86 datasets found
  1. g

    BOGS Training Metrics | gimi9.com

    • gimi9.com
    Updated Nov 10, 2023
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    (2023). BOGS Training Metrics | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_bogs-training-metrics/
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    Dataset updated
    Nov 10, 2023
    Description

    Through the Department of the Interior-Bureau of Indian Affairs Enterprise License Agreement (DOI-BIA ELA) program, BIA employees and employees of federally-recognized Tribes may access a variety of geographic information systems (GIS) online courses and instructor-led training events throughout the year at no cost to them. These online GIS courses and instructor-led training events are hosted by the Branch of Geospatial Support (BOGS) or offered by BOGS in partnership with other organizations and federal agencies. Online courses are self-paced and available year-round, while instructor-led training events have limited capacity and require registration and attendance on specific dates. This dataset does not any training where the course was not completed by the participant or where training was cancelled or otherwise not able to be completed. Point locations depict BIA Office locations or Tribal Office Headquarters. For completed trainings where a participant location was not provided a point locations may not be available. For more information on the Branch of Geospatial Support Geospatial training program, please visit:https://www.bia.gov/service/geospatial-training.

  2. m

    Schools

    • gisopendata.marincounty.gov
    Updated Feb 28, 2023
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    Public ArcGIS Online (2023). Schools [Dataset]. https://gisopendata.marincounty.gov/datasets/marincounty::schools-2
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    Dataset updated
    Feb 28, 2023
    Dataset authored and provided by
    Public ArcGIS Online
    License

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

    Area covered
    Description

    Elementary, middle, high school and college sites in Marin County. Both public and private schools are included.Updated February 2020 using dataset supplied by Marin County Office of Education

  3. f

    Data from: Self-assessment in student’s learning and developing teaching in...

    • tandf.figshare.com
    txt
    Updated May 29, 2024
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    Nora Fagerholm; Eliisa Lotsari; Tua Nylén; Niina Käyhkö; Jussi Nikander; Vesa Arki; Risto Kalliola (2024). Self-assessment in student’s learning and developing teaching in geoinformatics – case of Geoportti self-assessment tool [Dataset]. http://doi.org/10.6084/m9.figshare.24099390.v1
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    txtAvailable download formats
    Dataset updated
    May 29, 2024
    Dataset provided by
    Taylor & Francis
    Authors
    Nora Fagerholm; Eliisa Lotsari; Tua Nylén; Niina Käyhkö; Jussi Nikander; Vesa Arki; Risto Kalliola
    License

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

    Description

    In successful geoinformatics education, students’ active role in the learning process, e.g. through applying self-assessment, show an increasing interest but the evidence of benefits and challenges of self-assessment are sporadic. In this article, we examine the usefulness of an online self-assessment tool developed for geoinformatics education. We gathered data in two Finnish universities on five courses (n = 11–73 students/course) between 2019 and 2021. We examined 1) how the students’ self-assessed knowledge and understanding in geoinformatics subject topics changed during a course, 2) how the competencies at the end of a course changed between the years in different courses, and 3) what was the perceived usefulness of the self-assessment approach among the students. The results indicate support for the implementation of self-assessment, both as a formative and summative assessment. However, it is crucial to ensure that the students understand the contents of the self-assessment subject topics. To increase students’ motivation to take a self-assessment, it is crucial that the teacher actively highlights how it supports their studying and learning. As the teachers of the examined courses, we discuss the benefits and challenges of the self-assessment approach and the applied tool for the future development of geoinformatics education.

