100+ datasets found
  1. Integrated Client Database

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Jul 4, 2025
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    Social Security Administration (2025). Integrated Client Database [Dataset]. https://catalog.data.gov/dataset/integrated-client-database
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    Dataset updated
    Jul 4, 2025
    Dataset provided by
    Social Security Administrationhttp://ssa.gov/
    Description

    Database used to store client data both Identity and customer relationship management.

  2. Database Infrastructure for Mass Spectrometry - Per- and Polyfluoroalkyl...

    • data.nist.gov
    • catalog.data.gov
    Updated Jul 5, 2023
    + more versions
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    National Institute of Standards and Technology (2023). Database Infrastructure for Mass Spectrometry - Per- and Polyfluoroalkyl Substances [Dataset]. http://doi.org/10.18434/mds2-2905
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    Dataset updated
    Jul 5, 2023
    Dataset provided by
    National Institute of Standards and Technologyhttp://www.nist.gov/
    License

    https://www.nist.gov/open/licensehttps://www.nist.gov/open/license

    Description

    Data here contain and describe an open-source structured query language (SQLite) portable database containing high resolution mass spectrometry data (MS1 and MS2) for per- and polyfluorinated alykl substances (PFAS) and associated metadata regarding their measurement techniques, quality assurance metrics, and the samples from which they were produced. These data are stored in a format adhering to the Database Infrastructure for Mass Spectrometry (DIMSpec) project. That project produces and uses databases like this one, providing a complete toolkit for non-targeted analysis. See more information about the full DIMSpec code base - as well as these data for demonstration purposes - at GitHub (https://github.com/usnistgov/dimspec) or view the full User Guide for DIMSpec (https://pages.nist.gov/dimspec/docs). Files of most interest contained here include the database file itself (dimspec_nist_pfas.sqlite) as well as an entity relationship diagram (ERD.png) and data dictionary (DIMSpec for PFAS_1.0.1.20230615_data_dictionary.json) to elucidate the database structure and assist in interpretation and use.

  3. d

    Legislator Database

    • catalog.data.gov
    • data.ct.gov
    • +3more
    Updated Jul 12, 2025
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    data.ct.gov (2025). Legislator Database [Dataset]. https://catalog.data.gov/dataset/legislator-database
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    Dataset updated
    Jul 12, 2025
    Dataset provided by
    data.ct.gov
    Description

    A listing of State Representatives and State Senators. For more information see: http://www.cga.ct.gov/asp/menu/legdownload.asp

  4. C

    California Protected Areas Database

    • data.ca.gov
    • data.cnra.ca.gov
    • +4more
    Updated Jun 27, 2025
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    California Natural Resources Agency (2025). California Protected Areas Database [Dataset]. https://data.ca.gov/dataset/california-protected-areas-database
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    arcgis geoservices rest api, shpAvailable download formats
    Dataset updated
    Jun 27, 2025
    Dataset provided by
    California Protected Areas
    Authors
    California Natural Resources Agency
    License

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

    Area covered
    California
    Description

    The California Protected Areas Database (CPAD) is a GIS database of lands that are owned in fee and protected for open space purposes by over 1,000 public agencies or non-profit organizations. It is the authoritative GIS database of parks and open space in California.

    CPAD is maintained and published by GreenInfo Network (www.greeninfo.org). GreenInfo Network publishes CPAD twice annually.

  5. Synthetic Healthcare Database for Research (SyH-DR)

    • healthdata.gov
    • data.virginia.gov
    • +2more
    application/rdfxml +5
    Updated Sep 15, 2023
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    Agency for Healthcare Research and Quality (AHRQ) (2023). Synthetic Healthcare Database for Research (SyH-DR) [Dataset]. https://healthdata.gov/National/-Synthetic-Healthcare-Database-for-Research-SyH-DR/88gj-w5in
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    csv, json, tsv, application/rdfxml, application/rssxml, xmlAvailable download formats
    Dataset updated
    Sep 15, 2023
    Dataset provided by
    Agency for Healthcare Research and Qualityhttp://www.ahrq.gov/
    Authors
    Agency for Healthcare Research and Quality (AHRQ)
    Description

    The Agency for Healthcare Research and Quality (AHRQ) created SyH-DR from eligibility and claims files for Medicare, Medicaid, and commercial insurance plans in calendar year 2016. SyH-DR contains data from a nationally representative sample of insured individuals for the 2016 calendar year. SyH-DR uses synthetic data elements at the claim level to resemble the marginal distribution of the original data elements. SyH-DR person-level data elements are not synthetic, but identifying information is aggregated or masked.

