16 datasets found
  1. a

    Master's Degree Attainment By Sex in the U.S.

    • univredlands.hub.arcgis.com
    Updated Oct 23, 2022
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    URSpatial (2022). Master's Degree Attainment By Sex in the U.S. [Dataset]. https://univredlands.hub.arcgis.com/maps/8461740d6ddd4599b48ce7b42c768bb0
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    Dataset updated
    Oct 23, 2022
    Dataset authored and provided by
    URSpatial
    Area covered
    Description

    This map uses the American Community Survey(ACS) Education Attainment Variables feature layer. Attributes used include Women 25 Years and Over whose Highest Education Completed is Master's Degree and Men 25 Years and Over whose Highest Education Completed is Master's Degree. Both attributes are mapped by two contrasting colors. If the county has more women than men with their master's degree than the county is given the color associated with the women attribute. If the county has more men than women with their master's degree than the county is given the color associated with the male attribute. Predominance smart mapping uses transparency to represent how big the gap is between how many women vs. men 25 years and over have obtained their master's degree. Less transparency represents a large gap, and more transparency represents a smaller gap.In general, this make shows that more women than men have a master's degree as their highest completed education. Learn more about the completion gap between women and men in higher education by the Pew Research Center here.

  2. Digital Bedrock Geologic-GIS Map of Minuteman National Historical Site and...

    • catalog.data.gov
    Updated Nov 25, 2025
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    National Park Service (2025). Digital Bedrock Geologic-GIS Map of Minuteman National Historical Site and Vicinity, Massachusetts (NPS, GRD, GRI, MIMA, mima_bedrock digital map) adapted from a Boston College Master's Thesis map by Langford and Hepburn (2007), a U.S. Geological Survey Bulletin map by Hansen (1956) and a U.S. Geological Survey Open-File Report map by Stone and Stone (2006) [Dataset]. https://catalog.data.gov/dataset/digital-bedrock-geologic-gis-map-of-minuteman-national-historical-site-and-vicinity-massac
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    Dataset updated
    Nov 25, 2025
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Boston
    Description

    The Digital Bedrock Geologic-GIS Map of Minuteman National Historical Site and Vicinity, Massachusetts 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 (mima_bedrock_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 and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (mima_bedrock_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 (mima_geology.gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (mima_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 (mima_bedrock_geology_metadata_faq.pdf). Please read the mima_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: http://www.google.com/earth/index.html. 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: Boston College and 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 (mima_bedrock_geology_metadata.txt or mima_bedrock_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) 25.4 meters or 83.3 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).

  3. a

    Shoreline Management Master Program / shorelinemmp area

    • king-snocoplanning.opendata.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Sep 18, 2003
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    King County (2003). Shoreline Management Master Program / shorelinemmp area [Dataset]. https://king-snocoplanning.opendata.arcgis.com/datasets/kingcounty::shoreline-management-master-program-shorelinemmp-area
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    Dataset updated
    Sep 18, 2003
    Dataset authored and provided by
    King County
    Area covered
    Description

    K.C. Shoreline Management Master Program. Related to SAO wetlands and FEMA floodpln (has boolean attributes floodpln and wetlands).

  4. Careers With GIS - Patrick Rickles

    • teachwithgis.co.uk
    Updated Mar 31, 2022
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    Esri UK Education (2022). Careers With GIS - Patrick Rickles [Dataset]. https://teachwithgis.co.uk/items/7d9de42f8d7f40688c3116da30c451e0
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    Dataset updated
    Mar 31, 2022
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri UK Education
    Description

    Hi, I'm Patrick,I initially pursued an undergraduate degree in Computer Science because I wanted to make video games; however, after taking an Environmental Science course, I wanted to see if there was a way I could study both. This led me to GIS and I made that my specialism, doing a Masters and later PhD on the subject.

  5. a

    Shoreline Master Program (SMP) Environment Designations / smp designations...