  4. a

    Maryland Education Facilities - K thru 12 Education (Charter Schools)

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • data.imap.maryland.gov
    • +2more
    Updated Jan 1, 2015
    + more versions
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    ArcGIS Online for Maryland (2015). Maryland Education Facilities - K thru 12 Education (Charter Schools) [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/maryland::maryland-education-facilities-k-thru-12-education-charter-schools
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    Dataset updated
    Jan 1, 2015
    Dataset authored and provided by
    ArcGIS Online for Maryland
    Area covered
    Description

    Maryland's K thru 12 public charter schools offer more innovative programs and are held accountable for improved student achievement. Charter schools are publicly funded and accept applications for student enrollment. Maryland has a total of 48 charter schools located in 4 counties and the City of Baltimore.This is a MD iMAP hosted service layer. Find more information at https://imap.maryland.gov.Feature Service Layer Link:https://mdgeodata.md.gov/imap/rest/services/Education/MD_EducationFacilities/FeatureServer/6

  5. Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter...

    • catalog.data.gov
    • datasets.ai
    Updated Jun 5, 2024
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    National Park Service (2024). Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida (NPS, GRD, GRI, GUIS, GUIS_geomorphology digital map) adapted from U.S. Geological Survey Open File Report maps by Morton and Rogers (2009) and Morton and Montgomery (2010) [Dataset]. https://catalog.data.gov/dataset/digital-geomorphic-gis-map-of-gulf-islands-national-seashore-5-meter-accuracy-and-1-foot-r
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    United States, Guisguis Port Sariaya, Quezon
    Description

    The Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (guis_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (guis_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (guis_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (guis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (guis_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (guis_geomorphology_metadata_faq.pdf). Please read the guis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (guis_geomorphology_metadata.txt or guis_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:26,000 and United States National Map Accuracy Standards features are within (horizontally) 13.2 meters or 43.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

  6. Building a resource locator in ArcGIS Online (video)

    • coronavirus-disasterresponse.hub.arcgis.com
    • coronavirus-resources.esri.com
    Updated Mar 17, 2020
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    Esri’s Disaster Response Program (2020). Building a resource locator in ArcGIS Online (video) [Dataset]. https://coronavirus-disasterresponse.hub.arcgis.com/documents/34484698f776415cb4d4247eaf1d0c59
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    Dataset updated
    Mar 17, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri’s Disaster Response Program
    Description

    Building a resource locator in ArcGIS Online (video).View this short demonstration on how to build a simple resource locator in ArcGIS Online. In this demonstration the presenter publishes an existing Web Map to the Local Perspective configurable application template. The resulting application includes the ability to locate and navigate to different health resources that would be critical in managing a surge of displaced people related to a significant event impacting public health._Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...

  7. c

    Nonindigenous Aquatic Species (NAS) - USGS [ds731] GIS Dataset

    • map.dfg.ca.gov
    Updated Mar 15, 2022
    + more versions
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    (2022). Nonindigenous Aquatic Species (NAS) - USGS [ds731] GIS Dataset [Dataset]. https://map.dfg.ca.gov/metadata/ds0731.html
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    Dataset updated
    Mar 15, 2022
    Description

    CDFW BIOS GIS Dataset, Contact: Laura Ryley, Description: This GIS dataset offers a link to the California portion of the Nonindigenous Aquatic Species (NAS) information resource for the United States Geological Survey. The NAS program has been established as a central repository for accurate and spatially referenced biogeographic accounts of nonindigenous aquatic species. The program provides scientic reports, online/realtime queries, spatial data sets, regional contact lists, and general information

  8. d

    California State Waters Map Series--Offshore of Point Conception Web...

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). California State Waters Map Series--Offshore of Point Conception Web Services [Dataset]. https://catalog.data.gov/dataset/california-state-waters-map-series-offshore-of-point-conception-web-services
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Point Conception, California
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Point Conception map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Point Conception map area data layers. Data layers are symbolized as shown on the associated map sheets.

