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

World Countries Generalized represents generalized boundaries for the countries of the world as of August 2022. The generalized political boundaries improve draw performance and effectiveness at a global or continental level. This layer is best viewed out beyond a scale of 1:5,000,000.This layer's geography was developed by Esri and sourced from Garmin International, Inc., the U.S. Central Intelligence Agency (The World Factbook), and the National Geographic Society for use as a world basemap. It is updated annually as country names or significant borders change.

Référentiel géospatial et administratif simple. Ce jeu de données est construit à partir du Code Officiel Géographique de l'INSEE, disponible via leur interface SparQL. Modèle Il y a deux types d'objets: les niveaux les zones Zones Le fichier Zones {année} (json) est construit à partir des données extraites du COG, et contient, pour toutes les échelles géographiques, les informations suivantes : uri : URI de l'entité dans le graphe RDF de l'INSEE (exemple : "http://id.insee.fr/geo/arrondissement/6eeefa75-7352-48ee-884f-64783b8ca290"), nom : nom de l'entité (exemple : "Lyon"), codeINSEE : code INSEE de l'entité (exemple : "691"), nomSansArticle : nom sans article de l'éntité (exemple : "Lyon"), codeArticle : code de l'article de l'entité (exemple : "0"), type : type de l'entité (exemple : "Arrondissement"), is_deleted : booléen indiquant si l'entité a été administrativement supprimée (exemple : true), level : niveau d'échelle de l'entité (exemple : "fr:arrondissement"), _id : identifiant complet utilisé par data.gouv.fr (exemple : "fr:arrondissement:691") Le fichier Zones pays uniquement {année} (json) est un échantillon du fichier global Zones {année} (json) qui ne contient que les pays. Niveaux/Levels Le fichier contient les différents niveaux d'échelles possible, avec les informations suivantes : id : niveau d'échelle de l'entité, qui correspond au champ level du fichire Zones (exemple : "fr:region"), label : appellation du niveau d'échelle (exemple : "French region"), admin_level : code du niveau d'échelle (exemple : 40), parents : niveau(x) d'échelle directement supérieur(s) (exemple : ["country"]) Construction Ce jeu de données est construit à partir du COG de l'INSEE via un script python disponible ici. Historique 30/04/2015 : première version 15/04/2016 : ajout des URL des blasons/drapeaux ainsi qu'un export utilisant msgpack afin de réduire la taille de l'archive générée 19/04/2016 : version de correction fournissant un découpage plus fin des formes des communes 09/06/2016 : version de correction ajoutant les parents pour les communes de Corse/DROM-COM et calculant la population pour les districts 15/06/2017 : version incluant les données issues de GeoHisto et utilisant des GeoIDs, intègre les données 2017 (COG, OSM). 28/08/2017 : Ajout de l'historique des EPCIs issue de GeoHisto. 08/05/2019 : Passage au COG 2019, correction de bugs, ajout de la clé geonames, passage à Wikidata, les cantons et les iris ne sont plus exportés 30/11/2023 : Les données sont issues du COG de l'INSEE à partir de leur interface SparQL Archives Niveaux/Levels Ils permettent de modéliser les différents niveaux connus du référentiel et leur relations théoriques. Leur nom est traductible. Zones Une zone est l'association d'un identifiant unique à polygone géographique, un niveau et un nom. Il a moins un code unique pour le niveau. Il peut avoir plusieurs identifiants connus, qui ne sont pas nécessairement uniques. Le nom est optionnellement traductible (ex: Union européenne, Monde) Les attributs suivant sont exportés dans le GeoJSON: id : Un identifiant unique suivant la spécification GeoID code : L'identifiant unique pour une date donnée de la zone pour son niveau level : L'identifiant du niveau de rattachement name : Le nom d'affichage de la zone en anglais (peut-être traduit) population : La population approximative/estimée (optionnel) area : L'aire estimée/approximative en km2 (optionnel) wikidata : Le noeud Wikidata associé (optionnel) wikipedia : Une référence vers Wikipedia (optionnel) dbpedia : Une référence vers DBPedia (optionnel) flag : Une référence vers le drapeau DBPedia (optionnel) blazon : Une référence vers le blazon DBPedia (optionnel) keys : un dictionnaire des différents code connus pour cette zone parents : une liste non-ordonnée des identifiants des différents parents connus ancestors : la liste des éventuels ancêtres successors : la liste des éventuels successeurs validity: une période de validité (objet ayant les attributs start/end) (optionnel) Construction Ce jeu de données est construit avec l'outil GeoZones dont le code est publié sur Github. Vous pouvez retrouver le détail des spécificités françaises sur le dépôt. Améliorations futures possibles Champs Poids global = f(population, area, level) Livrables Différentes précisions JSON localisés (en anglais seulement pour l'instant) Traductions en JSON (comme alternative dur format PO/MO actuel) Statistiques des niveaux (nombre de zones, couverture des attributs...)