    • king-snocoplanning.opendata.arcgis.com
    Updated Sep 29, 2016
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    King County (2016). Shoreline Master Program (SMP) Environment Designations / smp designations area [Dataset]. https://king-snocoplanning.opendata.arcgis.com/maps/kingcounty::shoreline-master-program-smp-environment-designations-smp-designations-area
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    Dataset updated
    Sep 29, 2016
    Dataset authored and provided by
    King County
    Area covered
    Description

    For more information about this layer please see the GIS Data Catalog.SMP Environment Designations

  6. m

    Supplementary Datasets

    • data.mendeley.com
    Updated Mar 17, 2020
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    Natalia Novoselova (2020). Supplementary Datasets [Dataset]. http://doi.org/10.17632/8s3fps4vvb.2
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    Dataset updated
    Mar 17, 2020
    Authors
    Natalia Novoselova
    License

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

    Description

    The shared archived combined in Supplementary Datasets represent the actual databases used in the investigation considered in two papers:

    Meteorological conditions affecting black vulture (Coragyps atratus) soaring behavior in the southeast of Brazil: Implications for bird strike abatement (in submission)

    Remote sensing applications for abating the aircraft-bird strike risks in the southeast of Brazil (Human-Wildlife Interactions Journal, in print)

    The papers were based on my Master’s thesis defended in 2016 in the Institute of Biology of the University of Campinas (UNICAMP) in partial fulfilment of the requirements for the degree of Master in Ecology. Our investigation was devoted to reducing the risk of aircraft collision with Black vultures. It had two parts considered in these two papers. In the first one we studied the relationship between soaring activity of Black vultures and meteorological characteristics. In the second one we explored the dependence of soaring activity of vultures on superficial and anthropogenic characteristics. The study was implemented within surroundings of two airports in the southeast of Brazil taken as case studies. We developed the methodological approaches combining application of GIS and remote sensing technologies for data processing, which were used as the main research instrument. By dint of them we joined in the georeferenced databases (shapefiles) the data of bird's observation and three types of environmental factors: (i) meteorological characteristics collected together with the bird’s observation, (ii) superficial parameters (relief and surface temperature) obtained from the products of ASTER imagery; (iii) parameters of surface covering and anthropogenic pressure obtained from the satellite images of high resolution. Based on the analyses of the georeferenced databases, the relationship between soaring activity of vultures and environmental factors was studied; the behavioral patterns of vultures in soaring flight were revealed; the landscape types highly attractive for this species and forming the increased concentration of birds over them were detected; the maps giving a numerical estimation of hazard of bird strike events over the airport vicinities were constructed; the practical recommendations devoted to decrease the risk of collisions with vultures and other bird species were formulated.

    This archive contains all materials elaborated and used for the study, including the GIS database for two papers, remote sensing data, and Microsoft Excel datasets. You can find the description of supplementary files in the Description of Supplementary Dataset.docx. The links on supplementary files and their attribution to the text of papers are considered in the Attribution to the text of papers.docx. The supplementary files are in the folders Datasets, GIS_others, GIS_Raster, GIS_Shape.

    For any question please write me on this email: natalieenov@gmail.com

    Natalia Novoselova

  7. e

    Puyallup Shoreline Master Program Environments

    • epiceoc.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated Jun 15, 2020
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    City of Puyallup (2020). Puyallup Shoreline Master Program Environments [Dataset]. https://www.epiceoc.com/datasets/puyallup-shoreline-master-program-environments
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    Dataset updated
    Jun 15, 2020
    Dataset authored and provided by
    City of Puyallup
    Area covered
    Description

    Abstract:  This dataset 'approximately' represents the location of the SMP 200 foot shoreline environments of the Puyallup River and Clarks Creek within the City of Puyallup and its urban growth area.Purpose: This feature class is to be used to 'approximately' locate the 200 foot shoreline environment from the ordinary high water mark (OHWM) of the Puyallup River and Clarks Creek. The shoreline environments were created using the Clarks Creek centerline shapefile and Puyallup River polygon shapefile. Because this map was created using the afore mentioned sources (as apposed to the OHWM as required by the SMP), the shoreline evnironments shown here will extend further upland than depicted. As such these shoreline environments should be used as a reference only. Reports and field work conducted by qualified professional biologists are required to determine the true location of the OHWM/200 foot shoreline environment for any property along these waterways. NOTE: The puy_river.shp is a polygon shapefile which extends close to the shoreline but does not mark the OHWM of the river. The clarks_creek_cntr_ln.shp is a line feature class that does not come close to the shoreline of Clarks Creek. The shoreline, not the OHWM, can be anywhere from 20-30 feet on either side of the center line. For these reasons it is imperative to have a biologist establish the OHWM for Clarks Creek and the Puyallup River. Only then can the 200 foot shoreline environment be determined.