  9. Digital Geologic-GIS Map of San Miguel Island, California (NPS, GRD, GRI,...

    • catalog.data.gov
    Updated Jun 4, 2024
    + more versions
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    National Park Service (2024). Digital Geologic-GIS Map of San Miguel Island, California (NPS, GRD, GRI, CHIS, SMIS digital map) adapted from a American Association of Petroleum Geologists Field Trip Guidebook map by Weaver and Doerner (1969) [Dataset]. https://catalog.data.gov/dataset/digital-geologic-gis-map-of-san-miguel-island-california-nps-grd-gri-chis-smis-digital-map
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    Dataset updated
    Jun 4, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    San Miguel Island, California
    Description

    The Digital Geologic-GIS Map of San Miguel Island, California is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (smis_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (smis_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (smis_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) this file (chis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (chis_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (smis_geology_metadata_faq.pdf). Please read the chis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: American Association of Petroleum Geologists. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (smis_geology_metadata.txt or smis_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

  10. a

    Colleges and Universities

    • i-shore-idnr.hub.arcgis.com
    • disasters-geoplatform.hub.arcgis.com
    • +8more
    Updated Jun 30, 2022
    + more versions
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    GeoPlatform ArcGIS Online (2022). Colleges and Universities [Dataset]. https://i-shore-idnr.hub.arcgis.com/datasets/geoplatform::colleges-and-universities
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    Dataset updated
    Jun 30, 2022
    Dataset authored and provided by
    GeoPlatform ArcGIS Online
    License

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

    Area covered
    Description

    The Colleges and Universities feature class/shapefile is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, http://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2020-2021 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions. Overall, this data layer covers all 50 states, as well as Puerto Rico and other assorted U.S. territories. This feature class contains all MEDS/MEDS+ as approved by the National Geospatial-Intelligence Agency (NGA) Homeland Security Infrastructure Program (HSIP) Team. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the "Place Keyword" section of the metadata. This feature class does not have a relationship class but is related to Supplemental Colleges. Colleges and Universities that are not included in the NCES IPEDS data are added to the Supplemental Colleges feature class when found. This release includes the addition of 128 new records, the removal of 247 no longer reported by NCES, and modifications to the spatial location and/or attribution of 6312 records.

  11. O

    Schools Private

    • data.sccgov.org
    Updated May 2, 2023
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    (2023). Schools Private [Dataset]. https://data.sccgov.org/Education/Schools-Private/c6zz-mytg
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    csv, application/rssxml, tsv, kml, application/geo+json, xml, application/rdfxml, kmzAvailable download formats
    Dataset updated
    May 2, 2023
    Description

    Data derived from a database of private schools published online by a consortium of parents & other interested parties wanting to make information regarding private educational entities available to the public. THE GIS DATA IS PROVIDED "AS IS". THE COUNTY MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION, ANY IMPLIED WARRANTIES OR MERCHANTABILITY AND/OR FITNESS FOR A PARTICULAR PURPOSE, REGARDING THE ACCURACY, COMPLETENESS, VALUE, QUALITY, VALIDITY, MERCHANTABILITY, SUITABILITY, AND CONDITION, OF THE GIS DATA. USER'S OF COUNTY'S GIS DATA ARE HEREBY NOTIFIED THAT CURRENT PUBLIC PRIMARY INFORMATION SOURCES SHOULD BE CONSULTED FOR VERIFICATION OF THE DATA AND INFORMATION CONTAINED HEREIN. SINCE THE GIS DATA IS DYNAMIC, IT WILL BY ITS NATURE BE INCONSISTENT WITH THE OFFICIAL COUNTY DATA. ANY USE OF COUNTY'S GIS DATA WITHOUT CONSULTING OFFICIAL PUBLIC RECORDS FOR VERIFICATION IS DONE EXCLUSIVELY AT THE RISK OF THE PARTY MAKING SUCH USE.

