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Accessing scientific data through knowledge graphs with Ontop
In this tutorial, we learn how to set up and exploit the virtual knowledge graph (VKG) approach to access data stored in relational legacy systems and to enrich such data with domain knowledge coming from different heterogeneous (biomedical) resources. The VKG approach is based on an ontology that d...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8515008/ https://www.ncbi.nlm.nih.gov/pubmed/34693372 http://dx.doi.org/10.1016/j.patter.2021.100346 |
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author | Calvanese, Diego Lanti, Davide Mendes De Farias, Tarcisio Mosca, Alessandro Xiao, Guohui |
author_facet | Calvanese, Diego Lanti, Davide Mendes De Farias, Tarcisio Mosca, Alessandro Xiao, Guohui |
author_sort | Calvanese, Diego |
collection | PubMed |
description | In this tutorial, we learn how to set up and exploit the virtual knowledge graph (VKG) approach to access data stored in relational legacy systems and to enrich such data with domain knowledge coming from different heterogeneous (biomedical) resources. The VKG approach is based on an ontology that describes a domain of interest in terms of a vocabulary familiar to the user and exposes a high-level conceptual view of the data. Users can access the data by exploiting the conceptual view, and in this way they do not need to be aware of low-level storage details. They can easily integrate ontologies coming from different sources and can obtain richer answers thanks to the interaction between data and domain knowledge. |
format | Online Article Text |
id | pubmed-8515008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-85150082021-10-21 Accessing scientific data through knowledge graphs with Ontop Calvanese, Diego Lanti, Davide Mendes De Farias, Tarcisio Mosca, Alessandro Xiao, Guohui Patterns (N Y) Tutorial In this tutorial, we learn how to set up and exploit the virtual knowledge graph (VKG) approach to access data stored in relational legacy systems and to enrich such data with domain knowledge coming from different heterogeneous (biomedical) resources. The VKG approach is based on an ontology that describes a domain of interest in terms of a vocabulary familiar to the user and exposes a high-level conceptual view of the data. Users can access the data by exploiting the conceptual view, and in this way they do not need to be aware of low-level storage details. They can easily integrate ontologies coming from different sources and can obtain richer answers thanks to the interaction between data and domain knowledge. Elsevier 2021-10-08 /pmc/articles/PMC8515008/ /pubmed/34693372 http://dx.doi.org/10.1016/j.patter.2021.100346 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Tutorial Calvanese, Diego Lanti, Davide Mendes De Farias, Tarcisio Mosca, Alessandro Xiao, Guohui Accessing scientific data through knowledge graphs with Ontop |
title | Accessing scientific data through knowledge graphs with Ontop |
title_full | Accessing scientific data through knowledge graphs with Ontop |
title_fullStr | Accessing scientific data through knowledge graphs with Ontop |
title_full_unstemmed | Accessing scientific data through knowledge graphs with Ontop |
title_short | Accessing scientific data through knowledge graphs with Ontop |
title_sort | accessing scientific data through knowledge graphs with ontop |
topic | Tutorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8515008/ https://www.ncbi.nlm.nih.gov/pubmed/34693372 http://dx.doi.org/10.1016/j.patter.2021.100346 |
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