GeoVectors - Knowledge Graph (v1.0)
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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ftdatacite:10.5281/zenodo.4964300 2023-05-15T13:33:47+02:00 GeoVectors - Knowledge Graph (v1.0) Tempelmeier, Nicolas Gottschalk, Simon Demidova, Elena 2021 https://dx.doi.org/10.5281/zenodo.4964300 https://zenodo.org/record/4964300 unknown Zenodo https://dx.doi.org/10.5281/zenodo.4339523 Open Access Open Data Commons Open Database License v1.0 https://opendatacommons.org/licenses/odbl/1-0/ info:eu-repo/semantics/openAccess dataset Dataset 2021 ftdatacite https://doi.org/10.5281/zenodo.4964300 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 dataset was derived from an OpenStreetMap snapshot that was taken on November 10, 2020 (© OpenStreetMap contributors). 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. For further information, please visit http://geovectors.l3s.uni-hannover.de GeoVectors consists of the following subsets: Africa Africa. Tags: 10.5281/zenodo.4320881. Location: 10.5281/zenodo.4956827. Antarctica Antarctica. Tags: 10.5281/zenodo.4320869. Location: 10.5281/zenodo.4956951. Asia Asia. Tags: 10.5281/zenodo.4320895. Location: 10.5281/zenodo.4956955. Japan. Tags: 10.5281/zenodo.4320895. Location: 10.5281/zenodo.4957846. Indonesia. Tags: 10.5281/zenodo.4320895. Location: 10.5281/zenodo.4957818. Australia-Oceania Australia-Oceania. Tags: 10.5281/zenodo.4320963. Location: 10.5281/zenodo.4957176. Central-America Central-America. Tags: 10.5281/zenodo.4321010. Location: 10.5281/zenodo.4957278. Europe Europe-east. Tags: 10.5281/zenodo.4321012. Location: 10.5281/zenodo.4957475. Europe-west. Tags: 10.5281/zenodo.4321099. Location: 10.5281/zenodo.4957583. France. Tags: 10.5281/zenodo.4321153. Location: 10.5281/zenodo.4957689. Germany-nodes-relations. Tags: 10.5281/zenodo.4321406. Location: 10.5281/zenodo.4957746. Germany-ways. Tags: 10.5281/zenodo.4321420. Location: 10.5281/zenodo.4957746. Great-Britain. Tags: 10.5281/zenodo.4321175. Location: 10.5281/zenodo.4957805. Italy. Tags: 10.5281/zenodo.4321206. Location: 10.5281/zenodo.4957840. Netherlands. Tags: 10.5281/zenodo.4321252. Location: 10.5281/zenodo.4957583. Poland. Tags: 10.5281/zenodo.4321267. Location: 10.5281/zenodo.4957475. Russia. Tags: 10.5281/zenodo.4321358. Location: 10.5281/zenodo.4957903. North-America North-America. Tags: 10.5281/zenodo.4321449. Location: 10.5281/zenodo.4957873. US-Other. Tags: 10.5281/zenodo.4321762. Location: 10.5281/zenodo.4957931. US-South. Tags: 10.5281/zenodo.4321641. Location: 10.5281/zenodo.4957968. US-West. Tags: 10.5281/zenodo.4321708. Location: 10.5281/zenodo.4957931. South-America South-America. Tags: 10.5281/zenodo.4321635. Location: 10.5281/zenodo.4957911. Funding : This work was partially funded by DFG, German Research Foundation (“WorldKG", DE 2299/2-1), the Federal Ministry of Education and Research (BMBF), Germany (“Simple-ML", 01IS18054), the Federal Ministry for Economic Affairs and Energy (BMWi), Germany (“d-E-mand", 01ME19009B), and the European Commission (EU H2020, “smashHit", grant-ID 871477). Dataset Antarc* Antarctica DataCite Metadata Store (German National Library of Science and Technology) |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