  6. Returns and detention - Historic datasets

    • gov.uk
    Updated Aug 24, 2023
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    Home Office (2023). Returns and detention - Historic datasets [Dataset]. https://www.gov.uk/government/statistical-data-sets/returns-and-detention-datasets
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    Dataset updated
    Aug 24, 2023
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Home Office
    Description

    This page contains data for the immigration system statistics up to March 2023.

    For current immigration system data, visit ‘Immigration system statistics data tables’.

    Immigration detention

    https://assets.publishing.service.gov.uk/media/6462567294f6df000cf5ea90/detention-datasets-mar-2023.xlsx">Immigration detention (MS Excel Spreadsheet, 9.8 MB)
    Det_D01: Number of entries into immigration detention by nationality, age, sex and initial place of detention
    Det_D02: Number of people in immigration detention at the end of each quarter by nationality, age, sex, current place of detention and length of detention
    Det_D03: Number of occurrences of people leaving detention by nationality, age, sex, reason for leaving detention and length of detention
    This is not the latest data

    Returns

    https://assets.publishing.service.gov.uk/media/646357c494f6df0010f5eb0a/returns-datasets-mar-2023.xlsx">Returns (MS Excel Spreadsheet, 14.4 MB)
    Ret_D01: Number of returns from the UK, by nationality, age, sex, type of return and return destination group
    Ret_D02: Number of returns from the UK, by type of return and country of destination
    Ret_D03: Number of foreign national offender returns from the UK, by nationality and return destination group
    Ret_D04: Number of foreign national offender returns from the UK, by destination
    This is not the latest data

  7. Processed Products Database System

    • fisheries.noaa.gov
    • catalog.data.gov
    Updated Dec 22, 2016
    + more versions
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    NMFS Office of Science and Technology (2016). Processed Products Database System [Dataset]. https://www.fisheries.noaa.gov/inport/item/3476
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    Dataset updated
    Dec 22, 2016
    Dataset provided by
    National Marine Fisheries Servicehttps://www.fisheries.noaa.gov/
    Time period covered
    1969 - Jul 11, 2125
    Area covered
    United States
    Description

    Collection of annual data on processed seafood products. The Division provides authoritative advice, coordination and guidance on matters related to the collection, analysis and dissemination of biological, economic, market and sociological statistics by NMFS and state agencies. This data set contains quantity and value data for processed seafood products as well as employment data for included...

  8. d

    Major US Open Data Domains

    • catalog.data.gov
    • data.kingcounty.gov
    Updated Feb 2, 2024
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    data.kingcounty.gov (2024). Major US Open Data Domains [Dataset]. https://catalog.data.gov/dataset/major-us-open-data-domains
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    Dataset updated
    Feb 2, 2024
    Dataset provided by
    data.kingcounty.gov
    Area covered
    United States
    Description

    An incomplete collection of open data domains throughout the U.S. (intended for comparison with King County open data)

  9. u

    Data from: Conservation Practice Effectiveness (CoPE) Database

    • agdatacommons.nal.usda.gov
    • catalog.data.gov
    xlsx
    Updated Dec 18, 2023
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    Douglas Smith; Michael White; Eileen McLellan; Rehanon Pampell; Daren Harmel (2023). Conservation Practice Effectiveness (CoPE) Database [Dataset]. http://doi.org/10.15482/USDA.ADC/1504544
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    xlsxAvailable download formats
    Dataset updated
    Dec 18, 2023
    Dataset provided by
    Ag Data Commons
    Authors
    Douglas Smith; Michael White; Eileen McLellan; Rehanon Pampell; Daren Harmel
    License

