82 datasets found
  1. a

    High School Graduate Count

    • hub.arcgis.com
    • gis.data.alaska.gov
    • +5more
    Updated Sep 5, 2019
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    Dept. of Commerce, Community, & Economic Development (2019). High School Graduate Count [Dataset]. https://hub.arcgis.com/maps/DCCED::high-school-graduate-count
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    Dataset updated
    Sep 5, 2019
    Dataset authored and provided by
    Dept. of Commerce, Community, & Economic Development
    Area covered
    Description

    Count of high school graduates for each public school in Alaska. Data covers the School Year 2013 to the present. Each year's count includes students graduating at any point during the school year (July 1 to June 30).Source: Alaska Department of Education & Early Development

    This data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: Alaska Department of Education & Early Development Data Center.

  2. a

    High School Graduation Rates

    • hub.arcgis.com
    Updated Oct 20, 2016
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    Civic Analytics Network (2016). High School Graduation Rates [Dataset]. https://hub.arcgis.com/maps/2929a52f7868499492ad7ec716bf6545
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    Dataset updated
    Oct 20, 2016
    Dataset authored and provided by
    Civic Analytics Network
    Area covered
    Description

    This map shows the 4-year high school graduation rate in 2005-6 compared to the target rate. The map switches from state, to county data as the map zooms in. High school graduation is the leading health indicator for Social Determinants. A range of personal, social, economic, and environmental factors contribute to individual and population health. For example, people with a quality education, stable employment, safe homes and neighborhoods, and access to preventive services tend to be healthier throughout their lives. Conversely, poor health outcomes are often made worse by the interaction between individuals and their social and physical environment. Social determinants are in part responsible for the unequal and avoidable differences in health status within and between communities. The selection of Social Determinants as a Leading Health Topic recognizes the critical role of home, school, workplace, neighborhood, and community in improving health. For a complete list of indicators, please visit http://www.healthypeople.gov/2020/LHI/default.aspx. Note that many of the indicators on the Healthy Living list are not broken out below the national level; substitutions were made based on data in the Health Indicator warehouse (http://www.healthindicators.gov).

  3. a

    More Than Just Fake News

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Jul 29, 2020
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    University of Minnesota (2020). More Than Just Fake News [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/documents/8086f0ae257d41098d08733ae4a66083
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    Dataset updated
    Jul 29, 2020
    Dataset authored and provided by
    University of Minnesota
    Description

    “More Than Just Fake News: Propaganda in Political Campaign Advertising” is a static map created by Cecelia Isaac (Master of Geographic Information Sciences). It was awarded a U-Spatial Mapping Prize for most provocative/transformative Graduate map.

  4. Number of Graduates (Headcount) of UGC funded Programmes in Hong Kong

    • opendata.esrichina.hk
    • data-esrihk.opendata.arcgis.com
    Updated Feb 9, 2024
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    Esri China (Hong Kong) Ltd. (2024). Number of Graduates (Headcount) of UGC funded Programmes in Hong Kong [Dataset]. https://opendata.esrichina.hk/maps/70f34725859842e89b268ca7e08d233c
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    Dataset updated
    Feb 9, 2024
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri China (Hong Kong) Ltd.
    Area covered
    Description

    This web map shows the Number of Graduates (Headcount) of UGC-funded Programmes by University, Level of Study, Mode of Study and Academic Programme Category. It is a set of the data made available by the University Grants Committee Secretariat under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of Hong Kong CSDI Portal at https://portal.csdi.gov.hk.

  5. d

    GraduationRates byTract 08312017

    • catalog.data.gov
    • detroitdata.org
    • +6more
    Updated Sep 21, 2024
    + more versions
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    Data Driven Detroit (2024). GraduationRates byTract 08312017 [Dataset]. https://catalog.data.gov/dataset/graduationrates-bytract-08312017-3e507
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    Dataset updated
    Sep 21, 2024
    Dataset provided by
    Data Driven Detroit
    Description

    High School graduation rates for the 2015-2016 school year by census tract for the state of Michigan. Data Driven Detroit obtained these datasets from MI School Data, for the State of the Detroit Child tool in July 2017. Graduation rates were originally obtained on a school level and aggregated to tract by Data Driven Detroit. The graduation rates were calculated by Data Driven Detroit, using the count of students per cohort per school divided by the count of students who graduated.Click here for metadata (descriptions of the fields).