World Bank-approved administrative boundaries (Admin 0) (and polygons) including international boundaries, disputed areas, coastlines, and lakes. Boundaries are available as an ESRI GeoDatabase, in GeoJSON, a shapefile and API endpoints for interactive maps.

NATO Country members. Data retrieved from https://www.nato.int/cps/en/natohq/topics_52044.htm NATO's member countries website

HitHorizons Manufacturing Company Data API gives access to aggregated firmographic data on 4,289,762 manufacturing companies from the whole of Europe and beyond.

Company registration data: company name national identifier and its type registered address: street, postal code, city, state / province, country business activity: SIC code, local activity code with classification system year of establishment company type location type

Sales and number of employees data: sales in EUR, USD and local currency (with local currency code) total number of employees sales and number of employees accuracy local number of employees (in case of multiple branches) companies’ sales and number of employees market position compared to other companies in a country / industry / region

Industry data: size of the whole industry size of all companies operating within a particular SIC code benchmarking within a particular country or industry regional benchmarking (EU 27, state / province)

Contact details: company website company email domain (without person’s name)

Invoicing details available for selected countries: company name company address company VAT number

Context

This data set is as part of Data Science for Good : Kiva Crowdfunding

Content

The data set consists of HDI, GDI, population, Education, Health related data. New data set consists of countries boundary in Geojson format helpful for Geo spatial analysis.

Acknowledgements

The data set is downloaded from United nation development program site. Source
Geojson Sourse

Inspiration

Some interesting analysis which could be done using the dataset are

• Visual representation of different indicators at different countries of the world
• How Kiva loans are distributed based on the economic / social / other indicators.?

Geolocet's POI Data spans the entire European continent, offering a wealth of information about Points of Interest in all countries. The extensive database covers a wide spectrum of sectors, providing valuable insights into the retail landscape, healthcare facilities, educational institutions, and much more. Whether seeking insights into markets, healthcare services, or educational access, Geolocet's POI data offers access to comprehensive information.

🔍 Uncover the Essence of Localities

Geolocet's POI Data allows exploration into the unique characteristics of various localities. With information available for more than 2,500 types of Points of Interest (POIs), including businesses, services, and amenities within specific regions, Geolocet provides valuable aggregated insights. Alternatively, for those seeking precise locations, Geolocet can provide the exact coordinates of individual POIs. This granularity offers the flexibility to craft insightful profiles of local communities or pinpoint specific POIs, aiding in tailored strategies and decisions for specific areas.

🌍 Customizable Data Solutions

At Geolocet, we recognize the significance of tailored solutions, which is why our POI Data is entirely customizable to meet your specific requirements. Whether you need data for a single region, or multiple countries, Geolocet's flexible data solutions empower you to select and acquire precisely the information you need.

Tailored Selection: Our platform allows users to choose the sectors and geographic regions that align most closely with their objectives.

Preferred Formats: Data can be received in your preferred formats, whether it's Shapefile, GeoJSON, or any other compatible format.

Moreover, we provide two distinct lists of available attributes to cater to your diverse data needs:

For Customers Requiring Points Data: - ID - Name - Category - Location Latitude - Location Longitude - Address (available for 50% of records) - Phone Number - Email Address - Website - Opening Hours - Brand - Operator - Wheelchair Accessibility - Uber Grid Cell IDs

Please note that data availability within the above list of attributes may vary depending on the POI category.

For Customers Needing Aggregated Data:

• ID of the Area
• Name of the Area
• Number of Clothing Stores
• Number of Restaurants
• Number of Cafes
• Number of Bars
• Number of Cinemas
• Number of Schools
• Number of Universities
• Number of Hospitals

It's important to emphasize that the attributes listed for the Aggregated datasets serve as examples. Geolocet offers complete flexibility, allowing you to customize attributes to suit your specific needs.

Reach out to Geolocet today to explore how our POI Data can enhance your decision-making processes and provide invaluable insights for your success.

🔄 Regular Data Updates

To maintain current and relevant insights, Geolocet's POI data undergoes regular updates. Our subscription models provide access to the latest information, enabling users to stay ahead in analyses and strategies. Recognizing the importance of up-to-date data in today's fast-paced world, Geolocet supports ongoing data needs.

🌐 Integration Potential

Geolocet's POI Data seamlessly integrates with other data offerings, including Administrative Boundaries Spatial Data and Demographic Data. This integration enriches insights and provides a holistic understanding of regions. Combining POI data with administrative boundaries and demographic information empowers data-driven decisions that consider the broader context.

🔍 Craft Informed Strategies

Geolocet's POI Data goes beyond numbers, uncovering the essence of each locality and understanding its unique characteristics. Whether in retail, healthcare, education, or any other sector, the data equips users with the insights needed to craft informed strategies, optimize resource allocation, and make decisions that resonate with the target audiences.