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

    Description

    The Conservation Practice Effectiveness Database compiles information on the effectiveness of a suite of conservation practices. This database presents a compilation of data on the effectiveness of innovative practices developed to treat contaminants in surface runoff and tile drainage water from agricultural landscapes. Traditional conservation practices such as no-tillage and conservation crop rotation are included in the database, as well as novel practices such as drainage water management, blind inlets, and denitrification bioreactors. This will be particularly useful to conservation planners seeking new approaches to water quality problems associated with dissolved constituents, such as nitrate or soluble reactive phosphorus (SRP), and for researchers seeking to understand the circumstances in which such practices are most effective. Another novel feature of the database is the presentation of information on how individual conservation practices impact multiple water quality concerns. This information will be critical to enabling conservationists and policy makers to avoid (or at least be aware of) undesirable tradeoffs, whereby great efforts are made to improve water quality related to one resource concern (e.g., sediment) but exacerbate problems related to other concerns (e.g., nitrate or SRP). Finally, we note that the Conservation Practice Effectiveness Database can serve as a source of the soft data needed to calibrate simulation models assessing the potential water quality tradeoffs of conservation practices, including those that are still being developed. This database is updated and refined annually. Resources in this dataset:Resource Title: 2019 Conservation Practice Effectiveness (CoPE) Database. File Name: Conservation_Practice_Effectiveness_2019.xlsxResource Description: This version of the database was published in 2019.

  10. S

    Daily Corporation and Other Entity Filing Data

    • data.ny.gov
    • datasets.ai
    • +1more
    application/rdfxml +5
    Updated Jun 29, 2025
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    New York State Department of State (2025). Daily Corporation and Other Entity Filing Data [Dataset]. https://data.ny.gov/Economic-Development/Daily-Corporation-and-Other-Entity-Filing-Data/k4vb-judh
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    csv, tsv, json, application/rdfxml, application/rssxml, xmlAvailable download formats
    Dataset updated
    Jun 29, 2025
    Dataset authored and provided by
    New York State Department of Statehttp://www.dos.ny.gov/
    Description

    This data contains Corporations and other Entities filing information that were processed in the previous thirty days. Each line contains the Department of State ID number, Film ID, Date Filed, Effective Date, Entity Name, the law under which the filing was made and other pertinent filing information.

  11. Data from: Rat Genome Database (RGD)

    • healthdata.gov
    • data.virginia.gov
    • +2more
    application/rdfxml +5
    Updated Feb 13, 2021
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    (2021). Rat Genome Database (RGD) [Dataset]. https://healthdata.gov/dataset/Rat-Genome-Database-RGD-/j76d-psg3
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    xml, application/rdfxml, tsv, application/rssxml, csv, jsonAvailable download formats
    Dataset updated
    Feb 13, 2021
    Description

    The Rat Genome Database (RGD) is a collaborative effort between leading research institutions involved in rat genetic and genomic research to collect, consolidate, and integrate data generated from ongoing rat genetic and genomic research efforts and make these data widely available to the scientific community.

  12. Eldercare Locator Database

    • healthdata.gov
    • data.virginia.gov
    • +2more
    application/rdfxml +5
    Updated Feb 13, 2021
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    (2021). Eldercare Locator Database [Dataset]. https://healthdata.gov/dataset/Eldercare-Locator-Database/83xt-3i6a
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    application/rssxml, csv, tsv, application/rdfxml, xml, jsonAvailable download formats
    Dataset updated
    Feb 13, 2021
    Description

    The Eldercare Locator is a searchable database that allows a user to search via zip code or city/ state for agencies at the State and local levels that provide services to older adults.

  13. COVID-19 Diagnostic Laboratory Testing (PCR Testing) Time Series

    • healthdata.gov
    • data.virginia.gov
    • +2more
    Updated Dec 14, 2020
    + more versions
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    U.S. Department of Health & Human Services (2020). COVID-19 Diagnostic Laboratory Testing (PCR Testing) Time Series [Dataset]. https://healthdata.gov/dataset/COVID-19-Diagnostic-Laboratory-Testing-PCR-Testing/j8mb-icvb
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    application/rdfxml, tsv, csv, xml, application/rssxml, kmz, application/geo+json, kmlAvailable download formats
    Dataset updated
    Dec 14, 2020
    Dataset provided by
    United States Department of Health and Human Serviceshttp://www.hhs.gov/
    Authors
    U.S. Department of Health & Human Services
    License

    Open Data Commons Attribution License (ODC-By) v1.0https://www.opendatacommons.org/licenses/by/1.0/
    License information was derived automatically

    Description

    After May 3, 2024, this dataset and webpage will no longer be updated because hospitals are no longer required to report data on COVID-19 hospital admissions, and hospital capacity and occupancy data, to HHS through CDC’s National Healthcare Safety Network. Data voluntarily reported to NHSN after May 1, 2024, will be available starting May 10, 2024, at COVID Data Tracker Hospitalizations.


