11 datasets found
  1. c

    California Public Schools and Districts Map

    • gis.data.ca.gov
    • data.ca.gov
    • +2more
    Updated Oct 24, 2018
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    California Department of Education (2018). California Public Schools and Districts Map [Dataset]. https://gis.data.ca.gov/maps/169b581b560d4150b03ce84502fa5c72
    Explore at:
    Dataset updated
    Oct 24, 2018
    Dataset authored and provided by
    California Department of Education
    License

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

    Area covered
    Description

    This web map displays the California Department of Education's (CDE) core set of geographic data layers. This content represents the authoritative source for all statewide public school site locations and school district service areas boundaries for the 2018-19 academic year. The map also includes school and district layers enriched with student demographic and performance information from the California Department of Education's data collections. These data elements add meaningful statistical and descriptive information that can be visualized and analyzed on a map and used to advance education research or inform decision making.

  2. K

    Ohio School Districts

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Sep 13, 2018
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    State of Ohio (2018). Ohio School Districts [Dataset]. https://koordinates.com/layer/97252-ohio-school-districts/
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    csv, dwg, mapinfo tab, kml, geopackage / sqlite, geodatabase, pdf, mapinfo mif, shapefileAvailable download formats
    Dataset updated
    Sep 13, 2018
    Dataset authored and provided by
    State of Ohio
    Area covered
    Description

    This layer is sourced from gis.dot.state.oh.us.

    © ODOT

  3. d

    Data from: School Finder

    • catalog.data.gov
    • data.wu.ac.at
    Updated Mar 31, 2025
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    School District of Philadelphia (2025). School Finder [Dataset]. https://catalog.data.gov/dataset/school-finder
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    Dataset updated
    Mar 31, 2025
    Dataset provided by
    School District of Philadelphia
    Description

    Enter an address to see which school catchment area that address is located in. The application can also use the location of the user, retrieved from the user's browser, rather than an address. The map is powered by Google Maps.

  4. School Learning Modalities, 2020-2021

    • healthdata.gov
    • data.virginia.gov
    • +3more
    application/rdfxml +5
    Updated Nov 1, 2022
    + more versions
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    Centers for Disease Control and Prevention (2022). School Learning Modalities, 2020-2021 [Dataset]. https://healthdata.gov/National/School-Learning-Modalities-2020-2021/a8v3-a3m3
    Explore at:
    application/rdfxml, tsv, csv, xml, json, application/rssxmlAvailable download formats
    Dataset updated
    Nov 1, 2022
    Dataset authored and provided by
    Centers for Disease Control and Prevention
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    The 2020-2021 School Learning Modalities dataset provides weekly estimates of school learning modality (including in-person, remote, or hybrid learning) for U.S. K-12 public and independent charter school districts for the 2020-2021 school year, from August 2020 – June 2021.

    These data were modeled using multiple sources of input data (see below) to infer the most likely learning modality of a school district for a given week. These data should be considered district-level estimates and may not always reflect true learning modality, particularly for districts in which data are unavailable. If a district reports multiple modality types within the same week, the modality offered for the majority of those days is reflected in the weekly estimate. All school district metadata are sourced from the https://nces.ed.gov/ccd/files.asp#Fiscal:2,LevelId:5,SchoolYearId:35,Page:1">National Center for Educational Statistics (NCES) for 2020-2021.

    School learning modality types are defined as follows:

      • In-Person: All schools within the district offer face-to-face instruction 5 days per week to all students at all available grade levels.
      • Remote: Schools within the district do not offer face-to-face instruction; all learning is conducted online/remotely to all students at all available grade levels.
      • Hybrid: Schools within the district offer a combination of in-person and remote learning; face-to-face instruction is offered less than 5 days per week, or only to a subset of students.

    Data Information

      • School learning modality data provided here are model estimates using combined input data and are not guaranteed to be 100% accurate. This learning modality dataset was generated by combining data from four different sources: Burbio [1], MCH Strategic Data [2], the AEI/Return to Learn Tracker [3], and state dashboards [4-20]. These data were combined using a Hidden Markov model which infers the sequence of learning modalities (In-Person, Hybrid, or Remote) for each district that is most likely to produce the modalities reported by these sources. This model was trained using data from the 2020-2021 school year. Metadata describing the location, number of schools and number of students in each district comes from NCES [21].
      • You can read more about the model in the CDC MMWR: https://www.cdc.gov/mmwr/volumes/70/wr/mm7039e2.htm" target="_blank">COVID-19–Related School Closures and Learning Modality Changes — United States, August 1–September 17, 2021.
      • The metrics listed for each school learning modality reflect totals by district and the number of enrolled students per district for which data are available. School districts represented here exclude private schools and include the following NCES subtypes:
        • Public school district that is NOT a component of a supervisory union
        • Public school district that is a component of a supervisory union
        • Independent charter district
      • “BI” in the state column refers to school districts funded by the Bureau of Indian Education.