  8. a

    MATURE SUPPORT - Colleges and Universities in NJ, 3424

    • hub.arcgis.com
    Updated Jan 9, 2024
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    New Jersey Office of GIS (2024). MATURE SUPPORT - Colleges and Universities in NJ, 3424 [Dataset]. https://hub.arcgis.com/datasets/ab31a69538694428adc66319ac89bef2
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    Dataset updated
    Jan 9, 2024
    Dataset authored and provided by
    New Jersey Office of GIS
    Area covered
    Description

    This item is in mature support and is no longer updated. Available for historical reference only.This dataset contains the campus boundaries of Colleges and Universities of New Jersey mapped by parcel boundaries.The Colleges and Universities dataset is composed of any type of Post Secondary Education such as: colleges, universities, technical schools, trade schools, business schools, satellite (branch) campuses, etc. that grant First Professional, Associate, Bachelors, Masters, or Doctoral degrees. Secondary education facilities, Administrative offices, or Post Secondary Education facilities that are non degree granting schools are intended to be excluded from this dataset, but a few may be included. All data is non license restricted data that has been added from TGS research.

  9. Licensed Narcotic Treatment Programs

    • data.chhs.ca.gov
    • data.ca.gov
    • +5more
    Updated Nov 13, 2025
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    Department of Health Care Services (2025). Licensed Narcotic Treatment Programs [Dataset]. https://data.chhs.ca.gov/dataset/licensed-narcotic-treatment-programs
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    html, zip, geojson, kml, csv, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Nov 13, 2025
    Dataset provided by
    California Department of Health Care Serviceshttp://www.dhcs.ca.gov/
    Authors
    Department of Health Care Services
    Description

    The Narcotic Treatment Program Master List contains a list of all state-licensed and certified narcotic treatment programs. The Master List contains vital information for each program listed and additional details, such as the program’s address and contact information, total capacity, hours of operation and program director and medical director.

  10. n

    Estimating Mountain Lion Habitat Connectivity to Guide Wildlife Conservation...

    • data.niaid.nih.gov
    • dataone.org
    • +4more
    zip
    Updated May 31, 2022
    + more versions
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    Nikole Vannest; Grace Kumaishi (2022). Estimating Mountain Lion Habitat Connectivity to Guide Wildlife Conservation at The Nature Conservancy’s Jack and Laura Dangermond Preserve; University of California Santa Barbara; 2021-2022. [Dataset]. http://doi.org/10.25349/D9QG8X
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    zipAvailable download formats
    Dataset updated
    May 31, 2022
    Dataset provided by
    University of California, Santa Barbara
    Authors
    Nikole Vannest; Grace Kumaishi
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Santa Barbara
    Description

    This submission is from a master's group thesis project at The Bren School of Environmental Science & Management at the University of California, Santa Barbara, and contains the final written report and associated datasets. The graduate student researchers who completed this project include: Meghan Fletcher, Alyssa Kibbe, Grace Kumaishi, Anna Talken, and Nikole Vannest.

    The California landscape has been fragmented by urban development, infrastructure, and agriculture. Maintaining connectivity between areas of wildlife habitat is important for the viability of many long-ranging species, such as the mountain lion (Puma concolor). Mountain lion populations are highly susceptible to habitat fragmentation, and face reduced access to resources and decreased genetic diversity. This study explores the habitat connectivity between the Jack and Laura Dangermond Preserve (JLDP), a 24,460 acre protected property owned by The Nature Conservancy (TNC), and neighboring protected areas to identify potential pathways of movement for mountain lions along the Central and Southern California coast. In this project, we: 1) determine regional connectivity and least cost paths between core habitats by modeling suitable mountain lion habitat, 2) estimate mountain lion habitat use and movement on JLDP by performing a site-level suitability and corridor analysis and 3) create a short film focused on highlighting our research, the role that JLDP plays in conservation, and the importance of habitat connectivity. The results of our project show that JLDP contains suitable habitat for mountain lions and may play a positive role in coastal connectivity. When considering the connectivity between JLDP and other regional protected areas, our analyses indicate that urbanized coastal regions act as barriers to mountain lions and contain pinch points that channelize movement. These results can guide TNC in developing management strategies for protecting mountain lions on JLDP and in the surrounding region.

