Complete Topographic dataset in shapefile format. Consume this dataset if you wish to download the entire Topographic dataset at once.

The attached zip file contains the shapefile for Oakland's city council districts. You need all the files included in the zip file to open the .shp file, so please download the whole zip archive.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data for each decennial census. The Census Bureau delineates ZCTA boundaries for the United States, Puerto Rico, American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands once each decade following the decennial census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery. The Census Bureau uses tabulation blocks as the basis for defining each ZCTA. Tabulation blocks are assigned to a ZCTA based on the most frequently occurring ZIP Code for the addresses contained within that block. The most frequently occurring ZIP Code also becomes the five-digit numeric code of the ZCTA. These codes may contain leading zeros. Blocks that do not contain addresses but are surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA. Because the Census Bureau only uses the most frequently occurring ZIP Code to assign blocks, a ZCTA may not exist for every USPS ZIP Code. Some ZIP Codes may not have a matching ZCTA because too few addresses were associated with the specific ZIP Code or the ZIP Code was not the most frequently occurring ZIP Code within any of the blocks where it exists. The ZCTA boundaries in this release are those delineated following the 2020 Census.

Complete Cadastral dataset in shapefile format. Consume this dataset if you wish to download the entire Cadastral dataset at once.

Complete Drainage Utility Network in file shapefile format. Consume this dataset if you wish to download the entire Drainage Utility network dataset at once.

Complete Water Utility Network in file shapefile format. Consume this dataset if you wish to download the entire Water Utility network dataset at once.

The 2022 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The generalized boundaries for counties and equivalent entities are based on those as of January 1, 2022, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

A shapefile for mapping data by Modified Zip Code Tabulation Areas (MODZCTA) in NYC, based on the 2010 Census ZCTA shapefile. MODZCTA are being used by the NYC Department of Health & Mental Hygiene (DOHMH) for mapping COVID-19 Data.

🚢 Stanford Human Preferences Dataset (SHP)

If you mention this dataset in a paper, please cite the paper: Understanding Dataset Difficulty with V-Usable Information (ICML 2022).

  Summary

SHP is a dataset of 385K collective human preferences over responses to questions/instructions in 18 different subject areas, from cooking to legal advice. The preferences are meant to reflect the helpfulness of one response over another, and are intended to be used for training RLHF… See the full description on the dataset page: https://huggingface.co/datasets/stanfordnlp/SHP.

Complete Rights of Way dataset in shapefile format. Consume this dataset if you wish to download the entire Rights of Way dataset at once.

Download high-quality, up-to-date Mexico shapefile boundaries (SHP, projection system SRID 4326). Our Mexico Shapefile Database offers comprehensive boundary data for spatial analysis, including administrative areas and geographic boundaries. This dataset contains accurate and up-to-date information on all administrative divisions, zip codes, cities, and geographic boundaries, making it an invaluable resource for various applications such as geographic analysis, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including Shapefile, GeoJSON, KML, ASC, DAT, CSV, and GML, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

Overview

Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.

Our self-hosted geospatial data cover postal divisions for the whole world. The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.

Use cases for the Global Boundaries Database (Geospatial data, Map data, Polygon daa)

• In-depth spatial analysis

• Clustering

• Geofencing

• Reverse Geocoding

• Reporting and Business Intelligence (BI)

Product Features

• Coherence and precision at every level

• Edge-matched polygons

• High-precision shapes for spatial analysis

• Fast-loading polygons for reporting and BI

• Multi-language support

For additional insights, you can combine the map data with:

• Population data: Historical and future trends

• UNLOCODE and IATA codes

• Time zones and Daylight Saving Time (DST)

Data export methodology

Our location data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson

All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why companies choose our map data

• Precision at every level

• Coverage of difficult geographies

• No gaps, nor overlaps

Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.

This database consists of a series of maps that depict the spatial distribution of nearshore topo-bathymetric transects along the peak wave directions and accompanying profiles that present elevation and depth values along these transects on the islands of Maui and Molokai.

Transects are identified by Francis et al. (2024a). State of Hawaii Department of Transportation (HDOT) state routes and Maui County Roads are acquired from HDOT (2023) and MC (2022). Shoreline datasets are provided by NGS (2017). Elevation and depth values along the transects are referenced to local mean sea level (LMSL) and are sampled from a digital elevation model (DEM) prepared by Francis et al. (2019).