    Technical Notes

      • Data from September 1, 2020 to June 25, 2021 correspond to the 2020-2021 school year. During this timeframe, all four sources of data were available. Inferred modalities with a probability below 0.75 were deemed inconclusive and were omitted.
      • Data for the month of July may show “In Person” status although most school districts are effectively closed during this time for summer break. Users may wish to exclude July data from use for this reason where applicable.

    Sources

  5. School Learning Modalities, 2021-2022

    • datahub.hhs.gov
    • data.virginia.gov
    • +3more
    application/rdfxml +5
    Updated Jun 23, 2022
    + more versions
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    Centers for Disease Control and Prevention (2022). School Learning Modalities, 2021-2022 [Dataset]. https://datahub.hhs.gov/National/School-Learning-Modalities-2021-2022/aitj-yx37
    Explore at:
    json, application/rdfxml, tsv, csv, xml, application/rssxmlAvailable download formats
    Dataset updated
    Jun 23, 2022
    Dataset authored and provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    The 2021-2022 School Learning Modalities dataset provides weekly estimates of school learning modality (including in-person, remote, or hybrid learning) for U.S. K-12 public and independent charter school districts for the 2021-2022 school year and the Fall 2022 semester, from August 2021 – December 2022.

    These data were modeled using multiple sources of input data (see below) to infer the most likely learning modality of a school district for a given week. These data should be considered district-level estimates and may not always reflect true learning modality, particularly for districts in which data are unavailable. If a district reports multiple modality types within the same week, the modality offered for the majority of those days is reflected in the weekly estimate. All school district metadata are sourced from the https://nces.ed.gov/ccd/files.asp#Fiscal:2,LevelId:5,SchoolYearId:35,Page:1">National Center for Educational Statistics (NCES) for 2020-2021.

    School learning modality types are defined as follows:

      • In-Person: All schools within the district offer face-to-face instruction 5 days per week to all students at all available grade levels.
      • Remote: Schools within the district do not offer face-to-face instruction; all learning is conducted online/remotely to all students at all available grade levels.
      • Hybrid: Schools within the district offer a combination of in-person and remote learning; face-to-face instruction is offered less than 5 days per week, or only to a subset of students.
    Data Information
      • School learning modality data provided here are model estimates using combined input data and are not guaranteed to be 100% accurate. This learning modality dataset was generated by combining data from four different sources: Burbio [1], MCH Strategic Data [2], the AEI/Return to Learn Tracker [3], and state dashboards [4-20]. These data were combined using a Hidden Markov model which infers the sequence of learning modalities (In-Person, Hybrid, or Remote) for each district that is most likely to produce the modalities reported by these sources. This model was trained using data from the 2020-2021 school year. Metadata describing the location, number of schools and number of students in each district comes from NCES [21].
      • You can read more about the model in the CDC MMWR: https://www.cdc.gov/mmwr/volumes/70/wr/mm7039e2.htm" target="_blank">COVID-19–Related School Closures and Learning Modality Changes — United States, August 1–September 17, 2021.
      • The metrics listed for each school learning modality reflect totals by district and the number of enrolled students per district for which data are available. School districts represented here exclude private schools and include the following NCES subtypes:
        • Public school district that is NOT a component of a supervisory union
        • Public school district that is a component of a supervisory union
        • Independent charter district
      • “BI” in the state column refers to school districts funded by the Bureau of Indian Education.
    Technical Notes
      • Data from August 1, 2021 to June 24, 2022 correspond to the 2021-2022 school year. During this time frame, data from the AEI/Return to Learn Tracker and most state dashboards were not available. Inferred modalities with a probability below 0.6 were deemed inconclusive and were omitted. During the Fall 2022 semester, modalities for districts with a school closure reported by Burbio were updated to either “Remote”, if the closure spanned the entire week, or “Hybrid”, if the closure spanned 1-4 days of the week.
      • Data from August 1, 2022 to December 31, 2022 correspond to the 2022-2023 school year and were processed in a similar manner to data from the 2021-2022 school year.
      • Data for the month of July may show “In Person” status although most school districts are effectively closed during this time for summer break. Users may wish to exclude July data from use for this reason where applicable.
    Sources

  6. M

    Historical Public School District Center Locations, Minnesota, School Years...

