60 datasets found
  1. a

    Average number of hours spent on unpaid care work, by sex, age and location

    • hub.arcgis.com
    Updated Mar 12, 2025
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    UN DESA Statistics Division (2025). Average number of hours spent on unpaid care work, by sex, age and location [Dataset]. https://hub.arcgis.com/datasets/c800169aca8342a0ad24cae011453122
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    Dataset updated
    Mar 12, 2025
    Dataset authored and provided by
    UN DESA Statistics Division
    Area covered
    Description

    Data Series: Average number of hours spent on unpaid care work, by sex, age and location Indicator: I.1 - Average number of hours spent on unpaid domestic and care work, by sex, age and location Source year: 2024 This dataset is part of the Minimum Gender Dataset compiled by the United Nations Statistics Division. Domain: Economic structures, participation in productive activities and access to resources

  2. Outstanding Florida Springs (OFS)

    • geodata.dep.state.fl.us
    • mapdirect-fdep.opendata.arcgis.com
    • +2more
    Updated Aug 2, 2016
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    Florida Department of Environmental Protection (2016). Outstanding Florida Springs (OFS) [Dataset]. https://geodata.dep.state.fl.us/datasets/outstanding-florida-springs-ofs
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    Dataset updated
    Aug 2, 2016
    Dataset authored and provided by
    Florida Department of Environmental Protectionhttp://www.floridadep.gov/
    License

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

    Area covered
    Description

    Section 373.802(4), Florida Statutes (F.S.), defines “Outstanding Florida Springs” or “OFS” to include all historic first magnitude springs, as determined by the department using the most recent Florida Geological Survey springs bulletin, and the following additional six springs: DeLeon, Peacock, Poe, Rock, Wekiva, and Gemini. OFS do not include submarine springs or river rises. There are 30 OFS springs consisting of 24 historic first magnitude springs and the 6 named additional springs. While the statutory definition includes the spring runs associated with these springs and spring groups, this coverage identifies the WBIDs associated with the OFS spring vents. Please reference the metadata for contact information.

  3. T

    General Mills | GIS - Outstanding Shares | Trading Economics

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Apr 15, 2024
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    TRADING ECONOMICS (2024). General Mills | GIS - Outstanding Shares | Trading Economics [Dataset]. https://tradingeconomics.com/gis:us:outstanding-shares
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    excel, json, csv, xmlAvailable download formats
    Dataset updated
    Apr 15, 2024
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 2000 - Sep 8, 2025
    Area covered
    United States
    Description

    General Mills reported 564.55M in Outstanding Shares in April of 2024. Data for General Mills | GIS - Outstanding Shares including historical, tables and charts were last updated by Trading Economics this last September in 2025.

  4. a

    Outstanding Florida Waters

    • hub.arcgis.com
    • geodata.dep.state.fl.us
    • +2more
    Updated Oct 26, 2015
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    Florida Department of Environmental Protection (2015). Outstanding Florida Waters [Dataset]. https://hub.arcgis.com/datasets/681b93ec295f4003abb5a97cd5b51173
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    Dataset updated
    Oct 26, 2015
    Dataset authored and provided by
    Florida Department of Environmental Protection
    Area covered
    Description

    Outstanding Florida Waters, (OFW), are waters designated worthy of special protection because of their natural attributes. This special designation is applied to certain waters (including adjacent wetlands) and is intended to protect and maintain existing acceptable quality standards. The OFW layer is a GIS spatial dataset that represents the OFW boundaries throughout the state of Florida. This project involves adding new data to and modifying existing data within the OFW data layer for better accuracy and representation. Boundaries for Outstanding Florida Waters (OFWs) as described in Section 62-302.700, F.A.C. This layer includes all three types of OFWs: OFW Aquatic Preserves, Special OFWs, and Other OFWs.

