geodata data package providing geojson polygons for all the world's countries

Geojson polygons for all the world’s countries from DataHubIO

Polygons polygons for the largest administrative subdivisions in every countries

Countries layers that contains all teh countries in the world

Dataset

This dataset was created by Amir Baniasadi

Contents

High resolution, World Bank-approved administrative boundaries. Each download option (shapefile, GeoPackage, or GeoJSON format) includes Admin 0, 1, 2, Non-Determined Legal Status Areas (NDLSA), and an ocean mask. An Admin 0 line file (for visualization purposes with World Bank-specific drawing instructions) can also be found in the shapefile folder. A data dictionary and additional columns of information which can be joined to the Admin 1 and 2 files are available as separate downloads.

Also included are API endpoints for interactive maps.

If Bank staff use this data to create a map- print, web, presentations for an external audience (e.g. external web sites), etc., staff must receive legal clearance by submitting the finished map to the World Bank Cartography Unit.

To report an error in any of the admin boundary files, please raise a new issue here: https://github.com/worldbank/WB_GAD/issues and it will be considered during the next update cycle.

The United Nations Geospatial Data, or Geodata, is a worldwide geospatial dataset of the United Nations. The United Nations Geodata is provided to facilitate the preparation of cartographic materials in the United Nations includes geometry, attributes and labels to facilitate the adequate depiction and naming of geographic features for the preparation of maps in accordance with United Nations policies and practices. The geospatial dataset include polygons/areas of countries (BNDA_simplified). Please refer this page for more information.

Simple geospatial and administrative repository. This dataset is built from the Official Geographic Code of INSEE, available via their SparQL interface. ## Model There are two types of objects: - levels - areas ### Zones The file Zones {year} (json) is constructed from data extracted from the COG and contains, for all geographical scales, the following information: - uri: Entity URI in INSEE RDF graph (example: "http://id.insee.fr/geo/arrondissement/6eeefa75-7352-48ee-884f-64783b8ca290"), - name: name of the entity (example: "Lyon"), - INSEE code: INSEE code of the entity (example: "691"), - nameWithoutArticle: name without article of the entity (example: "Lyon"), - codeArticle: Entity item code (example: "0"), - type: type of entity (example: "Arrondissement"), - is_deleted: boolean indicating whether the entity has been administratively deleted (example: true), - level: level of scale of the entity (example: "fr:arrondissement"), - _id: full identifier used by data.gouv.fr (example: "fr:arrondissement:691") The Countries only zones {year} (json) file is a sample of the global Countries only zones {year} (json) file which contains only the countries. ### Levels/Levels The file contains the different possible scale levels, with the following information: - id: entity level of scale, which corresponds to the ‘level’ field in the Zones file (example: "en:region"), - label: naming the scale level (example: "French region"), - admin_level: Scale level code (example: 40), - parents: directly higher level(s) of scale (example: ["country"]) ## Construction This dataset is built from the INSEE COG via a python script available here. ## History - 30/04/2015: first version - 15/04/2016: addition of the URLs of the coats of arms/flags and an export using msgpack in order to reduce the size of the generated archive - 19/04/2016: correction version providing a finer cut of the shapes of the municipalities - 09/06/2016: correction version adding the parents for the municipalities of Corsica/DROM-COM and calculating the population for the districts - 15/06/2017: version including data from GeoHisto and using GeoIDs, integrates 2017 data (COG, OSM). - 28/08/2017: Added EPCI history from GeoHisto. - 08/05/2019: Switching to COG 2019, bug fixing, adding the "geonames" key, switching to Wikidata, cantons and iris are no longer exported - 30/11/2023: The data comes from the INSEE COG from their SparQL interface ## Archives ### Levels/Levels They make it possible to model the different known levels of the referential and their theoretical relationships. Their name is translatable. ### Zones A zone is the association of a unique identifier with a geographical polygon, a level and a name. It has less than one unique code for the level. It may have several known identifiers, which are not necessarily unique. The name is optionally translatable (ex: European Union, World) The following attributes are exported to the GeoJSON: - id: A unique identifier following the specification GeoID - code: The unique identifier for a given date of the zone for its level - level: The identifier of the level of attachment - name: The display name of the area in English (may be translated) - population: Approximate/estimated population (optional) - area: Estimated/approximate area in km2 (optional) - wikidata: The associated Wikidata node (optional) - wikipedia: A reference to Wikipedia (optional) - dbpedia: A reference to DBPedia (optional) - flag: A reference to the DBPedia flag (optional) - blazon: A reference to the DBPedia blazon (optional) - keys: a dictionary of the different codes known for this area - parents: an unordered list of the identifiers of the different known parents - ancestors: the list of possible ancestors - successful: the list of possible successors - validity: a period of validity (object with the attributes ‘start’/‘end’) (optional) ## Construction This dataset is built with the tool GeoZones whose code is published on Github. You can find the detail of French specificities on the repository. ## Possible future improvements ### Fields - Overall weight = f(population, area, level) ### Deliverables - Various clarifications - Localized JSON (in English only for now) - Translations in JSON (as a hard alternative to the current PO/MO format) - Level statistics (number of zones, coverage of attributes...)