    • gisdata.mn.gov
    fgdb, gpkg, html +2
    Updated Dec 12, 2024
    + more versions
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    Education Department (2024). Historical Public School District Center Locations, Minnesota, School Years 2006-07 - 2008-09 [Dataset]. https://gisdata.mn.gov/dataset/struc-schooldistrictctr-2000s
    Explore at:
    gpkg, jpeg, fgdb, html, shpAvailable download formats
    Dataset updated
    Dec 12, 2024
    Dataset provided by
    Education Department
    Area covered
    Minnesota
    Description

    This historical archive is a geodatabase that contains annual files for public school district center locations in the state of Minnesota for school years 2006-07 through 2008-09. The point locations of school district service offices were developed at MDE to complement other school locational information. Many school district offices, or service centers, are located in a current elementary, middle or high school building. Some have their own facility. All locations have been developed and compared to existing school locations or address matched using The Lawrence Group street centerline address files. Unmatched locations were matched through school district websites or Google maps. Some locations may be incorrect as a full QA/QC process has not been completed.
    This metadata summarizes the content of these files but individual metadata records are also included for each annual file.

  7. w

    Minnesota Public School District Center Locations, SY2007-2008

    • data.wu.ac.at
    bin
    Updated Apr 9, 2015
    + more versions
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    State of Minnesota (2015). Minnesota Public School District Center Locations, SY2007-2008 [Dataset]. https://data.wu.ac.at/schema/data_gov/MGE5ZGFmZWUtZDI2Zi00NmY5LWFlNDEtNDgyMGU1YzFjNTE1
    Explore at:
    binAvailable download formats
    Dataset updated
    Apr 9, 2015
    Dataset provided by
    State of Minnesota
    Area covered
    f38c521b3788518db45c209d2583b6af555b9a98
    Description

    The point locations of school district service offices were developed at MDE to complement other school locational information. Many school district offices, or service centers, are located in a current elementary, middle or high school building. Some have their own facility. All locations have been developed and compared to existing school locations or address matched using The Lawrence Group street centerline address files. Unmatched locations were matched through school district websites or Google maps. Some locations may be incorrect as a full QA/QC process has not been completed.

  8. w

    Public School District Center Locations, Minnesota, SY2006/07 - 2008/09

    • data.wu.ac.at
    • gisdata.mn.gov
    fgdb, gpkg, html +2
    Updated Mar 2, 2017
    + more versions
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    Education Department (2017). Public School District Center Locations, Minnesota, SY2006/07 - 2008/09 [Dataset]. https://data.wu.ac.at/odso/gisdata_mn_gov/ODVmMWQ1MGUtNTA4Mi00MmM5LWIwN2EtNTQyNzU0NjUzMmVj
    Explore at:
    shp, gpkg, jpeg, html, fgdbAvailable download formats
    Dataset updated
    Mar 2, 2017
    Dataset provided by
    Education Department
    Area covered
    f058d1974b1795ee215253b9fea84e0df4f163c1
    Description

    This file is a geodatabase that contains annual files for public school district center locations in the state of Minnesota for school years 2006/07-2008/09. The point locations of school district service offices were developed at MDE to complement other school locational information. Many school district offices, or service centers, are located in a current elementary, middle or high school building. Some have their own facility. All locations have been developed and compared to existing school locations or address matched using The Lawrence Group street centerline address files. Unmatched locations were matched through school district websites or Google maps. Some locations may be incorrect as a full QA/QC process has not been completed.
    This metadata summarizes the content of these files but individual metadata records are also included for each annual file.

  9. a

    GeoWeb Parcel Map Viewer

    • hub.arcgis.com
    Updated Aug 16, 2016
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    City of West Allis, WI (2016). GeoWeb Parcel Map Viewer [Dataset]. https://hub.arcgis.com/items/0d49b52012f74acda4a73037cc80a087
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    Dataset updated
    Aug 16, 2016
    Dataset authored and provided by
    City of West Allis, WI
    Area covered
    Description

