13 datasets found
  1. a

    High School Graduate Count

    • gis.data.alaska.gov
    • rural-utility-business-advisory-hub-site-1-dcced.hub.arcgis.com
    • +5more
    Updated Sep 5, 2019
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    Dept. of Commerce, Community, & Economic Development (2019). High School Graduate Count [Dataset]. https://gis.data.alaska.gov/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 Graduate or Higher (census tract)

    • equity-lacounty.hub.arcgis.com
    • geohub.lacity.org
    • +3more
    Updated Oct 30, 2023
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    County of Los Angeles (2023). High School Graduate or Higher (census tract) [Dataset]. https://equity-lacounty.hub.arcgis.com/items/d1aeaa00288f481c81e2ad448d5ff341
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    Dataset updated
    Oct 30, 2023
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    For the original data source: https://data.census.gov/table/ACSDP5Y2023.DP02. Layer published for the Equity Explorer, a web experience developed by the LA County CEO Anti-Racism, Diversity, and Inclusion (ARDI) initiative in collaboration with eGIS and ISD. Visit the Equity Explorer to explore educational attainment and other equity related datasets and indices, including the COVID Vulnerability and Recovery Index. High School Graduate or Higher rates for census tracts in LA County from the US Census American Communities Survey (ACS), 2023. Estimates are based on 2020 census tract boundaries, and tracts are joined to 2021 Supervisorial Districts, Service Planning Areas (SPA), and Countywide Statistical Areas (CSA). For more information about this dataset, please contact egis@isd.lacounty.gov.

  3. f

    PERM cases by degree level

    • froghire.ai
    Updated Apr 3, 2025
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    FrogHire.ai (2025). PERM cases by degree level [Dataset]. https://www.froghire.ai/major/Civil%20Engineering%3B%20Gis%20Graduate%20Program
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    Dataset updated
    Apr 3, 2025
    Dataset provided by
    FrogHire.ai
    Description

    This pie chart illustrates the distribution of degrees—Bachelor’s, Master’s, and Doctoral—among PERM graduates from Civil Engineering; Gis Graduate Program. It shows the educational composition of students who have pursued and successfully obtained permanent residency through their qualifications in Civil Engineering; Gis Graduate Program. This visualization helps to understand the diversity of educational backgrounds that contribute to successful PERM applications, reflecting the major’s role in fostering students’ career paths towards permanent residency in the U.S.

  4. f

    Data from: Average salary

    • froghire.ai
    Updated Apr 3, 2025
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    FrogHire.ai (2025). Average salary [Dataset]. https://www.froghire.ai/major/Civil%20Engineering%3B%20Gis%20Graduate%20Program
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    Dataset updated
    Apr 3, 2025
    Dataset provided by
    FrogHire.ai
    Description

    Explore the progression of average salaries for graduates in Civil Engineering; Gis Graduate Program 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 Civil Engineering; Gis Graduate Program relative to other fields. This data is essential for students assessing the return on investment of their education in Civil Engineering; Gis Graduate Program, providing a clear picture of financial prospects post-graduation.

  5. c

    GIS Data for Spring 2017 Historic Preservation Studio

    • academiccommons.columbia.edu
    Updated 2017
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    Lubitz, Adam Samuel (2017). GIS Data for Spring 2017 Historic Preservation Studio [Dataset]. http://doi.org/10.7916/d8-evk7-7p14
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    Dataset updated
    2017
    Authors
    Lubitz, Adam Samuel
    Description

    Student-collected data as part of the Spring 2017 Historic Preservation studio titled, “Past as Prologue: Preservation as a Tool for Social Inclusion in Poughkeepsie, New York,” at the Columbia Graduate School of Architecture, Planning, and Preservation. Includes shapefiles for building footprints, water elements, National Register designations, building use-related survey results, and studio recommendations including trolley route.