    Analyses were conducted using ArcGIS, Google Earth Engine, MaxENT, Circuitscape, and Omniscape. The project began in April 2021 and ended in June 2022. Methods Data was collected from open source data acquired using Google Earth Engine and Esri ArcOnline from the following sources: NASA, USGS, JPL-CalTech, Conservation Science Partners, CalFish, US Census and CalFire. It was processed using Esri ArcMap, ArcGIS Pro, Maxent, Omniscape via Jupyter Notebook and the Linkage Mapper Toolkit within ArcMap.

  11. a

    Shoreline Master Program Environment Designations

    • city-of-lakewood-geodata-portal-cityoflakewood.hub.arcgis.com
    Updated Dec 11, 2024
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    City of Lakewood, Washington (2024). Shoreline Master Program Environment Designations [Dataset]. https://city-of-lakewood-geodata-portal-cityoflakewood.hub.arcgis.com/datasets/shoreline-master-program-environment-designations
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    Dataset updated
    Dec 11, 2024
    Dataset authored and provided by
    City of Lakewood, Washington
    Area covered
    Description

    This data represents Environment Designations according to the City of Lakewood Shoreline Master Program.

  12. a

    Shoreline Master Program Open Data

    • pend-oreille-county-open-data-pendoreilleco.hub.arcgis.com
    Updated Jun 23, 2022
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    Pend Oreille County (2022). Shoreline Master Program Open Data [Dataset]. https://pend-oreille-county-open-data-pendoreilleco.hub.arcgis.com/datasets/shoreline-master-program-open-data/about
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    Dataset updated
    Jun 23, 2022
    Dataset authored and provided by
    Pend Oreille County
    Area covered
    Description

    Pend Oreille County Shoreline Master Program Designations

  13. Sustainable Development Report 2023 (with indicators)

    • sdg-transformation-center-sdsn.hub.arcgis.com
    Updated Jun 20, 2023
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    Sustainable Development Solutions Network (2023). Sustainable Development Report 2023 (with indicators) [Dataset]. https://sdg-transformation-center-sdsn.hub.arcgis.com/datasets/b488b8eeb229473f8cd332f67b0cace2
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    Dataset updated
    Jun 20, 2023
    Dataset authored and provided by
    Sustainable Development Solutions Networkhttps://www.unsdsn.org/
    Area covered
    Description

    Link to this report's codebookAbout the AuthorsProf. Jeffrey SachsDirector, SDSN; Project Director of the SDG IndexJeffrey D. Sachs is a world-renowned professor of economics, leader in sustainable development, senior UN advisor, bestselling author, and syndicated columnist whose monthly newspaper columns appear in more than 100 countries. He is the co-recipient of the 2015 Blue Planet Prize, the leading global prize for environmental leadership, and many other international awards and honors. He has twice been named among Time magazine’s 100 most influential world leaders. He was called by the New York Times, “probably the most important economist in the world,” and by Time magazine, “the world’s best known economist.” A survey by The Economist in 2011 ranked Professor Sachs as amongst the world’s three most influential living economists of the first decade of the 21st century.Professor Sachs serves as the Director of the Center for Sustainable Development at Columbia University. He is University Professor at Columbia University, the university’s highest academic rank. During 2002 to 2016 he served as the Director of the Earth Institute. Sachs is Special Advisor to United Nations Secretary-General António Guterres on the Sustainable Development Goals, and previously advised UN Secretary-General Ban Ki-moon on both the Sustainable Development Goals and Millennium Development Goals and UN Secretary-General Kofi Annan on the Millennium Development Goals.Guillaume LafortuneDirector, SDSN Paris; Scientific Co-Director of the SDG IndexGuillaume Lafortune took up his duties as Director of SDSN Paris in January 2021. He joined SDSN in 2017 to coordinate the production of the Sustainable Development Report and other projects on SDG data and statistics.Previously, he has served as an economist at the Organisation for Economic Co-operation and Development (OECD) working on public governance reforms and statistics. He was one of the lead advisors for the production of the 2015 and 2017 flagship statistical report Government at a Glance. He also contributed to analytical work related to public sector efficiency, open government data and citizens’ satisfaction with public services. Earlier, Guillaume worked as an economist at the Ministry of Economic Development in the Government of Quebec (Canada). Guillaume holds a M.Sc in public administration from the National School of Public Administration (ENAP) in Montreal and a B.Sc in international economics from the University of Montreal.Contact: EmailGrayson FullerSenior Analyst, SDG Index, SDSNGrayson Fuller is the Senior Analyst at SDSN. His role consists of managing the data, coding, and statistical analyses for the SDG Index and Dashboards report. He additionally carries out research related to sustainable development. Grayson received his Masters degree in Economic Development at Sciences Po Paris. He holds a Bachelors in Latin American Studies from Harvard University, where he graduated cum laude. Grayson has lived in several Latin American countries and speaks English, Spanish, French, Portuguese, and Russian. He enjoys playing violin and hails from Atlanta, GA.Contact: EmailEamon DrummSenior Program Officer, SDG Transformation CenterEamon Drumm leads the SDG Transformation Center. He has previously worked on policy coherence for sustainable development at the OECD and the UNESCO World Heritage Centre. He also worked for many years for an energy services company developing energy efficiency programs and smart city software products for cities… Originally trained as an urban planner, he has degrees in public policy and urban planning from Sciences Po Paris, the Sorbonne and the University of Virginia. He is originally from the United States and has been living in France since 2010.Contact: EmailAbout the PublishersDublin University PressDublin University Press is Ireland’s oldest printing and publishing house with its origins in Trinity College Dublin in 1734. The mission of Dublin University Press is to benefit society through scholarly communication, education, research and discourse. To further this goal, the Press operates as an open, innovative and inclusive channel for high quality scholarly publishing with an emphasis on equity, diversity and inclusion and with full support for author copyright retention, open access and open scholarship. As an independent, non-profit, ethical and research-centric publisher, Dublin University Press is committed to fostering the achievement of the United Nations Sustainable Development Goals.Sustainable Development Solutions Network (SDSN)The Sustainable Development Solutions Network (SDSN) has been operating since 2012 under the auspices of the UN Secretary-General. SDSN mobilizes global scientific and technological expertise to promote practical solutions for sustainable development, including the implementation of the Sustainable Development Goals (SDGs) and the Paris Climate Agreement.