    West Allis Parcel Web Viewer is a GIS Web application that helps citizens identify their parcel and obtain information about it as well as information about their surrounding Neighborhood. This application is typically used by citizens to see their parcel assessed valuation, and compare it to other parcels in their neighborhood, but it can be used for many other uses as well. You can also see the Schools in West Allis, both public and private, as well as the West Allis West Milwaukee Public School District boundaries. Additionally, you can view zip code areas, Neighborhood District boundaries, Assessment boundaries for Residential and Commercial neighborhoods, Census 2010 Tracts, Block Groups, and Blocks, Zoning Districts, TIF and BID Districts, Existing Land Use, Land Use 2010, and Comp Plan 2030 Land Use. There is also an Intersection Bing Google feature that when turned on and clicked, will link you directly to either a Bing Map or Google Map of the area providing additional aerial photos. The Viewer will extend out to the limits of Milwaukee County, and show you Municipal Divisions in Waukesha County as well. Ortho Photo coverage for all of Milwaukee County is using the latest 2015 and 2018 imagery. West Allis Parcel Viewer Map can be used by anyone who needs to check out a parcel of land within West Allis, WI. This application provides 24/7 access to the parcel information and typically supplements customer service phone calls to City Staff with questions concerning a particular parcel

  10. d

    Replication Data for: Haemoglobin concentration data on School-aged children...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 8, 2023
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    Robert, Bibian N.; Cherono, Anitah; Mumo, Eda; Mwandawiro, Charles; Okoyo, Collins; Gichuki, Paul M.; Blanford, Justine l.; Snow, Robert W.; Okiro, Emelda A. (2023). Replication Data for: Haemoglobin concentration data on School-aged children (5-14yrs) across Public Primary Schools in Western Kenya [Dataset]. http://doi.org/10.7910/DVN/6GRZZM
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Robert, Bibian N.; Cherono, Anitah; Mumo, Eda; Mwandawiro, Charles; Okoyo, Collins; Gichuki, Paul M.; Blanford, Justine l.; Snow, Robert W.; Okiro, Emelda A.
    Description

    This is a replication dataset for the manuscript titled: "Haemoglobin concentration data on School-aged children (5-14yrs) across Public Primary Schools in Western Kenya." A survey of children attending 82 public primary schools in eight counties (Bungoma, Busia, Kakamega, Kisumu, Homa Bay, Migori, Siaya, Vihiga) across Western Kenya was conducted in February 2022. All eight counties and the respective 62 sub-counties had at least one school surveyed. At each school, approximately 100 children aged 5–14 years were randomly sampled from Classes 2 to 6. Selected children were asked to provide a finger-prick blood sample,which was used to assess their haemoglobin concentration using a portable photometer (HemoCue AB, Ängelholm, Sweden). The location of each sampled school was recorded using a hand-held Global Positioning System (GPS). The children provided information on their village of residence with the help of their teachers. Village coordinates were geolocated using Google Earth/Maps and digital place-name gazetteers, including Geonames, Encarta, and OpenStreetMap. The village locations were validated in ArcMap version 10.5 (ESRI Inc., Redlands, CA, USA) using the approximate travel time to schools reported by the children.

  11. CDPHE CDOE School Locations and District Office Locations

    • geodata.colorado.gov
    • data.colorado.gov
    • +3more
    Updated Mar 21, 2017
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    Colorado Department of Public Health and Environment (2017). CDPHE CDOE School Locations and District Office Locations [Dataset]. https://geodata.colorado.gov/maps/CDPHE::cdphe-cdoe-school-locations-and-district-office-locations/about
    Explore at:
    Dataset updated
    Mar 21, 2017
    Dataset authored and provided by
    Colorado Department of Public Health and Environmenthttps://cdphe.colorado.gov/
    Area covered
    Description

    Point geometry feature class representing Colorado public school and private school locations along with the locations of school district offices, developed directly from address information obtained from the Colorado Department of Education in 2022. Coordinate locations (latitude/longitude) were derived from the known street addresses of health facilities using a combination of Centrus MapMarker geocoding software and Google Earth imagery locations. This file was developed by the Colorado Department of Public Health and Environment for use in program activities and emergency preparedness exercises.

  12. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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California Department of Education (2018). California Public Schools and Districts Map [Dataset]. https://gis.data.ca.gov/maps/169b581b560d4150b03ce84502fa5c72

California Public Schools and Districts Map

Explore at:
Dataset updated
Oct 24, 2018
Dataset authored and provided by
California Department of Education
License

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

Area covered
Description

This web map displays the California Department of Education's (CDE) core set of geographic data layers. This content represents the authoritative source for all statewide public school site locations and school district service areas boundaries for the 2018-19 academic year. The map also includes school and district layers enriched with student demographic and performance information from the California Department of Education's data collections. These data elements add meaningful statistical and descriptive information that can be visualized and analyzed on a map and used to advance education research or inform decision making.

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