistics historical data and the Department of Treasury and Finance, categorised by ‘government purpose classification’ (GPC) and ‘classification of the functions of government’ (COFOG).\r \r The Australian system of Government Finance Statistics (GFS) was revised by the Australian Bureau of Statistics, with the release of the Australian System of Government Finance Statistics: Concepts, Sources and Methods 2015 Cat. No. 5514.0.\r \r Implementation of the updated GFS manual has resulted in the COFOG framework replacing the former GPC framework, with effect from the 2018-19 financial year for financial reporting under AASB 1049.\r \r The underlying data from 1961-62 to 1997-98 represents a conversion from the original cash series to an accruals basis by estimating depreciation and superannuation expenses based on statistical modelling.\r \r Although the conversion provides a basis for comparison with total expenses in the current series of accrual GFS information from 1998 (in the attached table), the estimated accrued expense items have not been apportioned to individual purpose classifications.\r \r The absence of these splits between functional classifications in the attached table data therefore represents a break in the series and it is not possible to compare individual purpose categories with those in other tables.\r \r Similarly, the transition from GPC to COFOG represents an additional break in the series and comparability between the two frameworks will not be possible.\r \r The key reporting changes from GPC to COFOG are as follows:\r \r - the number of categories has reduced from 12 under GPC to 10 under COFOG; \r - the fuel and energy, agriculture, forestry, fishing and hunting categories have been abolished and are now part of the new economic affairs category. The majority of the outputs in other economic affairs are also included in this new category;\r - public debt transactions have moved from the other purposes category (i.e. primarily interest expense on borrowings) to general public services category;\r - a new environmental protection category was created to include functions such as waste management, water waste management, pollution and production of biodiversity and landscape, which were previously classified under housing and community amenities category, as well as national and state parks functions from the recreation and culture category; and\r - housing functions such as housing assistance and housing concessions are now part of the social protection category

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