🔍 Customized Data Solutions with DaaS

Geolocet's Data as a Service (DaaS) offers flexibility tailored to needs. The transparent pricing model ensures cost-efficiency, allowing payment solely for the required data. Whether a startup is exploring a local market or a multinational corporation is analyzing multiple regions, Geolocet provides solutions that align with those objectives.

Contact Geolocet today to explore how the POI Data can elevate decision-making processes and provide valuable insights for success in those endeavors.

Country, regional and world GDP in current US Dollars ($). Regional means collections of countries e.g. Europe & Central Asia. Data is sourced from the World Bank and turned into a standard normalized CSV.

HitHorizons Newly Established Companies Dataset gives access to aggregated firmographic data on 80M+ companies from the whole of Europe and beyond.

Company registration data: company name national identifier and its type registered address: street, postal code, city, state / province, country business activity: SIC code, local activity code with classification system year of establishment company type location type

Sales and number of employees data: sales in EUR, USD and local currency (with local currency code) total number of employees sales and number of employees accuracy local number of employees (in case of multiple branches) companies’ sales and number of employees market position compared to other companies in a country / industry / region

Industry data: size of the whole industry size of all companies operating within a particular SIC code benchmarking within a particular country or industry regional benchmarking (EU 27, state / province)

Contact details: company website company email domain (without person’s name)

Invoicing details available for selected countries: company name company address company VAT number

This map presents transportation data, including highways, roads, railroads, and airports for the world.

The map was developed by Esri using Esri highway data; Garmin basemap layers; HERE street data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and select countries in Africa. Data for Pacific Island nations and the remaining countries of Africa was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.

Dataset includes various regional-scale spatial data layers in geojson format.

This dataset provides the following levels of administrative boundaries for Andorra: Country, Communes (Parròquies) in GeoJSON and Shape file formats, rendered in the industry-standard coordinate reference system, EPSG:4326 (WGS84).

HitHorizons Employee Data API gives access to aggregated company data on 80M+ companies from the whole of Europe and beyond.

Company registration data: company name national identifier and its type registered address: street, postal code, city, state / province, country business activity: SIC code, local activity code with classification system year of establishment company type location type

Sales and number of employees data: sales in EUR, USD and local currency (with local currency code) total number of employees sales and number of employees accuracy local number of employees (in case of multiple branches) companies’ sales and number of employees market position compared to other companies in a country / industry / region

Industry data: size of the whole industry size of all companies operating within a particular SIC code benchmarking within a particular country or industry regional benchmarking (EU 27, state / province)

Contact details: company website company email domain (without person’s name)

Invoicing details available for selected countries: company name company address company VAT number

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 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. 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 boundaries for counties and equivalent entities are as of January 1, 2017, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

Company Financial API gives access to aggregated company financial data on 80M+ companies from the whole of Europe and beyond.

Company registration data: company name national identifier and its type registered address: street, postal code, city, state / province, country business activity: SIC code, local activity code with classification system year of establishment company type location type

Sales and number of employees data: sales in EUR, USD and local currency (with local currency code) total number of employees sales and number of employees accuracy local number of employees (in case of multiple branches) companies’ sales and number of employees market position compared to other companies in a country / industry / region

Industry data: size of the whole industry size of all companies operating within a particular SIC code benchmarking within a particular country or industry regional benchmarking (EU 27, state / province)

Contact details: company website company email domain (without person’s name)

Invoicing details available for selected countries: company name company address company VAT number

Egypt administrative level 0-3 boundaries (COD-AB) dataset.

The date that these administrative boundaries were established is unknown.

NOTE: See COD-PS caveats about one feature name. Age disaggregation unavailable.

This COD-AB was most recently reviewed for accuracy and necessary changes in December 2024. The COD-AB does not require any update.

Sourced from Central Agency for Public Mobilization and Statistics (CAPMAS)

Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID.

This COD-AB is suitable for database or GIS linkage to the Egypt COD-PS.

No edge-matched (COD-EM) version of this COD-AB has yet been prepared.

Please see the COD Portal.

Administrative level 1 contains 27 feature(s). The normal administrative level 1 feature type is ""Governorate"".

Administrative level 2 contains 365 feature(s). The normal administrative level 2 feature type is ""Region"".

Administrative level 3 contains 5,716 feature(s). The normal administrative level 3 feature type is ""currently not known"".

Recommended cartographic projection: Africa Albers Equal Area Conic

This metadata was last updated on January 9, 2025.

Interconnection of the Spanish electricity transmission network with Morocco. 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 (ONE, Morocco).

Abstract

Tables containing public GeoJSON data for country boundaries, groundwater basins and aerial survey flightlines