  12. d

    Geologic Hazards Science Center GIS Server

    • search.dataone.org
    • datadiscoverystudio.org
    • +1more
    Updated Apr 13, 2017
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    U.S. Geological Survey, Geologic Hazards Science Center (2017). Geologic Hazards Science Center GIS Server [Dataset]. https://search.dataone.org/view/7c572de7-9cec-4e5d-a005-559ab55f6829
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    Dataset updated
    Apr 13, 2017
    Dataset provided by
    USGS Science Data Catalog
    Authors
    U.S. Geological Survey, Geologic Hazards Science Center
    Time period covered
    Jan 1, 2006
    Area covered
    Earth
    Description

    The USGS Geologic Hazards Science Center (GHSC) in Golden, CO maintains a GIS server with services pertaining to various geologic hazard disciplines involving earthquakes and landslides. The online link provides an overview of the structure of this server and also outlines the GIS data it contains. The folders named eq (earthquakes), haz (earthquake hazards), and ls (landlsides) contain services with data associated with each discipline.

  13. BOGS Training Metrics

    • opendata-1-bia-geospatial.hub.arcgis.com
    • s.cnmilf.com
    • +1more
    Updated Feb 19, 2025
    + more versions
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    Bureau of Indian Affairs (2025). BOGS Training Metrics [Dataset]. https://opendata-1-bia-geospatial.hub.arcgis.com/items/cb84475860084633b4f44f8ddcd0d78f
    Explore at:
    Dataset updated
    Feb 19, 2025
    Dataset authored and provided by
    Bureau of Indian Affairshttp://www.bia.gov/
    Area covered
    Description

    Through the Department of the Interior-Bureau of Indian Affairs Enterprise License Agreement (DOI-BIA ELA) program, BIA employees and employees of federally-recognized Tribes may access a variety of geographic information systems (GIS) online courses and instructor-led training events throughout the year at no cost to them. These online GIS courses and instructor-led training events are hosted by the Branch of Geospatial Support (BOGS) or offered by BOGS in partnership with other organizations and federal agencies. Online courses are self-paced and available year-round, while instructor-led training events have limited capacity and require registration and attendance on specific dates. This dataset does not any training where the course was not completed by the participant or where training was cancelled or otherwise not able to be completed. Point locations depict BIA Office locations or Tribal Office Headquarters. For completed trainings where a participant location was not provided a point locations may not be available. For more information on the Branch of Geospatial Support Geospatial training program, please visit:https://www.bia.gov/service/geospatial-training.

  14. D

    Education - Seattle Neighborhoods

    • data.seattle.gov
    • hub.arcgis.com
    • +2more
    application/rdfxml +5
    Updated Oct 22, 2024
    + more versions
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    (2024). Education - Seattle Neighborhoods [Dataset]. https://data.seattle.gov/dataset/Education-Seattle-Neighborhoods/vuww-ynb6
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    application/rdfxml, csv, tsv, application/rssxml, json, xmlAvailable download formats
    Dataset updated
    Oct 22, 2024
    Area covered
    Seattle
    Description

    Table from the American Community Survey (ACS) 5-year series on education enrollment and attainment related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B14007/B14002 School Enrollment, B15003 Educational Attainment. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.


    Table created for and used in the Neighborhood Profiles application.

    Vintages: 2023
    ACS Table(s): B14007, B15003, B14002


    The United States Census Bureau's American Community Survey (ACS):
    This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.

    Data Note from the Census:
    Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.

    Data Processing Notes:
    • Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb(year)a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).
    • The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico
    • Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).
    • Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications <a

  15. Nonindigenous Aquatic Species (NAS) - USGS [ds731]

    • data.cnra.ca.gov
    • data.ca.gov
    • +6more
    Updated Mar 15, 2022
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    California Department of Fish and Wildlife (2022). Nonindigenous Aquatic Species (NAS) - USGS [ds731] [Dataset]. https://data.cnra.ca.gov/dataset/nonindigenous-aquatic-species-nas-usgs-ds731
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    csv, arcgis geoservices rest api, geojson, zip, kml, htmlAvailable download formats
    Dataset updated
    Mar 15, 2022
    Dataset authored and provided by
    California Department of Fish and Wildlifehttps://wildlife.ca.gov/
    License