  6. c

    GIS Data for Spring 2016 Historic Preservation Studio

    • academiccommons.columbia.edu
    Updated 2016
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    Alam, Tania; Angelucci, Valentina; Betz, Jessica; Canon, Elizabeth; Jallad, Mayssa; Kefalidis, Marisa; Lubitz, Adam; Menegus, Sarah; Mezydlo, Nicole; Prache, Ariane; Ray, Alex; Reddan, Sarah; Robertson, Cameron; Semrad, Allison; Sforza, Andrea; Spears, Teresa; Teng, Fei; Tomczyk, Stacy; Virbitsky, Katrina; Weinstein, Laura; Zhan, Mengjie; Zhang, Qi; Zhang, Yuanyi (2016). GIS Data for Spring 2016 Historic Preservation Studio [Dataset]. http://doi.org/10.7916/d8-ar2d-3f14
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    Dataset updated
    2016
    Authors
    Alam, Tania; Angelucci, Valentina; Betz, Jessica; Canon, Elizabeth; Jallad, Mayssa; Kefalidis, Marisa; Lubitz, Adam; Menegus, Sarah; Mezydlo, Nicole; Prache, Ariane; Ray, Alex; Reddan, Sarah; Robertson, Cameron; Semrad, Allison; Sforza, Andrea; Spears, Teresa; Teng, Fei; Tomczyk, Stacy; Virbitsky, Katrina; Weinstein, Laura; Zhan, Mengjie; Zhang, Qi; Zhang, Yuanyi
    Description

    GIS data used for Spring 2016 Historic Preservation studio titled, “A Study of Brooklyn's Cobble Hill and Boerum Hill Neighborhoods," at the Columbia Graduate School of Architecture, Planning, and Preservation. Includes shapefiles for building lots, soft sites, historic districts, and modified MapPLUTO data with corrected year built fields.

  7. a

    College Map

    • hub.arcgis.com
    • catalog.data.gov
    Updated Mar 15, 2017
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    National Center for Education Statistics (2017). College Map [Dataset]. https://hub.arcgis.com/items/54c1339972ad4b1eb347047c7ca3e616
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    Dataset updated
    Mar 15, 2017
    Dataset authored and provided by
    National Center for Education Statistics
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    Finding Schools is now easier than ever with the College Map, the first geographic search tool published by IPEDS (Integrated Postsecondary Education Data System) providing access to over 7,000 certificate, undergraduate and graduate-level schools. This all-in-one tool enables students, parents and counselors to filter potential programs for location, major, tuition and more. Including both certificate-level programs and advanced degrees, this public application makes the often overwhelming process of school searching simple, and it’s available on mobile devices.Once the results are narrowed down, users can share their lists on social media or download in excel format. Additionally, the College Map integrates with the College Navigator, a research based search tool providing data from the complete list of IPEDS Survey indicators.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

  8. High School Graduation Rate by School District

    • data-sccphd.opendata.arcgis.com
    • hub.arcgis.com
    Updated Feb 9, 2018
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    Santa Clara County Public Health (2018). High School Graduation Rate by School District [Dataset]. https://data-sccphd.opendata.arcgis.com/datasets/high-school-graduation-rate-by-school-district
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    Dataset updated
    Feb 9, 2018
    Dataset provided by
    Santa Clara County Public Health Departmenthttps://publichealth.sccgov.org/
    Authors
    Santa Clara County Public Health
    License

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

    Area covered
    Description

    High school 4-year cohort graduation rate, Santa Clara County, 2013-14. California Department of Education, DataQuest, 2013-14.

  9. Where are people who started college but did not finish?

    • hub.arcgis.com
    • atlas-connecteddmv.hub.arcgis.com
    Updated Oct 31, 2018
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    Urban Observatory by Esri (2018). Where are people who started college but did not finish? [Dataset]. https://hub.arcgis.com/maps/b15679adc8244399b6dc4a6848452a75
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    Dataset updated
    Oct 31, 2018
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    This map shows the percent of adults (25+) who have completed some college, but do not hold a degree - ideal places to implement college completion programs. For example, Texas implemented a state-wide program called GradTX aimed at helping stop-outs finish what they started. Other states such as Colorado and Florida have reverse transfer programs. An all-too common situation is that students take enough credits to successfully transfer from a 2-year college to a 4-year college, but do not attain an associate degree. Life happens and these transfer students do not graduate from the 4-year college, however, they have completed an additional semester or more of college credits. Reverse transfer programs allow these students to transfer these credits earned at the 4-year college back to the 2-year college in order to receive an associate degree. This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

  10. a

    Penn State Geodesign Masters Degree Capstone Projects

    • penn-state-geodesign-geodesignpsu.hub.arcgis.com
    Updated Feb 5, 2018
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    dmeehan_PSU (2018). Penn State Geodesign Masters Degree Capstone Projects [Dataset]. https://penn-state-geodesign-geodesignpsu.hub.arcgis.com/datasets/b00dffeb61784e78af50b7306dd48f3d
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    Dataset updated
    Feb 5, 2018
    Dataset authored and provided by
    dmeehan_PSU
    Description

    This application is a list of capstone projects for students in the Penn State Geodesign Masters in Professional Studies program.