    This time series dataset includes viral COVID-19 laboratory test [Polymerase chain reaction (PCR)] results from over 1,000 U.S. laboratories and testing locations including commercial and reference laboratories, public health laboratories, hospital laboratories, and other testing locations. Data are reported to state and jurisdictional health departments in accordance with applicable state or local law and in accordance with the Coronavirus Aid, Relief, and Economic Security (CARES) Act (CARES Act Section 18115).

    Data are provisional and subject to change.

    Data presented here is representative of diagnostic specimens being tested - not individual people - and excludes serology tests where possible. Data presented might not represent the most current counts for the most recent 3 days due to the time it takes to report testing information. The data may also not include results from all potential testing sites within the jurisdiction (e.g., non-laboratory or point of care test sites) and therefore reflect the majority, but not all, of COVID-19 testing being conducted in the United States.

    Sources: CDC COVID-19 Electronic Laboratory Reporting (CELR), Commercial Laboratories, State Public Health Labs, In-House Hospital Labs

    Data for each state is sourced from either data submitted directly by the state health department via COVID-19 electronic laboratory reporting (CELR), or a combination of commercial labs, public health labs, and in-house hospital labs. Data is taken from CELR for states that either submit line level data or submit aggregate counts which do not include serology tests.

  14. NMFS Menhaden CDFR (Logbook) Database

    • fisheries.noaa.gov
    • s.cnmilf.com
    • +1more
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    Southeast Fisheries Science Center, NMFS Menhaden CDFR (Logbook) Database [Dataset]. https://www.fisheries.noaa.gov/inport/item/28018
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    Dataset provided by
    Southeast Fisheries Science Center
    Time period covered
    1983 - Jul 11, 2125
    Area covered
    Description

    Data set consists of daily logs by menhaden purse-seine vessels w/ data on individual purse-seine set size, location, and date

  15. Drinking Water Treatability Database (TDB)

    • catalog.data.gov
    • data.globalchange.gov
    • +2more
    Updated Mar 16, 2024
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    U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW) (2024). Drinking Water Treatability Database (TDB) [Dataset]. https://catalog.data.gov/dataset/drinking-water-treatability-database-tdb
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    Dataset updated
    Mar 16, 2024
    Dataset provided by
    United States Environmental Protection Agencyhttp://www.epa.gov/
    Description

    The Drinking Water Treatability Database (TDB) presents referenced information on the control of contaminants in drinking water. It allows drinking water utilities, first responders to spills or emergencies, treatment process designers, research organizations, regulators and others to access referenced information gathered from thousands of literature sources on regulated and unregulated contaminants.

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

    • data.wu.ac.at
    • datadiscoverystudio.org
    • +1more
    Updated May 10, 2018
    + more versions
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    Department of the Interior (2018). Protected Areas Database of the United States (PAD-US) [Dataset]. https://data.wu.ac.at/schema/data_gov/M2EzYzUwM2EtYzE0OS00MDRiLWFmMmYtNTA3ZDExY2RiMDlk
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    the file downloads in a .zip formatAvailable download formats
    Dataset updated
    May 10, 2018
    Dataset provided by
    United States Department of the Interiorhttp://www.doi.gov/
    Area covered
    4291c7e62e080410fa866207746ad004ad9efc02, United States
    Description

    The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .

  17. U.S. State and Territorial Stay-At-Home Orders: March 15, 2020 – August 15,...

    • data.cdc.gov
    • data.virginia.gov
    • +2more
    application/rdfxml +5
    Updated Sep 10, 2021
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    Mara Howard-Williams, Public Health Law Program, Center for State, Tribal, Local, and Territorial Support, Centers for Disease Control and Prevention (2021). U.S. State and Territorial Stay-At-Home Orders: March 15, 2020 – August 15, 2021 by County by Day [Dataset]. https://data.cdc.gov/Policy-Surveillance/U-S-State-and-Territorial-Stay-At-Home-Orders-Marc/y2iy-8irm
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    csv, json, application/rdfxml, tsv, xml, application/rssxmlAvailable download formats
    Dataset updated
    Sep 10, 2021
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    Mara Howard-Williams, Public Health Law Program, Center for State, Tribal, Local, and Territorial Support, Centers for Disease Control and Prevention
    Area covered
    United States
    Description

    State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance.