References 1) Francis, O., Yang, L., & Togia, H. (2024a). Ocean Hazards Database (OHD) for the State of Hawaii Maui County Coastal Roads Report [Data set]. https://doi.org/10.17632/ndyy8nz77x.

2) Francis, O., Yang, L., Togia, H., & Tumino Di Costanzo, G. (2019). Ocean Hazards Database (OHD) for the State of Hawaii Statewide Coastal Highway Program Report [Data set]. https://doi.org/10.17632/7p3hyypmjm.

3) Francis, O., Zhang, G., Ma, D., Robertson, I., Togia, H., Yang, L., Eyre, K., Rossi, C., Martinez, B.A., Han, R., Hataishi, M., Hunter, N., Takahashi, C., Wang, Y., Yang, H., Zhou, S., & Yuan. R. (2024b). State of Hawaii Maui County coastal roads report. Prepared for the Maui County and State of Hawaii Department of Transportation, Project number HWY-L 2.3089, February 26, 2024.

4) HDOT (State of Hawaii Department of Transportation). (2023). “hpms” [shapefile]. Scale Not Given. HPMS (Highway Performance Monitoring System Roads for Hawaii - 2021). Hawaii Statewide GIS Program. Retrieved from https://files.hawaii.gov/dbedt/op/gis/data/hpms.shp.zip (September 2023).

5) MC (Maui County) (2022). “roads_mau” [shapefile]. Scale Not Given. Maui County Roads (2022). Hawaii Statewide GIS Program. Retrieved from https://files.hawaii.gov/dbedt/op/gis/data/roads_mau.shp.zip (September 2023).

6) NGS (National Geodetic Survey) (2017). National Oceanic and Atmospheric Administration (NOAA) Continually Updated Shoreline Product (CUSP). Retrieved from https://www.ngs.noaa.gov/CUSP/ (October 2017).

This database consists of a series of maps showing tsunami inundation based on historical events (1946 Aleutian, 1952 Kamchatka, 1957 Aleutian, 1960 Chile, and 1964 Alaska tsunamis) and hypothetical events (two great Aleutian earthquakes with moment magnitude (Mw) 9.3 and 9.6 as potential sources). Individual maps show inundation across mile-long sections of Hawaii state routes on the islands of Hawaii, Maui, Molokai, Oahu and Kauai previously identified for their vulnerability to the effects of climate change as part of the Statewide Coastal Highways Project Report.

Mileposts are identified by Brandes et al. (2019). State of Hawaii Department of Transportation (HDOT) state routes and county street centerline datasets are acquired from HDOT (2017) and HOLIS, C&CH (2017). Shoreline datasets are provided by NGS (2017).

Please read ‘Description-Map of Tsunami Inundation.docx’ for detailed information.

References Brandes, H., Doygun, O., Rossi, C., Francis, O., Yang, L., and Togia, H., (2019) Coastal Road Exposure Susceptibility Index (CRESI) for the State of Hawaii Statewide Coastal Highway Program Report. Department of Civil and Environmental Engineering, University of Hawai'i at Manoa, doi: 10.17632/frr3fsx3j6.2. HDOT (State of Hawaii Department of Transportation). “StateRoutes_SDOT” [shapefile]. Scale Not Given. State Routes. Hawaii Statewide GIS Program. Retrieved from http://files.hawaii.gov/dbedt/op/gis/data/StateAndCountyRoutes.shp.zip (December 2017). HOLIS, C&CH (Honolulu Land Information System, City and County of Honolulu). “Oah_streets” [shapefile]. Scale Not Given. Oahu Street Centerlines. Hawaii Statewide GIS Program. Retrieved from http://geoportal.hawaii.gov/datasets/roads-honolulu-county (December 2017). NGS (National Geodetic Survey) (2017). National Oceanic and Atmospheric Administration (NOAA) Continually Updated Shoreline Product (CUSP). Retrieved from https://www.ngs.noaa.gov/CUSP/ (October 2017).