  14. a

    Nursing Education Programs

    • center-for-health-statistics-gis-map-collection-txdshsea.hub.arcgis.com
    Updated Jun 3, 2022
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    Texas Department of State Health Services (2022). Nursing Education Programs [Dataset]. https://center-for-health-statistics-gis-map-collection-txdshsea.hub.arcgis.com/items/3227f48da869473a8ed37a0bc600bfda
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    Dataset updated
    Jun 3, 2022
    Dataset authored and provided by
    Texas Department of State Health Services
    Area covered
    Description

    This map shows locations that provide ADN (associate degree nursing), AE-MSN (alternate entry master of science in nursing), Diploma, BSN (bachelor of science in nursing), DE-MSN (direct entry master of science in nursing), and LVN (licensed vocation nursing) certifications. The data includes information on pass rates from 2020 through 2024.This map was created with data from Texas Center for Nursing Workforce Studies and last updated in May 2025.

  15. Sustainable Development Report 2025 (with indicators)

    • sdg-transformation-center-sdsn.hub.arcgis.com
    Updated Jun 4, 2025
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    Sustainable Development Solutions Network (2025). Sustainable Development Report 2025 (with indicators) [Dataset]. https://sdg-transformation-center-sdsn.hub.arcgis.com/datasets/sdsn::sustainable-development-report-2025-with-indicators/explore
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    Dataset updated
    Jun 4, 2025
    Dataset authored and provided by
    Sustainable Development Solutions Networkhttps://www.unsdsn.org/
    Area covered
    Description