  6. f

    Data from: System to outline the graduatestudents

    • scielo.figshare.com
    jpeg
    Updated Jun 5, 2023
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    Alberto Schanaider (2023). System to outline the graduatestudents [Dataset]. http://doi.org/10.6084/m9.figshare.14316961.v1
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    jpegAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    SciELO journals
    Authors
    Alberto Schanaider
    License

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

    Description

    Objective: to evaluate the system to outline the graduate students from the Post-Graduate Programs of CAPES Medicine III area. Method: it was analyzed the book of indicators and the Document of Area of the Post-Graduate Programs of Surgery, also checking the literature about this issue. Results: there was a paucity of data from most of the programs, as regards to the methods for evaluation of graduate students. The current system lacks a standard and an institutional support to outline the graduate students. In the public system there is a concentration of postgraduate students in Medicine; however, they represent a small part of those Brazilians students who finished their graduation courses in Medicine. In the current context, the quest for the post graduate courses and consequently for a research field or even a teaching career, has been replaced by the private sector jobs and the labor market, both in non-academic assistance activities. Conclusion: it is imperative to establish not only science and technology innovation policies but also educational and health policies acting harmoniously and stimulating the qualification and the teaching career, improving the post-graduate courses. It is necessary to develop a single form under the institutional guidance of CAPES with the conception of a National Program for Graduate Student in order to consolidate guidelines to mapping the graduate students of post-graduate programs in surgery, in our country.

  7. d

    GraduationRates 2016 2017 byTract 20181019

    • catalog.data.gov
    • detroitdata.org
    • +7more
    Updated Sep 21, 2024
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    Data Driven Detroit (2024). GraduationRates 2016 2017 byTract 20181019 [Dataset]. https://catalog.data.gov/dataset/graduationrates-2016-2017-bytract-20181019-0bb64
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    Dataset updated
    Sep 21, 2024
    Dataset provided by
    Data Driven Detroit
    Description

    High School graduation rates for the 2016-2017 school year by census tract for the state of Michigan. Data Driven Detroit obtained these datasets from MI School Data, for the State of the Detroit Child tool in October 2018. Graduation rates were originally obtained on a school level and aggregated to tract by Data Driven Detroit. The graduation rates were calculated by Data Driven Detroit, using the count of students per cohort per school divided by the count of students who graduated.Click here for metadata (descriptions of the fields).

  8. KU Students Wrap Up Course in Aerial Mapping Using Drones - Datasets -...

    • ckan.americaview.org
    Updated Sep 16, 2021
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    ckan.americaview.org (2021). KU Students Wrap Up Course in Aerial Mapping Using Drones - Datasets - AmericaView - CKAN [Dataset]. https://ckan.americaview.org/dataset/ku-students-wrap-up-course-in-aerial-mapping-using-drones
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    Dataset updated
    Sep 16, 2021
    Dataset provided by
    CKANhttps://ckan.org/
    License

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

    Description

    LAWRENCE — Fall break is barely behind us, but a group of University of Kansas students has just finished an innovative eight-week course in using drones to develop aerial maps. Over the past two months, they’ve visited sites in KU's West District and at the Baker Wetlands, taking still images and videos over those areas. “The drone mapping course has been excellent in providing a hands-on experience with the drones,” said Siddharth Shankar, graduate student from Lucknow, India. “The course has focused not just on drones and how to fly them but also has made us aware of the FAA rules and regulations about drone flying and safety precautions. “My research has been in glaciology, with the study of icebergs in Greenland. The drone mapping course has provided new insights into incorporating it with my research in the near future.” The course, offered annually during the fall semester, is designed to teach students about the rapidly growing technology of small unmanned aerial systems, referred to as drones, and its wide-ranging applications — which include search-and-rescue, real estate and environmental monitoring. Students in the course come from a variety of disciplines including geography & atmospheric science, geology, ecology & evolutionary biology and civil engineering. Enthusiasm for the course has been very high, and it has filled rapidly each time it has been offered.

  9. p

    Trends in Graduation Rate (2019-2022): Map Academy Charter School School...

    • publicschoolreview.com
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    Public School Review, Trends in Graduation Rate (2019-2022): Map Academy Charter School School District vs. Massachusetts [Dataset]. https://www.publicschoolreview.com/massachusetts/map-academy-charter-school-school-district/2500589-school-district
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    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    Massachusetts
    Description

    This dataset tracks annual graduation rate from 2019 to 2022 for Map Academy Charter School School District vs. Massachusetts

  10. a

    School District Graduation Rate: Four-Year

    • dcra-program-summaries-dcced.hub.arcgis.com
    • gis.data.alaska.gov
    • +4more
    Updated Nov 22, 2022
    + more versions
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    Dept. of Commerce, Community, & Economic Development (2022). School District Graduation Rate: Four-Year [Dataset]. https://dcra-program-summaries-dcced.hub.arcgis.com/datasets/school-district-graduation-rate-four-year
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    Dataset updated
    Nov 22, 2022
    Dataset authored and provided by
    Dept. of Commerce, Community, & Economic Development
    Area covered
    Description

    High school 4-year graduation rates data for Alaskan school districts. Includes multi-year data for borough, REAA, and city school districts in AK.Source: Alaska Department of Education & Early DevelopmentThis data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: Alaska Department of Education & Early Development Data Center.