These files add to and replace same-named files found within Submission 559 (hover over file display names to see actual file names in bottom-left corner of screen) The files included in this submission contain all data pertinent to the methods and results of a cohesive multi-state analysis of all known potential geothermal reservoirs in sedimentary rocks in the Appalachian Basin region, ranked by their potential favorability. Favorability is quantified using three metrics: Reservoir Productivity Index for water; Reservoir Productivity Index; Reservoir Flow Capacity. The metrics are explained in the Reservoirs Methodology Memo (included in zip file). The product represents a minimum spatial extent of potential sedimentary rock geothermal reservoirs. Only natural porosity and permeability were analyzed. Shapefile and images of the spatial distributions of these reservoir quality metrics and of the uncertainty on these metrics are included as well.

UPDATE: Accompanying geologic reservoirs data may be found at: https://gdr.openei.org/submissions/881 (linked below). Shapefile containing county boundaries for New York, Pennsylvania, and West Virginia. Contains dbf data file as well.

This project focused on defining geothermal play fairways and development of a detailed geothermal potential map of a large transect across the Great Basin region (96,000 km2), with the primary objective of facilitating discovery of commercial-grade, blind geothermal fields (i.e. systems with no surface hot springs or fumaroles) and thereby accelerating geothermal development in this promising region. Data included in this submission consists of: structural settings (target areas, recency of faulting, slip and dilation potential, slip rates, quality), regional-scale strain rates, earthquake density and magnitude, gravity data, temperature at 3 km depth, permeability models, favorability models, degree of exploration and exploration opportunities, data from springs and wells, transmission lines and wilderness areas, and published maps and theses for the Nevada Play Fairway area. Listing and location of all power plants and type within the Great Basin

This data package contains extracts from open datasets to support
the tutorials available at https://github.com/nismod/snail/

This version of the data goes with v0.1 of the tutorials:

https://github.com/nismod/snail/releases/tag/v0.1

WRI Aqueduct Flood Hazard Maps

`flood_layer` contains data extracted and derived from the Aqueduct
Flood Hazard Maps (version 2, updated October 20, 2020).

See https://www.wri.org/resources/data-sets/aqueduct-floods-hazard-maps

These data are shared under the CC-BY Creative Commons Attribution
License 4.0 - https://creativecommons.org/licenses/by/4.0/

Citation: Ward, P.J., H.C. Winsemius, S. Kuzma,
M.F.P. Bierkens, A. Bouwman, H. de Moel, A. Díaz Loaiza, et
al. 2020. “Aqueduct Floods Methodology.” Technical Note.
Washington, D.C.: World Resources Institute. Available online at:
www.wri.org/publication/aqueduct-floods-methodology.

Ghana - Subnational Administrative Boundaries

`gha_admbnda_gss_20210308_shp` contains data from Ghana Statistical
Services (GSS) contributed to Humanitarian Data Exchange by the OCHA
Regional Office for West and Central Africa, updated 11 March 2021.

See https://data.humdata.org/m/dataset/ghana-administrative-boundaries

These data are shared under the Creative Commons Attribution for
Intergovernmental Organisations (CC BY-IGO) - https://creativecommons.org/licenses/by/3.0/igo/

Ghana OpenStreetMap Extract

`ghana-latest-free.shp` contains data extracted from OpenStreetMap
and downloaded from GeoFabrik.

The files in this archive have been created from OpenStreetMap data
and are licensed under the Open Database 1.0 License. See
www.openstreetmap.org for details about the project.

This file contains OpenStreetMap data as of 2021-03-22T21:21:57Z.

More recent updates will be made available daily here:

http://download.geofabrik.de/africa/ghana-latest-free.shp.zip

A documentation of the layers in this shape file is available here:

http://download.geofabrik.de/osm-data-in-gis-formats-free.pdf

Ghana Road Network

`GHA_OSM_roads.gpkg` contains data derived from the OpenStreetMap
extract above, and can be reproduced by running through nismod/snail
tutorial 01.

These data are shared under the same Open Database 1.0 License. See
www.openstreetmap.org for details about the project.