  5. a

    County Outstanding Checks

    • data-sacramentocounty.opendata.arcgis.com
    Updated Jan 19, 2019
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    Sacramento County GIS (2019). County Outstanding Checks [Dataset]. https://data-sacramentocounty.opendata.arcgis.com/datasets/ced24b019d944449863d53937c9aa496
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    Dataset updated
    Jan 19, 2019
    Dataset authored and provided by
    Sacramento County GIS
    License

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

    Description

    Contained here is the inventory of all Sacramento County warrants (excluding those warrants that are considered private, such as welfare payments, child support, and employee payroll) that have been issued and mailed, but which remain uncashed six months after their issue date. Uncashed County warrants that are lost can be reissued up to two and a half years from the original issue date.Department of Finance - Auditor Controller - Unclaimed County Warrants (Checks) -- This data was last updated on Jul 25, 2025 at 09:36 AM.

  6. b

    All Property Unpaid Bills from 2023

    • data.buncombecounty.org
    • hub.arcgis.com
    • +1more
    Updated Feb 22, 2023
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    Buncombe County (2023). All Property Unpaid Bills from 2023 [Dataset]. https://data.buncombecounty.org/datasets/all-property-unpaid-bills-from-2023
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    Dataset updated
    Feb 22, 2023
    Dataset authored and provided by
    Buncombe County
    Description

    Ownership, Values, Amounts, and Billing information of all unpaid bills for Buncombe County for 2023

  7. b

    Unpaid Property Bills from 2015

    • data.buncombecounty.org
    • data-avl.opendata.arcgis.com
    • +1more
    Updated Apr 24, 2020
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    Buncombe County (2020). Unpaid Property Bills from 2015 [Dataset]. https://data.buncombecounty.org/maps/bunco::unpaid-property-bills-from-2015
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    Dataset updated
    Apr 24, 2020
    Dataset authored and provided by
    Buncombe County
    Description

    Ownership, Values, Amounts, and Billing information of all unpaid bills for Buncombe County for 2015

  8. N

    Cadw: Register of Historic Landscapes (3rd Party Data)

    • metadata.naturalresources.wales
    search
    Updated Jun 22, 2017
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    (2017). Cadw: Register of Historic Landscapes (3rd Party Data) [Dataset]. https://metadata.naturalresources.wales/geonetwork/srv/api/records/EXT_DS102211
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    searchAvailable download formats
    Dataset updated
    Jun 22, 2017
    Description

    Natural Resources of Wales (NRW) are supplied a number of historic and cultural datasets under a licence from Cadw. Cadw is the Welsh Government's historic environment service working for an accessible and well-protected historic environment for Wales. They were set up with the aim of conserving Wales's heritage, helping people understand and care about their history and helping to sustain the distinctive character of Wales. The Register of Historic Landscapes were digitised from the original hardcopy depictions taken from Registers that were created in 1998 and 2001. They are used in the production and evaluation of EIA's and as an integrated information resource for local authorities' structure and development plans on the coast and for the consideration of planning applications.

  9. b

    Unpaid Property Bills from 2024

    • data.buncombecounty.org
    • hub.arcgis.com
    • +1more
    Updated Mar 7, 2024
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    Buncombe County (2024). Unpaid Property Bills from 2024 [Dataset]. https://data.buncombecounty.org/datasets/unpaid-property-bills-from-2024
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    Dataset updated
    Mar 7, 2024
    Dataset authored and provided by
    Buncombe County
    Description

    Ownership, Values, Amounts, and Billing information of all unpaid bills for Buncombe County for 2024

  10. a

    Average number of hours spent on total work (paid and unpaid), by sex

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated May 16, 2023
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    UN DESA Statistics Division (2023). Average number of hours spent on total work (paid and unpaid), by sex [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/datasets/39375b10784e4dba92de4d51c378335c
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    Dataset updated
    May 16, 2023
    Dataset authored and provided by
    UN DESA Statistics Division
    Area covered
    Description

    Data Series: Average number of hours spent on total work (paid and unpaid), by sex Indicator: I.2 - Average number of hours spent on total work (paid and unpaid), by sex Source year: 2022 This dataset is part of the Minimum Gender Dataset compiled by the United Nations Statistics Division. Domain: Economic structures, participation in productive activities and access to resources