  11. G

    Non-medical Determinants of Health - High School Graduates, 1996

    • open.canada.ca
    • data.wu.ac.at
    jp2, zip
    Updated Mar 14, 2022
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    Natural Resources Canada (2022). Non-medical Determinants of Health - High School Graduates, 1996 [Dataset]. https://open.canada.ca/data/dataset/f184148f-8893-11e0-9858-6cf049291510
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    zip, jp2Available download formats
    Dataset updated
    Mar 14, 2022
    Dataset provided by
    Natural Resources Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    There is a tendency for life expectancy to be higher in those regions where high school attainment has been graduation by most individuals in this age grouping (25 to 29 years). Canada has an excellent record in providing its citizens with an education, and consequently a potential for better health. The highest proportions of Canadians with chronic conditions occur in the low educational attainment category. However, this pattern is not consistent throughout Canada where, in Saskatchewan for example, some provinces the reverse pattern is observed. In such locations, other determinants of health may mitigate the positive contributions associated with higher education. Education is one of the non-medical determinants of health. More people of lower educational attainment rated their own health as poor.

  12. e

    Map Viewing Service (WMS) of the dataset: West Sigap PPRT hazard zone in...

    • data.europa.eu
    unknown
    Updated Jan 19, 2022
    + more versions
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    (2022). Map Viewing Service (WMS) of the dataset: West Sigap PPRT hazard zone in Deux-Sèvres [Dataset]. https://data.europa.eu/data/datasets/fr-120066022-srv-ca855384-eae9-4f0b-97b0-415c874e4451
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    unknownAvailable download formats
    Dataset updated
    Jan 19, 2022
    Description

    Area exposed to one or more hazards represented on the hazard map used for risk analysis of the RPP. The hazard map is the result of the study of hazards, the objective of which is to assess the intensity of each hazard at any point in the study area. The evaluation method is specific to each hazard type. It leads to the delimitation of a set of areas on the study perimeter constituting a zoning graduated according to the level of the hazard. The assignment of a hazard level at a given point in the territory takes into account the probability of occurrence of the dangerous phenomenon and its degree of intensity.For PPRTs the hazard levels are determined by effect effect on maps by type of effect and overall on an aggregated level on a synthesis map.All hazard areas represented on the hazard map are included. Areas protected by protective structures must be represented (possibly in a specific way) as they are always considered to be subject to hazard (cases of breakage or inadequacy of the structure).The hazard zones may be classified as data compiled in so far as they result from a synthesis using several sources of calculated, modelled or observed hazard data. These source data are not covered by this class of objects but by another standard dealing with the knowledge of hazards.Some areas of the study perimeter are considered “zero or insignificant hazard zones”. These are the areas where the hazard has been studied and is nil. These areas are not included in the object class and do not have to be represented as hazard zones.

  13. e

    Map visualisation service (WMS) of the dataset: Alea area of PPRT Titanobel

    • data.europa.eu
    Updated Nov 25, 2022
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    (2022). Map visualisation service (WMS) of the dataset: Alea area of PPRT Titanobel [Dataset]. https://data.europa.eu/data/datasets/fr-120066022-srv-260ed15c-312a-4022-9447-2f65639b8d6b/embed
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    Dataset updated
    Nov 25, 2022
    Description

    Area exposed to one or more hazards shown on the hazard map used for the RPP risk analysis. The hazard map is the result of the study of hazards whose objective is to assess the intensity of each hazard at any point in the study area. The assessment method is specific to each type of hazard. It leads to the delimitation of a set of zones on the study perimeter constituting a graduated zoning according to the level of the hazard. The assignment of a hazard level at a given point in the territory takes into account the probability of occurrence of the dangerous phenomenon and its degree of intensity. For PPRTs hazard levels are determined effect by effect on maps by type of effects and overall according to an aggregate level on a synthesis map.

    All hazard areas shown on the hazard map are included. Areas protected by protective works must be represented (possibly in a specific way) because they are always considered subject to hazard (case of rupture or insufficiency of the structure). Hazard zones can be described as elaborated data to the extent that they result from a synthesis using several calculated, modelled or observed hazard data sources. These source data are not concerned by this class of objects but by another standard dealing with the knowledge of hazards. Some areas of the study perimeter are considered “zero or insignificant hazard areas”. These are the areas where the hazard has been studied and is zero. These areas are not included in the object class and do not have to be represented as hazard zones.