  11. a

    EquityAtlas Education 2022 V2 DRAFT

    • egisdata-dallasgis.hub.arcgis.com
    Updated May 8, 2024
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    City of Dallas GIS Services (2024). EquityAtlas Education 2022 V2 DRAFT [Dataset]. https://egisdata-dallasgis.hub.arcgis.com/maps/b265b198e85e4f41944058a1b613970b
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    Dataset updated
    May 8, 2024
    Dataset authored and provided by
    City of Dallas GIS Services
    Area covered
    Description

    [Disclaimer: This application is a DRAFT and is still under development. Your feedback is welcome.]Data Use: This map showcases the educational attainment levels across Dallas, focusing on the percentage of the population that has graduated high school or achieved higher education. This data is crucial for identifying areas with high and low graduation rates, revealing disparities in educational opportunities. Understanding these variations can help policymakers and educators develop targeted interventions to improve educational outcomes, enhance economic opportunities, and reduce the long-term socioeconomic impacts of educational inequities.Data Source: U.S. Census Bureau, "Educational Attainment," American Community Survey, ACS 5-Year Estimates Subject Tables, Table S1501, 2022.Variables:S1501_C02_014E: Estimate Percent Population 25 years and over High school graduate or higher (%)S1501_C02_032E: Estimate Percent White, not Hispanic or Latino High school graduate or higher (%)S1501_C02_035E: Estimate Percent Black High school graduate or higher (%)S1501_C02_038E: Estimate Percent American Indian or Alaska Native High school graduate or higher (%)S1501_C02_041E: Estimate Percent Asian High school graduate or higher (%)S1501_C02_044E: Estimate Percent Native Hawaiian and Other Pacific Islander High school graduate or higher (%)S1501_C02_047E: Estimate Percent Some other race High school graduate or higher (%)S1501_C02_050E: Estimate Percent Two or more races High school graduate or higher (%)S1501_C02_053E: Estimate Percent Hispanic or Latino Origin High school graduate or higher (%)Education_Rank: Education RankRank Scoring Process: Census tracts were grouped into quintiles based on the percentage of high school graduates or higher (S1501_C02_014E).The scoring process categorizes each tract as follows:Score of 1: 98.1% - 100% (highest percentage of high school graduates or higher)Score of 2: 91.6% - 98.1%Score of 3: 78.4% - 91.5%Score of 4: 64.7% - 78.1%Score of 5: 31.9% - 64.6% (lowest percentage of high school graduates or higher)Year: 2022Provider: U.S. Census Bureau

  12. a

    Economics & Education Statistics - Cities

    • hub.arcgis.com
    • data-sccphd.opendata.arcgis.com
    Updated Feb 9, 2018
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    Santa Clara County Public Health (2018). Economics & Education Statistics - Cities [Dataset]. https://hub.arcgis.com/datasets/088a11e1af3e4ca9b1da4f8ac52735c4
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    Dataset updated
    Feb 9, 2018
    Dataset authored and provided by
    Santa Clara County Public Health
    License

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

    Area covered
    Description

    City, Median household income, Unemployed (ages GE 16), Families below 185% FPL, Children (ages 0-17) below 185% FPL, Children (ages 3-4) enrolled in preschool or nursery school, Less than high school, High school graduate, Some college or associates degree, College graduate or higher, High school graduate or less. Percentages unless otherwise noted. Source information provided at: https://www.sccgov.org/sites/phd/hi/hd/Documents/City%20Profiles/Methodology/Neighborhood%20profile%20methodology_082914%20final%20for%20web.pdf

  13. Economics & Education Statistics - Small Area/Neighborhood

    • data-sccphd.opendata.arcgis.com
    • hub.arcgis.com
    Updated Feb 21, 2018
    + more versions
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    Santa Clara County Public Health (2018). Economics & Education Statistics - Small Area/Neighborhood [Dataset]. https://data-sccphd.opendata.arcgis.com/datasets/economics-education-statistics-small-area-neighborhood
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    Dataset updated
    Feb 21, 2018
    Dataset provided by
    Santa Clara County Public Health Departmenthttps://publichealth.sccgov.org/
    Authors
    Santa Clara County Public Health
    License

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

    Area covered
    Description

    Neighborhood; Median household income; Unemployed (ages GE 16); Families below 185% FPL; Children (ages 0-17) below 185% FPL; Children (ages 3-4) enrolled in preschool or nursery school; Less than high school; High school graduate; Some college or associates degree; College graduate or higher; High school graduate or less. Percentages unless otherwise noted. Source information provided at: https://www.sccgov.org/sites/phd/hi/hd/Documents/City%20Profiles/Methodology/Neighborhood%20profile%20methodology_082914%20final%20for%20web.pdf

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

High School Graduate Count

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196 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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