    Data were collected to determine when individuals in states and territories were subject to executive orders, administrative orders, resolutions, and proclamations for COVID-19 that require or recommend people stay in their homes. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level.

    These data are derived from the publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly require or recommend individuals stay at home found by the CDC, COVID-19 Community Intervention and At-Risk Task Force, Monitoring and Evaluation Team & CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 15, 2020 through August 15, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. These data do not include mandatory business closures, curfews, or limitations on public or private gatherings. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.

  18. D

    CDC COVID-19 Cases and Deaths Ensemble Forecast Archive

    • data.cdc.gov
    • data.virginia.gov
    application/rdfxml +5
    Updated Apr 26, 2023
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    COVID-19 Forecast Hub (2023). CDC COVID-19 Cases and Deaths Ensemble Forecast Archive [Dataset]. https://data.cdc.gov/Models/CDC-COVID-19-Cases-and-Deaths-Ensemble-Forecast-Ar/ci7c-73kg
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    application/rdfxml, csv, json, tsv, application/rssxml, xmlAvailable download formats
    Dataset updated
    Apr 26, 2023
    Dataset authored and provided by
    COVID-19 Forecast Hub
    License

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

    Description

    This dataset contains forecasted weekly numbers of reported COVID-19 incident cases, incident deaths, and cumulative deaths in the United States, previously reported on COVID Data Tracker (https://covid.cdc.gov/covid-data-tracker/#datatracker-home). These forecasts were generated using mathematical models by CDC partners in the COVID-19 Forecast Hub (https://covid19forecasthub.org/doc/ensemble/). A CDC ensemble model was produced every week using the submitted models from that week at the national, and state/territory level.

    This dataset is intended to mirror the observed and forecasted data, previously available for download on the CDC’s COVID Data Tracker. Mortality forecasts for both new and cumulative reported COVID-19 deaths were produced at the state and territory level and national level. Forecasts of new reported COVID-19 cases were produced at the county, state/territory, and national level. Please note that this dataset is not complete for every model, date, location or combination thereof. Specifically, county level submissions for COVID-19 incident cases were accepted, but not required, and are missing or incomplete for many models and dates. State and territory-level forecasts are more complete, but not all models submitted forecasts for all locations, dates, and targets (new reported deaths, new reported cases, and cumulative reported deaths). Forecasts for COVID-19 incident cases were discontinued in February 2022. Forecasts for COVID-19 cumulative and incident deaths were discontinued in March 2023.

  19. r

    GIP AssetList Database v1.2 20150130

    • researchdata.edu.au
    • data.gov.au
    • +1more
    Updated Mar 30, 2016
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    Bioregional Assessment Program (2016). GIP AssetList Database v1.2 20150130 [Dataset]. https://researchdata.edu.au/gip-assetlist-database-v12-20150130/2986327
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    Dataset updated
    Mar 30, 2016
    Dataset provided by
    data.gov.au
    Authors
    Bioregional Assessment Program
    Description

    Abstract

    \[x\[This dataset was superseded by GIP AssetList Database v1.3 20150212

    GUID: e0a8bc96-e97b-44d4-858e-abbb06ddd87f

    on 12/2/2015\]x\]

    The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

    This dataset contains the spatial and non-spatial (attribute) components of the Gippsland bioregion Asset List as two .mdb files, which are readable as an MS Access database or as an ESRI Personal Geodatabase.

    Under the BA program, a spatial assets database is developed for each defined bioregional assessment project. The spatial elements that underpin the identification of water dependent assets are identified in the first instance by regional NRM organisations (via the WAIT tool) and supplemented with additional elements from national and state/territory government datasets. All reports received associated with the WAIT process for Gippsland are included in the zip file as part of this dataset.

    Elements are initially included in the preliminary assets database if they are partly or wholly within the bioregion's preliminary assessment extent (Materiality Test 1, M1). Elements are then grouped into assets which are evaluated by project teams to determine whether they meet the second Materiality Test (M2). Assets meeting both Materiality Tests comprise the water dependent asset list. Descriptions of the assets identified in the Gippsland bioregion are found in the "AssetList" table of the database. In this version of the database only M1 has been assessed.

    Assets are the spatial features used by project teams to model scenarios under the BA program. Detailed attribution does not exist at the asset level. Asset attribution includes only the core set of BA-derived attributes reflecting the BA classification hierarchy, as described in Appendix A of "AssetList_database_GIP_v1p2_20150130.doc", located in the zip file as part of this dataset.