  14. f

    Data from: Average salary

    • froghire.ai
    Updated Apr 3, 2025
    + more versions
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    FrogHire.ai (2025). Average salary [Dataset]. https://www.froghire.ai/major/Surveying%20And%20Mapping
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    Dataset updated
    Apr 3, 2025
    Dataset provided by
    FrogHire.ai
    Description

    Explore the progression of average salaries for graduates in Surveying And Mapping from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Surveying And Mapping relative to other fields. This data is essential for students assessing the return on investment of their education in Surveying And Mapping, providing a clear picture of financial prospects post-graduation.

  15. g

    Map Viewing Service (WMS) of the dataset: PPRT Storengy (Area Zone)

    • gimi9.com
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    Map Viewing Service (WMS) of the dataset: PPRT Storengy (Area Zone) [Dataset]. https://gimi9.com/dataset/eu_fr-120066022-srv-49ec7223-0542-4553-9e2a-ec1359453f0a
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    License

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

    Description

    Area exposed to one or more hazards represented on the hazard map used for risk analysis of the RPP. The hazard map is the result of the study of hazards, the objective of which is to assess the intensity of each hazard at any point in the study area. The evaluation method is specific to each hazard type. It leads to the delimitation of a set of areas on the study perimeter constituting a zoning graduated according to the level of the hazard. The assignment of a hazard level at a given point in the territory takes into account the probability of occurrence of the dangerous phenomenon and its degree of intensity.For PPRTs the hazard levels are determined by effect effect on maps by type of effect and overall on an aggregated level on a synthesis map.All hazard areas represented on the hazard map are included. Areas protected by protective structures must be represented (possibly in a specific way) as they are always considered to be subject to hazard (cases of breakage or inadequacy of the structure).The hazard zones may be classified as data compiled in so far as they result from a synthesis using several sources of calculated, modelled or observed hazard data. These source data are not covered by this class of objects but by another standard dealing with the knowledge of hazards.Some areas of the study perimeter are considered “zero or insignificant hazard zones”. These are the areas where the hazard has been studied and is nil. These areas are not included in the object class and do not have to be represented as hazard zones.

  16. Consensus on activities and assessment methods that instil interprofessional...

    • figshare.com
    pdf
    Updated May 31, 2023
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    Gerard Filies; J Frantz (2023). Consensus on activities and assessment methods that instil interprofessional core competencies (data sets) [Dataset]. http://doi.org/10.6084/m9.figshare.17134679.v1
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    pdfAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Gerard Filies; J Frantz
    License

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

    Description

    Delphi round 1

    Suggested activities and assessments made by the participants for the IPE core competencies were ranked and captured accordingly.

    Delphi Round Two

    Fourteen of the experts participated in this round. The suggestions given for activities and assessment strategies that were common to the majority of participants were summarised and sent back to the participants for confirmation in the form of round two. Participants were requested to rate common suggestions on activities and assessments given as Likert items (see Table 2 and Table 3) and make necessary comments should there be any discrepancies.

  17. g

    Map visualisation service (WMS) of the dataset: Alea area of PPRT...

    • gimi9.com
    Updated Oct 2, 2022
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    (2022). Map visualisation service (WMS) of the dataset: Alea area of PPRT Nitro-Bickford | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_fr-120066022-srv-f5ddbff9-8e17-493e-bfab-f476b9e59044
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    Dataset updated
    Oct 2, 2022
    License

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

    Description

    Area exposed to one or more hazards shown on the hazard map used for the RPP risk analysis. The hazard map is the result of the study of hazards whose objective is to assess the intensity of each hazard at any point in the study area. The assessment method is specific to each type of hazard. It leads to the delimitation of a set of zones on the study perimeter constituting a graduated zoning according to the level of the hazard. The assignment of a hazard level at a given point in the territory takes into account the probability of occurrence of the dangerous phenomenon and its degree of intensity. For PPRTs hazard levels are determined effect by effect on maps by type of effects and overall according to an aggregate level on a synthesis map. All hazard areas shown on the hazard map are included. Areas protected by protective works must be represented (possibly in a specific way) because they are always considered subject to hazard (case of rupture or insufficiency of the structure). Hazard zones can be described as elaborated data to the extent that they result from a synthesis using several calculated, modelled or observed hazard data sources. These source data are not concerned by this class of objects but by another standard dealing with the knowledge of hazards. Some areas of the study perimeter are considered “zero or insignificant hazard areas”. These are the areas where the hazard has been studied and is zero. These areas are not included in the object class and do not have to be represented as hazard zones.