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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 dataset was derived from an OpenStreetMap snapshot that was taken on November 10, 2020 (© OpenStreetMap contributors). 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. For further information, please visit http://geovectors.l3s.uni-hannover.de GeoVectors consists of the following subsets: Africa Africa. Tags: 10.5281/zenodo.4320881. Location: 10.5281/zenodo.4956827. Antarctica Antarctica. Tags: 10.5281/zenodo.4320869. Location: 10.5281/zenodo.4956951. Asia Asia. Tags: 10.5281/zenodo.4320895. Location: 10.5281/zenodo.4956955. Japan. Tags: 10.5281/zenodo.4320895. Location: 10.5281/zenodo.4957846. Indonesia. Tags: 10.5281/zenodo.4320895. Location: 10.5281/zenodo.4957818. Australia-Oceania Australia-Oceania. Tags: 10.5281/zenodo.4320963. Location: 10.5281/zenodo.4957176. Central-America Central-America. Tags: 10.5281/zenodo.4321010. Location: 10.5281/zenodo.4957278. Europe Europe-east. Tags: 10.5281/zenodo.4321012. Location: 10.5281/zenodo.4957475. Europe-west. Tags: 10.5281/zenodo.4321099. Location: 10.5281/zenodo.4957583. France. Tags: 10.5281/zenodo.4321153. Location: 10.5281/zenodo.4957689. Germany-nodes-relations. Tags: 10.5281/zenodo.4321406. Location: 10.5281/zenodo.4957746. Germany-ways. Tags: 10.5281/zenodo.4321420. Location: 10.5281/zenodo.4957746. Great-Britain. Tags: 10.5281/zenodo.4321175. Location: 10.5281/zenodo.4957805. Italy. Tags: 10.5281/zenodo.4321206. Location: 10.5281/zenodo.4957840. Netherlands. Tags: 10.5281/zenodo.4321252. Location: 10.5281/zenodo.4957583. Poland. Tags: 10.5281/zenodo.4321267. Location: 10.5281/zenodo.4957475. Russia. Tags: 10.5281/zenodo.4321358. Location: 10.5281/zenodo.4957903. North-America North-America. Tags: 10.5281/zenodo.4321449. Location: 10.5281/zenodo.4957873. US-Other. Tags: 10.5281/zenodo.4321762. Location: 10.5281/zenodo.4957931. US-South. Tags: 10.5281/zenodo.4321641. Location: 10.5281/zenodo.4957968. US-West. Tags: 10.5281/zenodo.4321708. Location: 10.5281/zenodo.4957931. South-America South-America. Tags: 10.5281/zenodo.4321635. Location: 10.5281/zenodo.4957911. Funding : This work was partially funded by DFG, German Research Foundation (“WorldKG", DE 2299/2-1), the Federal Ministry of Education and Research (BMBF), Germany (“Simple-ML", 01IS18054), the Federal Ministry for Economic Affairs and Energy (BMWi), Germany (“d-E-mand", 01ME19009B), and the European Commission (EU H2020, “smashHit", grant-ID 871477). |
format |
Dataset |
author |
Tempelmeier, Nicolas Gottschalk, Simon Demidova, Elena |
spellingShingle |
Tempelmeier, Nicolas Gottschalk, Simon Demidova, Elena GeoVectors - Knowledge Graph (v1.0) |
author_facet |
Tempelmeier, Nicolas Gottschalk, Simon Demidova, Elena |
author_sort |
Tempelmeier, Nicolas |
title |
GeoVectors - Knowledge Graph (v1.0) |
title_short |
GeoVectors - Knowledge Graph (v1.0) |
title_full |
GeoVectors - Knowledge Graph (v1.0) |
title_fullStr |
GeoVectors - Knowledge Graph (v1.0) |
title_full_unstemmed |
GeoVectors - Knowledge Graph (v1.0) |
title_sort |
geovectors - knowledge graph (v1.0) |
publisher |
Zenodo |
publishDate |
2021 |
url |
https://dx.doi.org/10.5281/zenodo.4964300 https://zenodo.org/record/4964300 |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
https://dx.doi.org/10.5281/zenodo.4339523 |
op_rights |
Open Access Open Data Commons Open Database License v1.0 https://opendatacommons.org/licenses/odbl/1-0/ info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5281/zenodo.4964300 https://doi.org/10.5281/zenodo.4339523 |
_version_ |
1766046078642159616 |