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

    Description

    This GIS dataset offers a link to the California portion of the Nonindigenous Aquatic Species (NAS) information resource for the United States Geological Survey. The NAS program has been established as a central repository for accurate and spatially referenced biogeographic accounts of nonindigenous aquatic species. The program provides scientic reports, online/realtime queries, spatial data sets, regional contact lists, and general information. The goal of the information system is to provide timely, reliable data about the presence and distribution of nonindigenous aquatic species. The NAS database contains locality information for more than 1100 species of vertebrates, invertebrates, and vascular plants. The NAS program provides a continual national repository of distribution information for nonindigenous aquatic species that is used to gain an understanding of aquatic introductions, identify geographic gaps, and access the status of introduced aquatic species nationwide. Data are obtained from many sources including literature, museums, databases, monitoring programs, state and federal agencies, professional communications, online reporting forms, and Aquatic Nuisance Species (ANS) hotline reports. The NAS program defines a nonindigenous aquatic species as a member(s) of a species that enters a body of water of aquatic ecosystem outside of its historic or native range. This includes not only species that arrived from outside of North America but also species native to North America that have been introduced to drainages outside their ranges within the country. Please visit http://nas.er.usgs.gov for more information and to see all of the products and data available through the NAS program.

  16. a

    Public Schools

    • hifld-geoplatform.hub.arcgis.com
    • data.amerigeoss.org
    • +7more
    Updated Mar 28, 2024
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    GeoPlatform ArcGIS Online (2024). Public Schools [Dataset]. https://hifld-geoplatform.hub.arcgis.com/datasets/geoplatform::public-schools/explore
    Explore at:
    Dataset updated
    Mar 28, 2024
    Dataset authored and provided by
    GeoPlatform ArcGIS Online
    License

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

    Area covered
    Description

    This Public Schools feature dataset is composed of all Public elementary and secondary education facilities in the United States as defined by the Common Core of Data (CCD, https://nces.ed.gov/ccd/), National Center for Education Statistics (NCES, https://nces.ed.gov), US Department of Education for the 2022-2023 school year. This includes all Kindergarten through 12th grade schools as tracked by the Common Core of Data. Included in this dataset are military schools in US territories and referenced in the city field with an APO or FPO address. DOD schools represented in the NCES data that are outside of the United States or US territories have been omitted. Complete field and attribute information is available in the "Entities and Attributes" metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the Place Keyword section of the metadata. This release includes the addition of 2,556 new records, modifications to the spatial location and/or attribution of 99,712 records.

  17. h

    Parcels - Hawaii Statewide

    • geoportal.hawaii.gov
    • opendata.hawaii.gov
    • +2more
    Updated Nov 9, 2015
    + more versions
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    Hawaii Statewide GIS Program (2015). Parcels - Hawaii Statewide [Dataset]. https://geoportal.hawaii.gov/datasets/parcels-hawaii-statewide
    Explore at:
    Dataset updated
    Nov 9, 2015
    Dataset authored and provided by
    Hawaii Statewide GIS Program
    Area covered
    Description

    [Metadata] Description: TMK Parcels for the State of Hawaii - 2024; specific dates vary by county.Sources: County of Hawaii: 5/2/24; County of Maui: 5/2/24; City and County of Honolulu: 5/2/24; County of Kauai: 5/15/24. Hawaii Statewide GIS Program projected to a common projection/datum (UTM Zone 4, NAD 83 HARN) and merged all counties parcel data into one layer. Where necessary, the State standardized field names or added fields to the county layers such as creating text fields for corresponding numeric tmk fields, etc., and / or calculated values for fields such as links to qpublic9.qpublic.net websites showing additional information for each parcel.The parcel boundaries are intended to provide a visual reference only and do not represent legal or survey level accuracy. Attributes are for assessment purposes only and are subject to change at any time. For more information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/tmk_state.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website:https://planning.hawaii.gov/gis.