    Since 2016, the Sustainable Development Report (SDR) has provided the most up-to-date data available to track and rank the performance of all UN member states on the SDGs. Eighty years after the creation of the UN system, the report also provides improved and updated measures to track countries' efforts to support UN-based multilateralism. In total, more than 200,000 individual data points are used to produce 200+ country and regional SDG profiles. This year's edition was authored by a group of independent experts at the SDG Transformation Center, an initiative of the SDSN.This year's SDR emphasizes the following eight key message:Global commitment to the SDGs is strong: 190 out of 193 countries have presented national action plans for advancing sustainable development. A decade after the adoption of Agenda 30 and the SDGs, 190 of the 193 UN member states have participated in the Voluntary National Review (VNR) process, presenting their SDG implementation plans and sustainable development priorities to the international community. The European Union and State of Palestine have also presented VNRs. Most UN member states have presented two or more VNRs, and 39 countries volunteered to present one in 2025. Only three UN member states have not taken part in the VNR process: Haiti, Myanmar, and the United States. Additionally, a growing number of regional and local leaders have prepared Voluntary Local Reviews (VLRs) to report on SDG implementation at the subnational level. As of March 2025, 249 VLRs were listed on the dedicated UN websiteEast and South Asia has outperformed all other regions in SDG progress since 2015. This year's SDR introduces a streamlined SDG Index (SDGi), which uses 17 headline indicators to track overall SDG progress. On average, East and South Asia has shown the fastest progress on the SDGs since 2015, driven notably by rapid progress on the socioeconomic targetOther countries that have progressed more rapidly than their peers include the following: Benin (Sub-Saharan Africa), Nepal (East and South Asia), Peru (Latin America and the Caribbean), the United Arab Emirates (Middle East and North Africa), Uzbekistan (Eastern Europe and Central Asia), Costa Rica (OECD), and Saudi Arabia (G20)European countries continue to top the SDG Index. Finland ranks first this year and 19 of the top 20 countries are in Europe. Yet even these countries face significant challenges in achieving at least two goals, including those related to climate and biodiversity. In this year's SDG Index, China (#49) and India (#99) have entered the top 50 and top 100 performers respectivelyOn average globally, the SDGs are far off-track. At the global level, none of the 17 goals are currently on course to be achieved by 2030. Conflicts, structural vulnerabilities, and limited fiscal space impede SDG progress in many parts of the world. But while only 17 percent of the targets are on track to be achieved worldwide, most UN member states have made strong progress on targets related to access to basic services and infrastructure, including mobile broadband use (SDG 9), access to electricity (SDG 7), internet use (SDG 9), under-5 mortality rate (SDG 3), and neonatal mortality (SDG 3)Barbados ranks first and the United States ranks last in UN-based multilateralism. Barbados stands out as the country most committed to UN-based multilateralism, while the United States ranks last in this year's Index of countries' support for UN-based multilateralism (UN-Mi). In early 2025, the United States announced its withdrawal from the Paris Climate Agreement and the World Health Organization (WHO) and formally declared its opposition to the SDGs and the 2030 Agenda. Among G20 countries, Brazil is the most committed to UN-based multilateralism, with Chile leading among OECD countries For many developing countries, a lack of fiscal space is the major obstacle to SDG progress. Roughly half the world's population lives in countries that cannot invest adequately in sustainable development due to debt burdens and a lack of access to affordable, long-term capital. Global public goods are vastly under-financed. UN member states gathering at the 4th International Conference on Financing for Development (FfD4) in Seville, Spain (June 30 – July 3, 2025) have an enormous responsibility, not only to their own citizens but to all of humanitySustainable development offers high returns: capital should flow to the emerging and developing countries on more favourable terms. The Global Financial Architecture (GFA) is broken. Money flows readily to rich countries and not to the emerging and developing economies (EMDEs) that offer higher growth potential and rates of return. At the top of the agenda at FfD4 is the need to reform the GFA so that capital flows in far larger sums to the EMDEs. Part 1 of this report (also published online by the SDSN in May 2025) offers practical recommendations to scale up and align international financing flows to support global public goods and achieve sustainable development.About the AuthorsProf. Jeffrey Sachs, Director, SDSN; Project Director of the SDG IndexJeffrey D. Sachs is a world-renowned professor of economics, leader in sustainable development, senior UN advisor, bestselling author, and syndicated columnist whose monthly newspaper columns appear in more than 100 countries. He is the co-recipient of the 2015 Blue Planet Prize, the leading global prize for environmental leadership, and many other international awards and honors. He has twice been named among Time magazine’s 100 most influential world leaders. He was called by the New York Times, “probably the most important economist in the world,” and by Time magazine, “the world’s best known economist.” A survey by The Economist in 2011 ranked Professor Sachs as amongst the world’s three most influential living economists of the first decade of the 21st century.Professor Sachs serves as the Director of the Center for Sustainable Development at Columbia University. He is University Professor at Columbia University, the university’s highest academic rank. During 2002 to 2016 he served as the Director of the Earth Institute. Sachs is Special Advisor to United Nations Secretary-General António Guterres on the Sustainable Development Goals, and previously advised UN Secretary-General Ban Ki-moon on both the Sustainable Development Goals and Millennium Development Goals and UN Secretary-General Kofi Annan on the Millennium Development Goals.Guillaume Lafortune Director, SDSN Paris; Scientific Co-Director of the SDG IndexGuillaume Lafortune took up his duties as Director of SDSN Paris in January 2021. He joined SDSN in 2017 to coordinate the production of the Sustainable Development Report and other projects on SDG data and statistics.Previously, he has served as an economist at the Organisation for Economic Co-operation and Development (OECD) working on public governance reforms and statistics. He was one of the lead advisors for the production of the 2015 and 2017 flagship statistical report Government at a Glance. He also contributed to analytical work related to public sector efficiency, open government data and citizens’ satisfaction with public services. Earlier, Guillaume worked as an economist at the Ministry of Economic Development in the Government of Quebec (Canada). Guillaume holds a M.Sc in public administration from the National School of Public Administration (ENAP) in Montreal and a B.Sc in international economics from the University of Montreal.Contact: guillaume.lafortune@unsdsn.org Grayson Fuller Manager, SDG Index & Data team, SDSNGrayson Fuller is the lead statistician and senior manager for the SDG Index, and of the team working on SDG data and statistics at SDSN. He is co-author of the Sustainable Development Report, for which he manages the data, coding, and statistical analyses. He also coordinates the production of regional and subnational editions of the SDG Index, in addition to other statistical reports, in collaboration with national governments, NGOs and international organizations such as the WHO, UNDP and the European Commission. Grayson received his Masters degree in Economic Development at Sciences Po Paris. He holds a Bachelors in Romance Languages and Latin American Studies from Harvard University, where he graduated cum laude. Grayson has lived in several Latin American countries and speaks English, Spanish, French, Portuguese and Italian. He enjoys playing the violin, rock-climbing and taking care of his numerous plants in his free time.Contact: grayson.fuller@unsdsn.orgGuilherme Iablonovski GIS Specialist, SDG Index & Data team, SDSNGuilherme Iablonovski is a Geospatial Data Specialist at SDSN, where he conceptualizes and develops new geospatial indicators to measure important aspects of the Sustainable Development Goals. He holds a M.Sc in Urban and Environmental Planning from the Ecole d'Urbanisme de Paris, where his research focused on urban metabolism, environmental sustainability and universal scaling laws. Before joining SDSN, Guilherme worked as a solutions engineer for Esri and as geospatial data scientist for humanitarian organizations such as the World Bank, the Red Cross and UNEP. He also teaches GIS at the Peace Studies Master Programme at Université Paris-Dauphine PSL.Contact: guilherme.iablonovski@unsdsn.org---About the PublishersDublin University Press Dublin University Press is Ireland’s oldest printing and publishing house with its origins in Trinity College Dublin in 1734. The mission of Dublin University Press is to benefit society through scholarly communication, education, research and discourse. To further this goal, the Press operates as an open, innovative and inclusive channel for high quality scholarly publishing with an emphasis on equity, diversity and inclusion and with full support for author copyright retention, open access and open scholarship. As an independent, non-profit,

