GeoVectors-Antarctica-location (v1.0)

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 en...

Full description

Bibliographic Details
Main Authors: Tempelmeier, Nicolas, Gottschalk, Simon, Demidova, Elena
Format: Other/Unknown Material
Language:unknown
Published: Zenodo 2021
Subjects:
Online Access:https://doi.org/10.5281/zenodo.4956951
id ftzenodo:oai:zenodo.org:4956951
record_format openpolar
spelling ftzenodo:oai:zenodo.org:4956951 2024-09-15T17:43:05+00:00 GeoVectors-Antarctica-location (v1.0) Tempelmeier, Nicolas Gottschalk, Simon Demidova, Elena 2021-06-15 https://doi.org/10.5281/zenodo.4956951 unknown Zenodo https://doi.org/10.5281/zenodo.4956950 https://doi.org/10.5281/zenodo.4956951 oai:zenodo.org:4956951 info:eu-repo/semantics/openAccess ODC Open Database License v1.0 http://www.opendatacommons.org/licenses/odbl/1.0/ info:eu-repo/semantics/other 2021 ftzenodo https://doi.org/10.5281/zenodo.495695110.5281/zenodo.4956950 2024-07-26T19:57:45Z 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. Contents This dataset was derived from an OpenStreetMap snapshot that was taken on November 10,2020 (© OpenStreetMap contributors). We provide the GeoVectors in region-specific subsets. This subset contains location-embeddings for the region "Antarctica" including the following countries: Antarctica File format The embeddings are provided in the tab-separated values(tsv) format. Each row contains the embedding of a single OpenStreetMap entity. The first column contains the OpenStreetMap type and the second column contains the OpenStreetMap id of the respective entity. The type can either be node (n), way (w), or relation (r). The remaining columns represent the dimensions of the embedding space. (See also header.tsv) Further information: For further information, please visit http://geovectors.l3s.uni-hannover.de 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). Other/Unknown Material Antarc* Antarctica Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
description 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. Contents This dataset was derived from an OpenStreetMap snapshot that was taken on November 10,2020 (© OpenStreetMap contributors). We provide the GeoVectors in region-specific subsets. This subset contains location-embeddings for the region "Antarctica" including the following countries: Antarctica File format The embeddings are provided in the tab-separated values(tsv) format. Each row contains the embedding of a single OpenStreetMap entity. The first column contains the OpenStreetMap type and the second column contains the OpenStreetMap id of the respective entity. The type can either be node (n), way (w), or relation (r). The remaining columns represent the dimensions of the embedding space. (See also header.tsv) Further information: For further information, please visit http://geovectors.l3s.uni-hannover.de 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 Other/Unknown Material
author Tempelmeier, Nicolas
Gottschalk, Simon
Demidova, Elena
spellingShingle Tempelmeier, Nicolas
Gottschalk, Simon
Demidova, Elena
GeoVectors-Antarctica-location (v1.0)
author_facet Tempelmeier, Nicolas
Gottschalk, Simon
Demidova, Elena
author_sort Tempelmeier, Nicolas
title GeoVectors-Antarctica-location (v1.0)
title_short GeoVectors-Antarctica-location (v1.0)
title_full GeoVectors-Antarctica-location (v1.0)
title_fullStr GeoVectors-Antarctica-location (v1.0)
title_full_unstemmed GeoVectors-Antarctica-location (v1.0)
title_sort geovectors-antarctica-location (v1.0)
publisher Zenodo
publishDate 2021
url https://doi.org/10.5281/zenodo.4956951
genre Antarc*
Antarctica
genre_facet Antarc*
Antarctica
op_relation https://doi.org/10.5281/zenodo.4956950
https://doi.org/10.5281/zenodo.4956951
oai:zenodo.org:4956951
op_rights info:eu-repo/semantics/openAccess
ODC Open Database License v1.0
http://www.opendatacommons.org/licenses/odbl/1.0/
op_doi https://doi.org/10.5281/zenodo.495695110.5281/zenodo.4956950
_version_ 1810489915385839616