GeoVectors-Antarctica-location (v0.1)

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 similarities of OpenStreetMap...

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Bibliographic Details
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.4322563
https://zenodo.org/record/4322563
id ftdatacite:10.5281/zenodo.4322563
record_format openpolar
spelling ftdatacite:10.5281/zenodo.4322563 2023-05-15T13:55:44+02:00 GeoVectors-Antarctica-location (v0.1) Tempelmeier, Nicolas Gottschalk, Simon Demidova, Elena 2020 https://dx.doi.org/10.5281/zenodo.4322563 https://zenodo.org/record/4322563 unknown Zenodo https://dx.doi.org/10.5281/zenodo.4322562 Open Access Open Data Commons Open Database License v1.0 https://opendatacommons.org/licenses/odbl/1-0/ info:eu-repo/semantics/openAccess dataset Dataset 2020 ftdatacite https://doi.org/10.5281/zenodo.4322563 https://doi.org/10.5281/zenodo.4322562 2021-11-05T12:55:41Z 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 similarities of OpenStreetMap entities and make them directly accessible to machine learning applications. The "-tags" datasets provide embeddings that capture the semantic similarities of OpenStreetMap entities. The "-location" datasets provide the geographic similarities. 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). 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 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 similarities of OpenStreetMap entities and make them directly accessible to machine learning applications. The "-tags" datasets provide embeddings that capture the semantic similarities of OpenStreetMap entities. The "-location" datasets provide the geographic similarities. 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 Dataset
author Tempelmeier, Nicolas
Gottschalk, Simon
Demidova, Elena
spellingShingle Tempelmeier, Nicolas
Gottschalk, Simon
Demidova, Elena
GeoVectors-Antarctica-location (v0.1)
author_facet Tempelmeier, Nicolas
Gottschalk, Simon
Demidova, Elena
author_sort Tempelmeier, Nicolas
title GeoVectors-Antarctica-location (v0.1)
title_short GeoVectors-Antarctica-location (v0.1)
title_full GeoVectors-Antarctica-location (v0.1)
title_fullStr GeoVectors-Antarctica-location (v0.1)
title_full_unstemmed GeoVectors-Antarctica-location (v0.1)
title_sort geovectors-antarctica-location (v0.1)
publisher Zenodo
publishDate 2020
url https://dx.doi.org/10.5281/zenodo.4322563
https://zenodo.org/record/4322563
genre Antarc*
Antarctica
genre_facet Antarc*
Antarctica
op_relation https://dx.doi.org/10.5281/zenodo.4322562
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.4322563
https://doi.org/10.5281/zenodo.4322562
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