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Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets
The majority of available datasets in open government data are statistical. They are widely published by various governments to be used by the public and data consumers. However, most open government data portals do not provide the five-star Linked Data standard datasets. The published datasets are...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10111831/ https://www.ncbi.nlm.nih.gov/pubmed/37072859 http://dx.doi.org/10.1186/s13326-023-00284-w |
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author | Rajabi, Enayat Midha, Rishi de Souza, Jairo Francisco |
author_facet | Rajabi, Enayat Midha, Rishi de Souza, Jairo Francisco |
author_sort | Rajabi, Enayat |
collection | PubMed |
description | The majority of available datasets in open government data are statistical. They are widely published by various governments to be used by the public and data consumers. However, most open government data portals do not provide the five-star Linked Data standard datasets. The published datasets are isolated from one another while conceptually connected. This paper constructs a knowledge graph for the disease-related datasets of a Canadian government data portal, Nova Scotia Open Data. We leveraged the Semantic Web technologies to transform the disease-related datasets into Resource Description Framework (RDF) and enriched them with semantic rules. An RDF data model using the RDF Cube vocabulary was designed in this work to develop a graph that adheres to best practices and standards, allowing for expansion, modification and flexible re-use. The study also discusses the lessons learned during the cross-dimensional knowledge graph construction and integration of open statistical datasets from multiple sources. |
format | Online Article Text |
id | pubmed-10111831 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-101118312023-04-19 Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets Rajabi, Enayat Midha, Rishi de Souza, Jairo Francisco J Biomed Semantics Research The majority of available datasets in open government data are statistical. They are widely published by various governments to be used by the public and data consumers. However, most open government data portals do not provide the five-star Linked Data standard datasets. The published datasets are isolated from one another while conceptually connected. This paper constructs a knowledge graph for the disease-related datasets of a Canadian government data portal, Nova Scotia Open Data. We leveraged the Semantic Web technologies to transform the disease-related datasets into Resource Description Framework (RDF) and enriched them with semantic rules. An RDF data model using the RDF Cube vocabulary was designed in this work to develop a graph that adheres to best practices and standards, allowing for expansion, modification and flexible re-use. The study also discusses the lessons learned during the cross-dimensional knowledge graph construction and integration of open statistical datasets from multiple sources. BioMed Central 2023-04-18 /pmc/articles/PMC10111831/ /pubmed/37072859 http://dx.doi.org/10.1186/s13326-023-00284-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Rajabi, Enayat Midha, Rishi de Souza, Jairo Francisco Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets |
title | Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets |
title_full | Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets |
title_fullStr | Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets |
title_full_unstemmed | Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets |
title_short | Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets |
title_sort | constructing a knowledge graph for open government data: the case of nova scotia disease datasets |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10111831/ https://www.ncbi.nlm.nih.gov/pubmed/37072859 http://dx.doi.org/10.1186/s13326-023-00284-w |
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