GeoVectors - Knowledge Graph

The GeoVectors corpus is a comprehensive large-scale linked open corpus of OpenStreetMap (https://www.openstreetmap.org/) entity embeddings that provides latent representations of over 980 million entities. The GeoVectors capture the semantic and geographic dimensions of OpenStreetMap entities and m...

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Main Authors: Tempelmeier, Nicolas, Gottschalk, Simon, Demidova, Elena
Format: Dataset
Language:unknown
Published: Zenodo 2020
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.4339524
https://zenodo.org/record/4339524
id ftdatacite:10.5281/zenodo.4339524
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spelling ftdatacite:10.5281/zenodo.4339524 2023-05-15T13:51:03+02:00 GeoVectors - Knowledge Graph Tempelmeier, Nicolas Gottschalk, Simon Demidova, Elena 2020 https://dx.doi.org/10.5281/zenodo.4339524 https://zenodo.org/record/4339524 unknown Zenodo https://dx.doi.org/10.5281/zenodo.4339523 Open Access ODC Open Database License v1.0 http://www.opendatacommons.org/licenses/odbl/1.0/ odbl-1.0 info:eu-repo/semantics/openAccess dataset Dataset 2020 ftdatacite https://doi.org/10.5281/zenodo.4339524 https://doi.org/10.5281/zenodo.4339523 2021-11-05T12:55:41Z The GeoVectors corpus is a comprehensive large-scale linked open corpus of OpenStreetMap (https://www.openstreetmap.org/) entity embeddings that provides latent representations of over 980 million entities. The GeoVectors capture the semantic and geographic dimensions of OpenStreetMap entities and make them directly accessible to machine learning applications. The "-tags" datasets provide embeddings that capture the semantic dimension of OpenStreetMap entities. The "-location" datasets provide the geographic dimension. This repository contains the GeoVectors Knowledge graph that models metadata of the embeddings and links to well-established sources such as Wikidata and DBpedia. The GeoVectors corpus is partitioned into regional subsets. The GeoVectors knowledge graph can be used to identify the subset that contains a particular linked entity. GeoVectors consists of the following subsets: Africa Africa. Tags: 10.5281/zenodo.4320881. Location: 10.5281/zenodo.4322486. Antarctica Antarctica. Tags: 10.5281/zenodo.4320869. Location: 10.5281/zenodo.4322563. Asia Asia. Tags: 10.5281/zenodo.4320895. Location: 10.5281/zenodo.4322859. Japan. Tags: 10.5281/zenodo.4320895. Location: 10.5281/zenodo.4323105. Indonesia. Tags: 10.5281/zenodo.4320895. Location: 10.5281/zenodo.4323074. Australia-Oceania Australia-Oceania. Tags: 10.5281/zenodo.4320963. Location: 10.5281/zenodo.4322931. Central-America Central-America. Tags: 10.5281/zenodo.4321010. Location: 10.5281/zenodo.4322935. Europe Europe-East. Tags: 10.5281/zenodo.4321012. Location: 10.5281/zenodo.4322948. Europe-West. Tags: 10.5281/zenodo.4321099. Location: 10.5281/zenodo.4322972. France. Tags: 10.5281/zenodo.4321153. Location: 10.5281/zenodo.4322994. Germany (Nodes, Relations). Tags: 10.5281/zenodo.4321406. Location: 10.5281/zenodo.4323008. Germany (Ways). Tags: 10.5281/zenodo.4321420. Location: 10.5281/zenodo.4323008. Great-Britain. Tags: 10.5281/zenodo.4321175. Location: 10.5281/zenodo.4323020. Italy. Tags: 10.5281/zenodo.4321206. Location: 10.5281/zenodo.4323088. Netherlands. Tags: 10.5281/zenodo.4321252. Location: 10.5281/zenodo.4322972. Poland. Tags: 10.5281/zenodo.4321267. Location: 10.5281/zenodo.4322948. Russia. Tags: 10.5281/zenodo.4321358. Location: 10.5281/zenodo.4323185. North-America North-America. Tags: 10.5281/zenodo.4321449. Location: 10.5281/zenodo.4323162. US-other. Tags: 10.5281/zenodo.4321762. Location: 10.5281/zenodo.4326975. US-south. Tags: 10.5281/zenodo.4321641. Location: 10.5281/zenodo.4326931. US-west. Tags: 10.5281/zenodo.4321708. Location: 10.5281/zenodo.4326975. South-America South-America. Tags: 10.5281/zenodo.4321635. Location: 10.5281/zenodo.4323263. Dataset Antarc* Antarctica DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