  11. a

    DMV Boot and Tow

    • hub.arcgis.com
    • opendata.dc.gov
    • +2more
    Updated Dec 11, 2020
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    City of Washington, DC (2020). DMV Boot and Tow [Dataset]. https://hub.arcgis.com/maps/DCGIS::dmv-boot-and-tow
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    Dataset updated
    Dec 11, 2020
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    April 1, 2025: data feeds from DMV are currently offline while the agency works to migrate reporting systems. The most recent data available is from December 2024. Open Data DC is working with DMV to restore data feeds as soon as possible.The DC Department of Public Works (DPW) boots or tows vehicles in the District of Columbia that have two or more 61-day-old, unpaid tickets. A boot is a device attached to the vehicle's wheel to immobilize it. The boot can be safely removed only by DPW. A booted vehicle is subject to towing immediately, if the outstanding tickets and boot fee remain unpaid. Boots are normally removed less than 2 hours after fines have been paid. A vehicle may be towed by DPW or the Metropolitan Police Department (MPD) if it is parked so as to create a traffic or safety hazard.

  12. a

    Unpaid Property Bills from 2018

    • hub.arcgis.com
    • data.buncombecounty.org
    • +1more
    Updated Apr 24, 2020
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    Buncombe County (2020). Unpaid Property Bills from 2018 [Dataset]. https://hub.arcgis.com/maps/bunco::unpaid-property-bills-from-2018
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    Dataset updated
    Apr 24, 2020
    Dataset authored and provided by
    Buncombe County
    Description

    Ownership, Values, Amounts, and Billing information of all unpaid bills for Buncombe County for 2018

  13. a

    Area of Outstanding Natural Beauty

    • coastal-data-hub-theriverstrust.hub.arcgis.com
    • data.catchmentbasedapproach.org
    • +2more
    Updated Jul 2, 2019
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    geospatial.data_nrw (2019). Area of Outstanding Natural Beauty [Dataset]. https://coastal-data-hub-theriverstrust.hub.arcgis.com/items/92ee53cc8e5e47e883a099b3d9ace72b
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    Dataset updated
    Jul 2, 2019
    Dataset authored and provided by
    geospatial.data_nrw
    Area covered
    Description

    An AONB is an area of countryside in England, Wales or Northern Ireland which has been designated for conservation due to its significant landscape value. Areas are designated in recognition of their national importance, by the relevant public body

  14. b

    Unpaid Property Bills from 2021

    • data.buncombecounty.org
    • data-avl.opendata.arcgis.com
    • +1more
    Updated Mar 3, 2021
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    Buncombe County (2021). Unpaid Property Bills from 2021 [Dataset]. https://data.buncombecounty.org/maps/unpaid-property-bills-from-2021
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    Dataset updated
    Mar 3, 2021
    Dataset authored and provided by
    Buncombe County
    Description

    Ownership, Values, Amounts, and Billing information of all unpaid bills for Buncombe County for 2021

  15. w

    Hydrography - MO 2014 Outstanding National Resource Water Watersheds (SHP)

    • data.wu.ac.at
    xml, zip
    Updated Aug 19, 2017
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    NSGIC State | GIS Inventory (2017). Hydrography - MO 2014 Outstanding National Resource Water Watersheds (SHP) [Dataset]. https://data.wu.ac.at/schema/data_gov/NzRlZjUwZDktY2Y5NS00ZDlkLTgzNTQtYzI1NzRmZTNkMDll
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    xml, zipAvailable download formats
    Dataset updated
    Aug 19, 2017
    Dataset provided by
    NSGIC State | GIS Inventory
    Area covered
    08326e9603d81a110b97c57f9ebcb9a4c8664027
    Description

    This feature class contains watersheds associated with Missouri's use designations for waters listed in Table D - Outstanding National Resource Waters of the Water Quality Standards rule published in the Missouri Code of State Regulations (CSR), 10 CSR 20-7.031, on January 29, 2014 and approved by the United States Environmental Protection Agency (EPA), on October 22, 2014.