  18. g

    Map visualisation service (WMS) of the dataset: Alea area of PPRT Titanobel...

    • gimi9.com
    Updated Oct 2, 2022
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    (2022). Map visualisation service (WMS) of the dataset: Alea area of PPRT Titanobel | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_fr-120066022-srv-260ed15c-312a-4022-9447-2f65639b8d6b
    Explore at:
    Dataset updated
    Oct 2, 2022
    License

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

    Description

    Area exposed to one or more hazards shown on the hazard map used for the RPP risk analysis. The hazard map is the result of the study of hazards whose objective is to assess the intensity of each hazard at any point in the study area. The assessment method is specific to each type of hazard. It leads to the delimitation of a set of zones on the study perimeter constituting a graduated zoning according to the level of the hazard. The assignment of a hazard level at a given point in the territory takes into account the probability of occurrence of the dangerous phenomenon and its degree of intensity. For PPRTs hazard levels are determined effect by effect on maps by type of effects and overall according to an aggregate level on a synthesis map. All hazard areas shown on the hazard map are included. Areas protected by protective works must be represented (possibly in a specific way) because they are always considered subject to hazard (case of rupture or insufficiency of the structure). Hazard zones can be described as elaborated data to the extent that they result from a synthesis using several calculated, modelled or observed hazard data sources. These source data are not concerned by this class of objects but by another standard dealing with the knowledge of hazards. Some areas of the study perimeter are considered “zero or insignificant hazard areas”. These are the areas where the hazard has been studied and is zero. These areas are not included in the object class and do not have to be represented as hazard zones.

  19. f

    Data from: Average salary

    • froghire.ai
    Updated Apr 6, 2025
    + more versions
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    FrogHire.ai (2025). Average salary [Dataset]. https://www.froghire.ai/major/Surveying%20And%20Mapping%20Engineering
    Explore at:
    Dataset updated
    Apr 6, 2025
    Dataset provided by
    FrogHire.ai
    Description

    Explore the progression of average salaries for graduates in Surveying And Mapping Engineering from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Surveying And Mapping Engineering relative to other fields. This data is essential for students assessing the return on investment of their education in Surveying And Mapping Engineering, providing a clear picture of financial prospects post-graduation.

  20. g

    Map Viewing Service (WMS) of the dataset: Saint-Fromond PPRT hazard zone

    • gimi9.com
    + more versions
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    Map Viewing Service (WMS) of the dataset: Saint-Fromond PPRT hazard zone [Dataset]. https://gimi9.com/dataset/eu_fr-120066022-srv-896bf4f5-1c86-4870-9501-82c875be9c5f
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    License

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

    Area covered
    Saint-Fromond
    Description

    Area exposed to one or more hazards represented on the hazard map used for risk analysis of the RPP. The hazard map is the result of the study of hazards, the objective of which is to assess the intensity of each hazard at any point in the study area. The evaluation method is specific to each hazard type. It leads to the delimitation of a set of areas on the study perimeter constituting a zoning graduated according to the level of the hazard. The allocation of a hazard level at a given point in the territory takes into account the probability of occurrence of the dangerous phenomenon and its degree of intensity. For PPRTs the hazard levels are determined effect by effect on maps by type of effect and overall on an aggregated level on a synthesis map. All hazard areas shown on the hazard map are included. Areas protected by protective structures must be represented (possibly in a specific way) as they are always considered subject to hazard (case of breakage or inadequacy of the structure). Hazard zones can be described as developed data to the extent that they result from a synthesis using multiple sources of calculated, modelled or observed hazard data. These source data are not concerned by this class of objects but by another standard dealing with the knowledge of hazards. Some areas within the study area are considered “no or insignificant hazard zones”. These are the areas where the hazard has been studied and is nil. These areas are not included in the object class and do not have to be represented as hazard zones.

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Dept. of Commerce, Community, & Economic Development (2019). High School Graduate Count [Dataset]. https://hub.arcgis.com/maps/DCCED::high-school-graduate-count

High School Graduate Count

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181 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Sep 5, 2019
Dataset authored and provided by
Dept. of Commerce, Community, & Economic Development
Area covered
Description

Count of high school graduates for each public school in Alaska. Data covers the School Year 2013 to the present. Each year's count includes students graduating at any point during the school year (July 1 to June 30).Source: Alaska Department of Education & Early Development

This data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: Alaska Department of Education & Early Development Data Center.

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