description The GeoVectors corpus is a comprehensive large-scale linked open corpus of OpenStreetMap (https://www.openstreetmap.org/) entity embeddings that provides latent representations of over 980 million entities. The GeoVectors capture the semantic and geographic dimensions of OpenStreetMap entities and make them directly accessible to machine learning applications. The "-tags" datasets provide embeddings that capture the semantic dimension of OpenStreetMap entities. The "-location" datasets provide the geographic dimension. This repository contains the GeoVectors Knowledge graph that models metadata of the embeddings and links to well-established sources such as Wikidata and DBpedia. The GeoVectors corpus is partitioned into regional subsets. The GeoVectors knowledge graph can be used to identify the subset that contains a particular linked entity. GeoVectors consists of the following subsets: Africa Africa. Tags: 10.5281/zenodo.4320881. Location: 10.5281/zenodo.4322486. Antarctica Antarctica. Tags: 10.5281/zenodo.4320869. Location: 10.5281/zenodo.4322563. Asia Asia. Tags: 10.5281/zenodo.4320895. Location: 10.5281/zenodo.4322859. Japan. Tags: 10.5281/zenodo.4320895. Location: 10.5281/zenodo.4323105. Indonesia. Tags: 10.5281/zenodo.4320895. Location: 10.5281/zenodo.4323074. Australia-Oceania Australia-Oceania. Tags: 10.5281/zenodo.4320963. Location: 10.5281/zenodo.4322931. Central-America Central-America. Tags: 10.5281/zenodo.4321010. Location: 10.5281/zenodo.4322935. Europe Europe-East. Tags: 10.5281/zenodo.4321012. Location: 10.5281/zenodo.4322948. Europe-West. Tags: 10.5281/zenodo.4321099. Location: 10.5281/zenodo.4322972. France. Tags: 10.5281/zenodo.4321153. Location: 10.5281/zenodo.4322994. Germany (Nodes, Relations). Tags: 10.5281/zenodo.4321406. Location: 10.5281/zenodo.4323008. Germany (Ways). Tags: 10.5281/zenodo.4321420. Location: 10.5281/zenodo.4323008. Great-Britain. Tags: 10.5281/zenodo.4321175. Location: 10.5281/zenodo.4323020. Italy. Tags: 10.5281/zenodo.4321206. Location: 10.5281/zenodo.4323088. Netherlands. Tags: 10.5281/zenodo.4321252. Location: 10.5281/zenodo.4322972. Poland. Tags: 10.5281/zenodo.4321267. Location: 10.5281/zenodo.4322948. Russia. Tags: 10.5281/zenodo.4321358. Location: 10.5281/zenodo.4323185. North-America North-America. Tags: 10.5281/zenodo.4321449. Location: 10.5281/zenodo.4323162. US-other. Tags: 10.5281/zenodo.4321762. Location: 10.5281/zenodo.4326975. US-south. Tags: 10.5281/zenodo.4321641. Location: 10.5281/zenodo.4326931. US-west. Tags: 10.5281/zenodo.4321708. Location: 10.5281/zenodo.4326975. South-America South-America. Tags: 10.5281/zenodo.4321635. Location: 10.5281/zenodo.4323263.
format Dataset
author Tempelmeier, Nicolas
Gottschalk, Simon
Demidova, Elena
spellingShingle Tempelmeier, Nicolas
Gottschalk, Simon
Demidova, Elena
GeoVectors - Knowledge Graph
author_facet Tempelmeier, Nicolas
Gottschalk, Simon
Demidova, Elena
author_sort Tempelmeier, Nicolas
title GeoVectors - Knowledge Graph
title_short GeoVectors - Knowledge Graph
title_full GeoVectors - Knowledge Graph
title_fullStr GeoVectors - Knowledge Graph
title_full_unstemmed GeoVectors - Knowledge Graph
title_sort geovectors - knowledge graph
publisher Zenodo
publishDate 2020
url https://dx.doi.org/10.5281/zenodo.4339524
https://zenodo.org/record/4339524
genre Antarc*
Antarctica
genre_facet Antarc*
Antarctica
op_relation https://dx.doi.org/10.5281/zenodo.4339523
op_rights Open Access
ODC Open Database License v1.0
http://www.opendatacommons.org/licenses/odbl/1.0/
odbl-1.0
info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.5281/zenodo.4339524
https://doi.org/10.5281/zenodo.4339523
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