  16. d

    MEP - Coastal Natural Character Outstanding

    • catalogue.data.govt.nz
    • hub.arcgis.com
    • +1more
    Updated Mar 20, 2020
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    Marlborough District Council (2020). MEP - Coastal Natural Character Outstanding [Dataset]. https://catalogue.data.govt.nz/dataset/groups/mep-coastal-natural-character-outstanding2
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    geojson, zip, html, csv, kml, ogc wfs, ogc wms, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Mar 20, 2020
    Dataset provided by
    Marlborough District Council
    Description

    This dataset is part of the proposed Marlborough Environment Plan, as amended by decisions.

    Depicts terrestrial and marine areas in the coastal environment with oustanding natural character.

    For more information, check the Marlborough Environment Plan website.

    Symbology settings for display in GIS applications:

    Cross-hatching, line fill.

    Line colour: RGB 153, 77, 255

  17. a

    Unpaid Property Bills from 2019

    • data-avl.opendata.arcgis.com
    • data.buncombecounty.org
    • +1more
    Updated Apr 24, 2020
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    Buncombe County (2020). Unpaid Property Bills from 2019 [Dataset]. https://data-avl.opendata.arcgis.com/datasets/bunco::unpaid-property-bills-from-2019
    Explore at:
    Dataset updated
    Apr 24, 2020
    Dataset authored and provided by
    Buncombe County
    Description

    Ownership, Values, Amounts, and Billing information of all unpaid bills for Buncombe County for 2019

  18. a

    Outstanding Water

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • gis-modnr.opendata.arcgis.com
    Updated Jun 29, 2020
    + more versions
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    Missouri Department of Natural Resources (2020). Outstanding Water [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/e964dbcffe5e45c693f12d0973d1a9d8
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    Dataset updated
    Jun 29, 2020
    Dataset authored and provided by
    Missouri Department of Natural Resources
    Area covered
    Description

    Outstanding National Waters Outstanding State Waters - Marshes Outstanding State Waters - Rivers and Streams

  19. a

    Unpaid Property Bills from 2020

    • hub.arcgis.com
    • data.buncombecounty.org
    • +1more
    Updated Apr 24, 2020
    + more versions
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    Buncombe County (2020). Unpaid Property Bills from 2020 [Dataset]. https://hub.arcgis.com/maps/bunco::unpaid-property-bills-from-2020
    Explore at:
    Dataset updated
    Apr 24, 2020
    Dataset authored and provided by
    Buncombe County
    Description

    Ownership, Values, Amounts, and Billing information of all unpaid bills for Buncombe County for 2020

  20. a

    Total Population 15 Years and Over by Unpaid Hours Spent Providing Care to...

    • communautaire-esrica-apps.hub.arcgis.com
    • hub.arcgis.com
    • +4more
    Updated Dec 11, 2024
    + more versions
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    The Regional Municipality of York (2024). Total Population 15 Years and Over by Unpaid Hours Spent Providing Care to Seniors 2001 Census [Dataset]. https://communautaire-esrica-apps.hub.arcgis.com/maps/york::total-population-15-years-and-over-by-unpaid-hours-spent-providing-care-to-seniors-2001-census-1
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    Dataset updated
    Dec 11, 2024
    Dataset authored and provided by
    The Regional Municipality of York
    Area covered
    Description

    Presents socio-demographic information of York Region’s population and is aggregated from Statistics Canada’s Census data. For reference purposes, York Region data is compared to those of Ontario, Canada, the Greater Toronto Area and York Region local municipalities.

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UN DESA Statistics Division (2025). Average number of hours spent on unpaid care work, by sex, age and location [Dataset]. https://hub.arcgis.com/datasets/c800169aca8342a0ad24cae011453122

Average number of hours spent on unpaid care work, by sex, age and location

Explore at:
Dataset updated
Mar 12, 2025
Dataset authored and provided by
UN DESA Statistics Division
Area covered
Description

Data Series: Average number of hours spent on unpaid care work, by sex, age and location Indicator: I.1 - Average number of hours spent on unpaid domestic and care work, by sex, age and location Source year: 2024 This dataset is part of the Minimum Gender Dataset compiled by the United Nations Statistics Division. Domain: Economic structures, participation in productive activities and access to resources

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