    The "Element_to_Asset" table contains the relationships and identifies the elements that were grouped to create each asset.

    Detailed information describing the database structure and content can be found in the document "AssetList_database_GIP_v1p2_20150130.doc" located in the zip file.

    Some of the source data used in the compilation of this dataset is restricted.

    Purpose

    \[x\[\\\\\THIS IS NOT THE CURRENT ASSET LIST\\\\\

    This dataset was superseded by GIP AssetList Database v1.3 20150212

    GUID: e0a8bc96-e97b-44d4-858e-abbb06ddd87f

    on 12/2/2015

    THIS DATASET IS NOT TO BE PUBLISHED IN ITS CURRENT FORM\]x\]

    Dataset History

    This dataset is an update of the previous version of the Gippsland asset list database: "Gippsland Asset List V1 20141210"; ID: 112883f7-1440-4912-8fc3-1daf63e802cb, which was updated with the inclusion of a number of additional datasets from the Victorian Department of the Environment and Primary Industries as identified in the "linkages" section and below.

    Victorian Farm Dam Boundaries

    https://data.bioregionalassessments.gov.au/datastore/dataset/311a47f9-206d-4601-aa7d-6739cfc06d61

    Flood Extent 100 year extent West Gippsland Catchment Management Authority GIP v140701

    https://data.bioregionalassessments.gov.au/dataset/2ff06a4f-fdd5-4a34-b29a-a49416e94f15

    Irrigation District Department of Environment and Primary Industries GIP

    https://data.bioregionalassessments.gov.au/datastore/dataset/880d9042-abe7-4669-be3a-e0fbe096b66a

    Landscape priority areas (West)

    West Gippsland Regional Catchment Strategy Landscape Priorities WGCMA GIP 201205

    https://data.bioregionalassessments.gov.au/datastore/dataset/6c8c0a81-ba76-4a8a-b11a-1c943e744f00

    Plantation Forests Public Land Management(PLM25) DEPI GIP 201410

    https://data.bioregionalassessments.gov.au/datastore/dataset/495d0e4e-e8cd-4051-9623-98c03a4ecded

    and additional data identifying "Vulnerable" species from the datasets:

    Victorian Biodiversity Atlas flora - 1 minute grid summary

    https://data.bioregionalassessments.gov.au/datastore/dataset/d40ac83b-f260-4c0b-841d-b639534a7b63

    Victorian Biodiversity Atlas fauna - 1 minute grid summary

    https://data.bioregionalassessments.gov.au/datastore/dataset/516f9eb1-ea59-46f7-84b1-90a113d6633d

    A number of restricted datasets were used to compile this database. These are listed in the accompanying documentation and below:

    • The Collaborative Australian Protected Areas Database (CAPAD) 2010

    • Environmental Assets Database (Commonwealth Environmental Water Holder)

    • Key Environmental Assets of the Murray-Darling Basin

    • Communities of National Environmental Significance Database

    • Species of National Environmental Significance

    • Ramsar Wetlands of Australia 2011

    Dataset Citation

    Bioregional Assessment Programme (2015) GIP AssetList Database v1.2 20150130. Bioregional Assessment Derived Dataset. Viewed 07 February 2017, http://data.bioregionalassessments.gov.au/dataset/6f34129d-50a3-48f7-996c-7a6c9fa8a76a.

    Dataset Ancestors

  20. Callisto Crater Database - Dataset - NASA Open Data Portal

    • data.nasa.gov
    • data.staging.idas-ds1.appdat.jsc.nasa.gov
    Updated Mar 31, 2025
    + more versions
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    nasa.gov (2025). Callisto Crater Database - Dataset - NASA Open Data Portal [Dataset]. https://data.nasa.gov/dataset/callisto-crater-database
    Explore at:
    Dataset updated
    Mar 31, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    This web page leads to a database of images and information about the 150 major impact craters on Callisto and is updated semi-regularly based on continuing analysis of Voyager images.

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Social Security Administration (2025). Integrated Client Database [Dataset]. https://catalog.data.gov/dataset/integrated-client-database
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Integrated Client Database

Explore at:
79 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 4, 2025
Dataset provided by
Social Security Administrationhttp://ssa.gov/
Description

Database used to store client data both Identity and customer relationship management.

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