This dataset provides the following levels of administrative boundaries for Monaco: Country (Pays), Administrative districts (Quartiers administratifs) in GeoJSON and Shape file formats, rendered in the industry-standard coordinate reference system, EPSG:4326 (WGS84).

This dataset contains data about the number of response centres (hospitals, fire stations, police offices and railway stations) in every city in Portugal. It is compound of a GeoJSON file with geographic boundaries of the entire country, a GeoJSON file containing the geometry and response centres counting for each city, an OpenStreetMap (OSM) file for each city and a CSV table that summarizes all the data.

The zip file contains Health region (adm1) and districts boundaries (adm2) for DRC in shapefile and GeoJSON format. These datasets can be found in the WHO Ebola open data platform: https://ebolaoutbreak2018-who.opendata.arcgis.com

Dataset is implementing one of the tasks of the “Flora Altaica” Project (http://altaiflora.asu.ru) to monitor rare and endemic plant species that grow in the Altai Mountainous Country using biodiversity informatics. The obligatory basis for the entry of the taxon into the Dataset "Red Book of Altai Mountain Country (plants)", as well as for the currently available ones, is the presence of precise geo-referencing. The empirical background to the dataset is the material of Herbarium ALTB (Barnaul), with more than 450 thousand specimens. It is planned to update regularly the dataset "Red Book of Altai Mountain Country (plants)" with information on new locations and taxa from the list in case they appear in the collection of Herbarium ALTB. The AMC's borders are defined according to 19 botanical and geographical areas revealed by R. V. Kamelin in the first volume of “Flora Altaica” (Flora Altaica, V. 1, 2005. The team of authors (Ed.) R.V. Kamelyn, Barnaul, 340 p.). The AMC polygon (GeoJSON) for the required taxon research is available in the section “AMC Map” of the project “Flora Altaica" on the website (http://altaiflora.asu.ru MAP). GeoJSON polygon can be implemented in "Location" item of "Occurrence" section of GBIF.

Dataset provides the most complete list of rare and some endemic plant species of transboundary territory of the Altai Mountainous Country (AMC) within Russia, Kazakhstan, China and Mongolia. The AMC's borders are defined according to 19 botanical and geographical areas revealed by R. V. Kamelin in the first volume of “Flora Altaica” (Flora Altaica, V. 1, 2005. The team of authors (Ed.) R.V. Kamelyn, Barnaul, 340 p.). The AMC polygon (GeoJSON) for the required taxon research is available in the section “AMC Map” of the project “Flora Altaica" on the website (http://altaiflora.asu.ru > AMC Map). GeoJSON polygon can be implemented in "Location" item of "Occurrence" section of GBIF.

This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2.

Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database www.geoboundaries.org is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.

Main nodes and major lines of the electricity transmission network of Saudi Arabia. Interconnection lines with neighboring countries included. The properties for nodes are "name" and "node type" (city, town, plant, dam...). The properties for lines are the "transmission power" in kV (e.g. 400), the "type of line" (single, double...), the linked nodes (identified by the nodes names) and, for international interconnections, the "interconnection" property gathers the two linked countries identified by name. The format is GeoJSON, nodes are displayed as points and lines as lines. Data comes from the Arab Union of Electricity and country utility (SEC).

Main nodes and major lines of the electricity transmission network of Syria. Interconnection lines with neighboring countries included. The properties for nodes are "name" and "node type" (city, town, plant, dam...). The properties for lines are the "transmission power" in kV (e.g. 400), the "type of line" (single, double...), the linked nodes (identified by the nodes names) and, for international interconnections, the "interconnection" property gathers the two linked countries identified by name. The format is GeoJSON, nodes are displayed as points and lines as lines. Data comes from the Arab Union of Electricity.

Polygon Shapefile, Uganda Regions (date unknown) Proj: EPSG 4326 (unprojected): Source: http://www.maplibrary.org/library/stacks/Africa/Uganda/index.htm Description: Four regions of Uganda

List of the world's major cities (above 15,000 inhabitants)

Main nodes and major lines of the electricity transmission network of Iraq. Interconnection lines with neighboring countries included.

The properties for nodes are "name" and "node type" (city, town, plant, dam...). The properties for lines are the "transmission power" in kV (e.g. 400), the "type of line" (single, double...), the linked nodes (identified by the nodes names) and, for international interconnections, the "interconnection" property gathers the two linked countries identified by name. The format is GeoJSON, nodes are displayed as points and lines as lines.

Data comes from the Arab Union of Electricity and Iraq Ministry of Electricity.

Main nodes and major lines of the electricity transmission network of Libya. Interconnection lines with neighboring countries included.

The properties for nodes are "name" and "node type" (city, town, plant, dam...). The properties for lines are the "transmission power" in kV (e.g. 400), the "type of line" (single, double...), the linked nodes (identified by the nodes names) and, for international interconnections, the "interconnection" property gathers the two linked countries identified by name. The format is GeoJSON, nodes are displayed as points and lines as lines.

Data comes from the Arab Union of Electricity and country utility (GECOL).