  16. a

    Economics & Education Statistics - Small Area/Neighborhood

    • hub.arcgis.com
    • data-sccphd.opendata.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://hub.arcgis.com/datasets/c93017c1bf7340b6bbbc19ce86cf9717
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    Dataset updated
    Feb 21, 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

    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

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

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URSpatial (2022). Master's Degree Attainment By Sex in the U.S. [Dataset]. https://univredlands.hub.arcgis.com/maps/8461740d6ddd4599b48ce7b42c768bb0

Master's Degree Attainment By Sex in the U.S.

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Dataset updated
Oct 23, 2022
Dataset authored and provided by
URSpatial
Area covered
Description

This map uses the American Community Survey(ACS) Education Attainment Variables feature layer. Attributes used include Women 25 Years and Over whose Highest Education Completed is Master's Degree and Men 25 Years and Over whose Highest Education Completed is Master's Degree. Both attributes are mapped by two contrasting colors. If the county has more women than men with their master's degree than the county is given the color associated with the women attribute. If the county has more men than women with their master's degree than the county is given the color associated with the male attribute. Predominance smart mapping uses transparency to represent how big the gap is between how many women vs. men 25 years and over have obtained their master's degree. Less transparency represents a large gap, and more transparency represents a smaller gap.In general, this make shows that more women than men have a master's degree as their highest completed education. Learn more about the completion gap between women and men in higher education by the Pew Research Center here.

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