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Towards the Integration of Agricultural Data from Heterogeneous Sources: Perspectives for the French Agricultural Context Using Semantic Technologies
Sustainable agriculture is crucial to society since it aims at supporting the world’s current food needs without compromising future generations. Recent developments in Smart Agriculture and Internet of Things have made possible the collection of unprecedented amounts of agricultural data with the g...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7225512/ http://dx.doi.org/10.1007/978-3-030-49165-9_8 |
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author | Jiang, Shufan Angarita, Rafael Chiky, Raja Cormier, Stéphane Rousseaux, Francis |
author_facet | Jiang, Shufan Angarita, Rafael Chiky, Raja Cormier, Stéphane Rousseaux, Francis |
author_sort | Jiang, Shufan |
collection | PubMed |
description | Sustainable agriculture is crucial to society since it aims at supporting the world’s current food needs without compromising future generations. Recent developments in Smart Agriculture and Internet of Things have made possible the collection of unprecedented amounts of agricultural data with the goal of making agricultural processes better and more efficient, and thus supporting sustainable agriculture. These data coming from different types of IoT devices can also be combined with relevant information published in online social networks and on the Web in the form of textual documents. Our objective is to integrate such heterogeneous data into knowledge bases that can support farmers in their activities, and to present global, real-time and comprehensive information to researchers. Semantic technologies and linked data provide a possibility for data integration and for automatic information extraction. This paper aims to give a brief review on the current semantic web technology applications for agricultural corpus, then to discuss the limits and potentials in construction and maintenance of existing ontologies in agricultural domain. |
format | Online Article Text |
id | pubmed-7225512 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-72255122020-05-15 Towards the Integration of Agricultural Data from Heterogeneous Sources: Perspectives for the French Agricultural Context Using Semantic Technologies Jiang, Shufan Angarita, Rafael Chiky, Raja Cormier, Stéphane Rousseaux, Francis Advanced Information Systems Engineering Workshops Article Sustainable agriculture is crucial to society since it aims at supporting the world’s current food needs without compromising future generations. Recent developments in Smart Agriculture and Internet of Things have made possible the collection of unprecedented amounts of agricultural data with the goal of making agricultural processes better and more efficient, and thus supporting sustainable agriculture. These data coming from different types of IoT devices can also be combined with relevant information published in online social networks and on the Web in the form of textual documents. Our objective is to integrate such heterogeneous data into knowledge bases that can support farmers in their activities, and to present global, real-time and comprehensive information to researchers. Semantic technologies and linked data provide a possibility for data integration and for automatic information extraction. This paper aims to give a brief review on the current semantic web technology applications for agricultural corpus, then to discuss the limits and potentials in construction and maintenance of existing ontologies in agricultural domain. 2020-04-29 /pmc/articles/PMC7225512/ http://dx.doi.org/10.1007/978-3-030-49165-9_8 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Jiang, Shufan Angarita, Rafael Chiky, Raja Cormier, Stéphane Rousseaux, Francis Towards the Integration of Agricultural Data from Heterogeneous Sources: Perspectives for the French Agricultural Context Using Semantic Technologies |
title | Towards the Integration of Agricultural Data from Heterogeneous Sources: Perspectives for the French Agricultural Context Using Semantic Technologies |
title_full | Towards the Integration of Agricultural Data from Heterogeneous Sources: Perspectives for the French Agricultural Context Using Semantic Technologies |
title_fullStr | Towards the Integration of Agricultural Data from Heterogeneous Sources: Perspectives for the French Agricultural Context Using Semantic Technologies |
title_full_unstemmed | Towards the Integration of Agricultural Data from Heterogeneous Sources: Perspectives for the French Agricultural Context Using Semantic Technologies |
title_short | Towards the Integration of Agricultural Data from Heterogeneous Sources: Perspectives for the French Agricultural Context Using Semantic Technologies |
title_sort | towards the integration of agricultural data from heterogeneous sources: perspectives for the french agricultural context using semantic technologies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7225512/ http://dx.doi.org/10.1007/978-3-030-49165-9_8 |
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