  18. a

    Safety and Security

    • hub.arcgis.com
    Updated Dec 8, 2017
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    Westchester County GIS (2017). Safety and Security [Dataset]. https://hub.arcgis.com/items/a7d54b7db8314ce9bdc6287bcd08705d
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    Dataset updated
    Dec 8, 2017
    Dataset authored and provided by
    Westchester County GIS
    Description

    Safety and Security is part of the Livable Communities Initiative map series developed by Westchester County GIS for the Westchester County Department of Senior Program and Services.Map series consists of several ArcGIS online map applications to provide Westchester County seniors and their family’s access to information regarding health care, housing, food and nutrition programs, social and recreational, and transportation among others.

    For more information contact:Westchester County Department of Senior Program and Services.

  19. m

    Maryland Education Facilities - PreK thru 12 Education (Public Schools)

    • data.imap.maryland.gov
    Updated Aug 21, 2018
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    ArcGIS Online for Maryland (2018). Maryland Education Facilities - PreK thru 12 Education (Public Schools) [Dataset]. https://data.imap.maryland.gov/datasets/f49c4bb1a9a74029ae974e6d6fd08b71
    Explore at:
    Dataset updated
    Aug 21, 2018
    Dataset authored and provided by
    ArcGIS Online for Maryland
    Area covered
    Description

    Maryland's PreK - 12 public school system ranks first overall based on the latest data in six graded categories. Maryland ranks second in the achievement category and third in teaching as well as transitions and alignment. This is a MD iMAP hosted service. Find more information on https://imap.maryland.gov.Feature Service Link: https://mdgeodata.md.gov/imap/rest/services/Education/MD_EducationFacilities/FeatureServer/5

  20. Geographical tracking and mapping of COVID-19 (IJHG)

    • coronavirus-resources.esri.com
    Updated Mar 23, 2020
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    Esri’s Disaster Response Program (2020). Geographical tracking and mapping of COVID-19 (IJHG) [Dataset]. https://coronavirus-resources.esri.com/documents/disasterresponse::geographical-tracking-and-mapping-of-covid-19-ijhg/about?path=
    Explore at:
    Dataset updated
    Mar 23, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri’s Disaster Response Program
    Description

    Geographical tracking and mapping of COVID-19 (International Journal of Health Geographics).In 2019, a new virus causing severe acute respiratory syndrome emerged in Wuhan, Hubei Province, China. This paper offers pointers to, and describes, a range of practical online/mobile GIS and mapping dashboards and applications for tracking the coronavirus epidemic and associated events as they unfold around the world.Citation:Kamel Boulos, M.N., Geraghty, E.M. Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbreaks and epidemics. Int J Health Geogr 19, 8 (2020). https://doi.org/10.1186/s12942-020-00202-8_Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...

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(2023). BOGS Training Metrics | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_bogs-training-metrics/

BOGS Training Metrics | gimi9.com

Explore at:
Dataset updated
Nov 10, 2023
Description

Through the Department of the Interior-Bureau of Indian Affairs Enterprise License Agreement (DOI-BIA ELA) program, BIA employees and employees of federally-recognized Tribes may access a variety of geographic information systems (GIS) online courses and instructor-led training events throughout the year at no cost to them. These online GIS courses and instructor-led training events are hosted by the Branch of Geospatial Support (BOGS) or offered by BOGS in partnership with other organizations and federal agencies. Online courses are self-paced and available year-round, while instructor-led training events have limited capacity and require registration and attendance on specific dates. This dataset does not any training where the course was not completed by the participant or where training was cancelled or otherwise not able to be completed. Point locations depict BIA Office locations or Tribal Office Headquarters. For completed trainings where a participant location was not provided a point locations may not be available. For more information on the Branch of Geospatial Support Geospatial training program, please visit:https://www.bia.gov/service/geospatial-training.

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