Natural Earth Country Boundaries

`ne_10m_admin_0_countries` contains Natural Earth 1:10m Cultural Vectors,
Admin ) - Countries version 4.1.0

See https://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-countries/

These data are declared to be in the public domain, and may be shared
and modified without restriction - https://www.naturalearthdata.com/about/terms-of-use/

QGIS project

`overview.qgz` is a QGIS project intended to help preview and explore
the data in this package.

It is shared under the CC-BY Creative Commons Attribution
License 4.0 - https://creativecommons.org/licenses/by/4.0/

Please cite it as part of this data package, by Tom Russell (2021).

Results

`results` contains the results of analysis that can be reproduced
by running through all the nismod/snail tutorials.

These are derived from all the data above, shared under the
combined terms of Open Database 1.0 License and CC-BY licenses as
applicable to derived, extracted and modified data.

The 2023 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. States and equivalent entities are the primary governmental divisions of the United States. In addition to the fifty states, the Census Bureau treats the District of Columbia, Puerto Rico, and each of the Island Areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands) as the statistical equivalents of states for the purpose of data presentation.

These files add to and replace same-named files found within Submission 559 (https://gdr.openei.org/submissions/559) The files included in this submission contain all data pertinent to the methods and results of a cohesive multi-state analysis of all known potential geothermal reservoirs in sedimentary rocks in the Appalachian Basin region, ranked by their potential favorability. Favorability is quantified using three metrics: Reservoir Productivity Index for water; Reservoir Productivity Index; Reservoir Flow Capacity. The metrics are explained in the Reservoirs Methodology Memo (included in zip file). The product represents a minimum spatial extent of potential sedimentary rock geothermal reservoirs. Only natural porosity and permeability were analyzed. Shapefile and images of the spatial distributions of these reservoir quality metrics and of the uncertainty on these metrics are included as well.

UPDATE: Accompanying geologic reservoirs data may be found at: https://gdr.openei.org/submissions/881 (linked below). Contains the file components of the Reservoirs shapefile.

This database consists of a series of maps showing the maximum annually recurring wave information adjacent to 302 mileposts along Hawaii state routes on the islands of Hawaii, Maui, Molokai, Oahu and Kauai previously identified for their vulnerability to the effects of climate change as part of the Statewide Coastal Highways Project Report.

PWD represents Peak Wave Direction, from which the wave is coming, SWH represents Significant Wave Height, and PWP represents Peak Wave Period. Virtual Buoys (VB) are identified by Francis et al. (2019), and Mileposts (MP) are identified by Brandes et al. (2019). HDOT state routes and county street centerline datasets are acquired from HDOT (2017) and HOLIS, C&CH (2017). Shoreline datasets are provided by NGS (2017).

Please read ‘Description-Map of Maximum Annually Recurring Wave Information.docx’ for detailed information.

References Brandes, H., Doygun, O., Rossi, C., Francis, O., Yang, L., and Togia, H., (2019) Coastal Road Exposure Susceptibility Index (CRESI) for the State of Hawaii Statewide Coastal Highway Program Report. Department of Civil and Environmental Engineering, University of Hawai'i at Manoa, doi: 10.17632/frr3fsx3j6.2. Francis, Oceana; Yang, Linqiang; Togia, Harrison; Tumino Di Costanzo, Giannicola (2019), “Ocean Hazards Database (OHD) for the State of Hawaii Statewide Coastal Highway Program Report”, Mendeley Data, doi: 10.17632/7p3hyypmjm HDOT (State of Hawaii Department of Transportation). “StateRoutes_SDOT” [shapefile]. Scale Not Given. State Routes. Hawaii Statewide GIS Program. Retrieved from http://files.hawaii.gov/dbedt/op/gis/data/StateAndCountyRoutes.shp.zip (December 2017). HOLIS, C&CH (Honolulu Land Information System, City and County of Honolulu). “Oah_streets” [shapefile]. Scale Not Given. Oahu Street Centerlines. Hawaii Statewide GIS Program. Retrieved from http://geoportal.hawaii.gov/datasets/roads-honolulu-county (December 2017). NGS (National Geodetic Survey) (2017). National Oceanic and Atmospheric Administration (NOAA) Continually Updated Shoreline Product (CUSP). Retrieved from https://www.ngs.noaa.gov/CUSP/ (October 2017).